@misc{BuergerFloresAlsinaArellanoGarciaetal., author = {B{\"u}rger, Patrick and Flores-Alsina, Xavier and Arellano-Garc{\´i}a, Harvey and Gernaey, Krist V.}, title = {Improved Prediction of Phosphorus Dynamics in Biotechnological Processes by Considering Precipitation and Polyphosphate Formation: A Case Study on Antibiotic Production with Streptomyces coelicolor}, series = {Industrial \& engineering chemistry research}, volume = {57}, journal = {Industrial \& engineering chemistry research}, issn = {1520-5045}, doi = {10.1021/acs.iecr.7b05249}, abstract = {Improved Prediction of Phosphorus Dynamics in Biotechnological Processes by Considering Precipitation and Polyphosphate Formation: A Case Study on Antibiotic Production with Streptomyces coelicolor}, language = {en} } @misc{BaenaMorenoGonzalezCastanoArellanoGarciaetal., author = {Baena-Moreno, Francisco Manuel and Gonz{\´a}lez-Casta{\~n}o, Miriam and Arellano-Garc{\´i}a, Harvey and Ramirez Reina, Tomas}, title = {Exploring profitability of bioeconomy paths: Dimethyl ether from biogas as case study}, series = {Energy}, volume = {225}, journal = {Energy}, issn = {0360-5442}, doi = {10.1016/j.energy.2021.120230}, pages = {9}, abstract = {Herein a novel path is analysed for its economic viability to synergize the production of biomethane and dimethyl ether from biogas. We conduct a profitability analysis based on the discounted cash flow method. The results revealed an unprofitable process with high cost/revenues ratios. Profitable scenarios would be reached by setting prohibitive DME prices (1983-5566 €/t) or very high feed-in tariffs subsidies (95.22 €/MWh in the best case scenario). From the cost reduction side, the analysis revealed the need of reducing investment costs. For this purpose, we propose a percentage of investment as incentive scheme. Although the size increase benefits cost/revenues ratio, only the 1000 m3/h biogas plant size will reach profitability if 90\% of the investment is subsidized. A sensitivity analysis to check the influence of some important economical parameters is also included. Overall this study evidences the big challenge that our society faces in the way towards a circular economy.}, language = {en} } @misc{GonzalezCastanoSacheBerryetal., author = {Gonz{\´a}lez-Casta{\~n}o, Miriam and Sach{\´e}, Estelle le and Berry, Cameron and Pastor-P{\´e}rez, Laura and Arellano-Garc{\´i}a, Harvey and Wang, Qiang and Ramirez Reina, Tomas}, title = {Nickel Phosphide Catalysts as Efficient Systems for CO2 Upgrading via Dry Reforming of Methane}, series = {Catalysts}, volume = {11}, journal = {Catalysts}, number = {4}, issn = {2073-4344}, doi = {10.3390/catal11040446}, abstract = {This work establishes the primordial role played by the support's nature when aimed at the constitution of Ni2P active phases for supported catalysts. Thus, carbon dioxide reforming of methane was studied over three novel Ni2P catalysts supported on Al2O3, CeO2 and SiO2-Al2O3 oxides. The catalytic performance, shown by the catalysts' series, decreased according to the sequence: Ni2P/Al2O3 > Ni2P/CeO2 > Ni2P/SiO2-Al2O3. The depleted CO2 conversion rates discerned for the Ni2P/SiO2-Al2O3 sample were associated to the high sintering rates, large amounts of coke deposits and lower fractions of Ni2P constituted in the catalyst surface. The strong deactivation issues found for the Ni2P/CeO2 catalyst, which also exhibited small amounts of Ni2P species, were majorly associated to Ni oxidation issues. Along with lower surface areas, oxidation reactions might also affect the catalytic behaviour exhibited by the Ni2P/CeO2 sample. With the highest conversion rate and optimal stabilities, the excellent performance depicted by the Ni2P/Al2O3 catalyst was mostly related to the noticeable larger fractions of Ni2P species established}, language = {en} } @misc{GonzalezCastanoNavarrodeMiguelSinhaetal., author = {Gonz{\´a}lez-Casta{\~n}o, Miriam and Navarro de Miguel, Juan Carlos and Sinha, F. and Ghomsi Wabo, Samuel and Klepel, Olaf and Arellano-Garc{\´i}a, Harvey}, title = {Cu supported Fe-SiO2 nanocomposites for reverse water gas shift reaction}, series = {Journal of CO2 Utilization}, volume = {46}, journal = {Journal of CO2 Utilization}, issn = {2212-9820}, doi = {10.1016/j.jcou.2021.101493}, pages = {8}, abstract = {This work analyses the catalytic activity displayed by Cu/SiO2, Cu-Fe/SiO2 and Cu/FSN (Fe-SiO2 nanocomposite) catalysts for the Reverse Water Gas Shift reaction. Compared to Cu/SiO2 catalyst, the presence of Fe resulted on higher CO's selectivity and boosted resistances against the constitution of the deactivation carbonaceous species. Regarding the catalytic performance however, the extent of improvement attained through incorporation Fe species strongly relied on the catalysts' configuration. At 30 L/gh and H2:CO2 ratios = 3, the performance of the catalysts' series increased according to the sequence: Cu/SiO2 < Cu-Fe/SiO2 << Cu/FSN. The remarkable catalytic enhancements provided by Fe-SiO2 nanocomposites under different RWGS reaction atmospheres were associated to enhanced catalyst surface basicity's and stronger Cu-support interactions. The catalytic promotion achieved by Fe-SiO2 nanocomposites argue an optimistic prospective for nanocomposite catalysts within future CO2-valorising technologies.}, language = {en} } @misc{GonzalezCastanoIvanovaIoanidesetal., author = {Gonz{\´a}lez-Casta{\~n}o, Miriam and Ivanova, Svetlana and Ioanides, Theophiles and Centeno, Miguel Angel and Arellano-Garc{\´i}a, Harvey and Odriozola, Jos{\´e} Antonio}, title = {Zr and Fe on Pt/CeO2-MOx/Al2O3 catalysts for WGS reaction}, series = {International Journal of Energy Research}, journal = {International Journal of Energy Research}, issn = {1099-114X}, doi = {10.1002/er.6646}, pages = {12}, abstract = {By evaluating the functional modifications induced by Zr and Fe as dopants in Pt/CeO2-MOx/Al2O3 catalysts (M = Fe and Zr), the key features for improving water gas shift (WGS) performance for these systems have been addressed. Pt/ceria intrinsic WGS activity is often related to improved H2 surface dynamics, H2O absorption, retentions and dissociation capacities which are influenced greatly by the support nature. Two metals, iron and zirconia, were chosen as ceria dopants in this work, either in separate manner or combined. Iron incorporation resulted in CO-redox properties and oxygen storage capacities (OSC) improvement but the formation of Ce-Fe solid solutions did not offer any catalytic benefit, while the Zr incorporation influenced in a great manner surface electron densities and shows higher catalytic activity. When combined both metals showed an important synergy evidenced by 30\% higher CO conversions and attributed to greater surface electron densities population and therefore absorption and activity. This work demonstrates that for Pt/ceria catalysts OSC enhancement does not necessarily imply a catalytic promotion.}, language = {en} } @misc{GonzalezCastanoDorneanuArellanoGarcia, author = {Gonz{\´a}lez-Casta{\~n}o, Miriam and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {The Reverse Water Gas Shift Reaction: A Process Systems Engineering Perspective}, series = {Reaction Chemistry \& Engineering}, journal = {Reaction Chemistry \& Engineering}, issn = {2058-9883}, doi = {10.1039/D0RE00478B}, abstract = {The catalytic reduction of CO2 into value-added products has been considered a compelling solution for alleviating global warming and energy crises. The reverse water gas shift (RWGS) reaction plays a pivotal role among the various CO2 utilization approaches, due to the fact that it produces syngas, the building block of numerous conversion processes. Although a lot of work has been carried out towards the development of a RWGS process, ranging from efficient catalytic systems to reactor units, and even pilot scale processes, there is still a lack of understanding of the fundamental phenomena that take place at the various levels and scales of the process. This contribution presents the main solutions and remaining challenges for a structured, trans- and multidisciplinary framework in which catalysis engineering and process systems engineering can work together to incorporate understanding and methods from both sides, to accelerate the investigation, creation and operation of an efficient industrial CO2 conversion process based on the RWGS reaction.}, language = {en} } @misc{GonzalezAriasGonzalezCastanoArellanoGarciaetal., author = {Gonz{\´a}lez-Arias, Judith and Gonz{\´a}lez-Casta{\~n}o, Miriam and Arellano-Garc{\´i}a, Harvey and Lichtfouse, Eric and Zhang, Zhien}, title = {Unprofitability of small biogas plants without subsidies in the Brandenburg region}, series = {Environmental Chemistry Letters}, journal = {Environmental Chemistry Letters}, issn = {1610-3661}, doi = {10.1007/s10311-020-01175-7}, pages = {7}, abstract = {The circular economy is calling for the rapid use of already-developed renewable energies. However, the successful implementation of those new fuels is limited by economic and political issues. For instance, in the Brandenburg region, Germany, biogas production from anaerobic digestion of biomass and wastes is a current alternative. However, the upgrading biogas to biomethane is still challenging and the economic viability is unknown. Therefore, we performed an economic analysis for biogas upgrading to biomethane in the Brandenburg region. Five biogas plant sizes were analyzed by the method of discounted cash flow. This method yields the net present value of the projects, thus revealing the profitability or non-profitability of the plants. Results indicate profitable outputs for medium and large plants, with net present values between 415 and 7009 k€. However, the smallest plants have net present values from -4250 to -3389 k€, thus needing further economic efforts or subsidies to reach profitability. Indeed, biomethane prices should range between 52.1 and 95.6 €/MWh to make these projects profitable. Combinations of 50\% of investment subsidized and 11.5 €/MWh feed-in tariffs subsidies could make the projects reach profitability. These findings reveal that political actions such as green policies and subsidies are needed to implement green energy. This case study should serve as a potential tool for policy-makers toward a sustainable bioeconomy.}, language = {en} } @misc{BaenaMorenoGonzalezCastanoNavarrodeMigueletal., author = {Baena-Moreno, Francisco Manuel and Gonz{\´a}lez-Casta{\~n}o, Miriam and Navarro de Miguel, Juan Carlos and Miah, Kamal Uddin Mohammad and Ossenbrink, Ralf and Odriozola, Jos{\´e} Antonio and Arellano-Garc{\´i}a, Harvey}, title = {Stepping toward Efficient Microreactors for CO2 Methanation: 3D Printed Gyroid Geometry}, series = {ACS Sustainable Chemistry \& Engineering}, volume = {9}, journal = {ACS Sustainable Chemistry \& Engineering}, number = {24}, issn = {2168-0485}, doi = {10.1021/acssuschemeng.1c01980}, pages = {8198 -- 8206}, abstract = {This work presents a comparative study towards the development of efficient micro-reactors based on 3D-printed structures. Thus, the study evaluates the influence of the metal substrate geometry on the performance of structured catalysts for the CO2 methanation reaction. For this purpose, 0.5\%Ru-15\%Ni/MgAl2O4 catalyst is wash coated over two different micro-monolithic metal substrates: a conventional parallel channel honeycomb structure and a novel 3D-printed structure with a complex gyroid geometry. The effect of the metal substrate geometry is analyzed for several CO2 sources including ideal flue gas atmospheres, the presence of residual CH4 and CO in the flue gas, as well as simulated biogas sources. The advantages of the gyroid-3D complex geometries over the honeycomb structures are shown for all evaluated conditions, providing at the best-case scenario a 14\% improvement of CO2 conversion. Moreover, this contribution shows that systematically tailoring geometrical features of structured catalysts becomes an effective strategy to achieve improved catalysts performances independent of the flue gas composition. By enhancing the transport processes and the gas-catalyst interactions, the employed gyroid 3D metal substrates enable boosted CO2 conversions and greater CH4 selectivity within diffusional controlled regimes.}, language = {en} } @misc{GonzalezCastanoNavarrodeMiguelPernkovaetal., author = {Gonz{\´a}lez-Casta{\~n}o, Miriam and Navarro de Miguel, Juan Carlos and Pernkova, A. and Centeno, Miguel Angel and Odriozola, Jos{\´e} Antonio and Arellano-Garc{\´i}a, Harvey}, title = {Ni/YMnO3 perovskite catalyst for CO2 methanation}, series = {Applied Materials Today}, volume = {23}, journal = {Applied Materials Today}, doi = {10.1016/j.apmt.2021.101055}, abstract = {Ni/YMnO3 perovskite catalyst for CO2 methanation}, language = {en} } @misc{GonzalezCastanoGonzalezAriasSanchezetal., author = {Gonz{\´a}lez-Casta{\~n}o, Miriam and Gonz{\´a}lez-Arias, Judith and S{\´a}nchez, Marta Elena and Cara-Jim{\´e}nez, Jorge and Arellano-Garc{\´i}a, Harvey}, title = {Syngas production using CO2-rich residues: From ideal to real operating conditions}, series = {Journal of CO2 utilization}, volume = {52}, journal = {Journal of CO2 utilization}, issn = {2212-9839}, doi = {10.1016/j.jcou.2021.101661}, pages = {10}, language = {en} } @misc{GonzalezAriasGonzalezCastanoSanchezetal., author = {Gonz{\´a}lez-Arias, Judith and Gonz{\´a}lez-Casta{\~n}o, Miriam and S{\´a}nchez, Marta Elena and Cara-Jim{\´e}nez, Jorge and Arellano-Garc{\´i}a, Harvey}, title = {Valorization of biomass-derived CO2 residues with Cu-MnOx catalysts for RWGS reaction}, series = {Renewable Energy}, journal = {Renewable Energy}, number = {182}, issn = {1879-0682}, doi = {10.1016/j.renene.2021.10.029}, pages = {443 -- 451}, abstract = {This study delivers useful understanding towards the design of effective catalytic systems for upgrading real CO2erich residual streams derived from biomass valorization. Within this perspective, a catalysts' series based on (5 wt\%) Cu - (X wt\%) Mn/Al2O3with X¼0, 3, 8, and 10 is employed. The improved catalyst performance achieved through Mn incorporation is ascribed to enhanced Cu dispersions and promoted surface basic concentrations. Under standard RWGS conditions, the highest reaction rates achieved by(5 wt\%) Cu - (8 wt\%) Mn/Al2O3catalyst were associated to improved Cu dispersions along with the constitution of highly active Cu-MnOxdomains. Remarkably, variations on the optimal Cu to Mn ratios were detected as a function of the RWGS reaction conditions. Thus, under simulated CO2-rich residual feedstock's, i.e., in presence of CO and CH4, the further promotion on the Cu dispersion attained by the larger amounts of MnOxrendered the (5 wt\%) Cu - (10 wt\%) Mn/Al2O3catalyst as the best performing sample. Overall, the presented outcomes underline operative strategies for developing catalytic systems with advanced implementation potentialities.}, language = {en} } @misc{GonzalezCastanoNavarrodeMiguelBoelteetal., author = {Gonzalez-Castano, Miriam and Navarro de Miguel, Juan Carlos and Boelte, Jens-H. and Centeno, Miguel Angel and Klepel, Olaf and Arellano-Garc{\´i}a, Harvey}, title = {Assessing the impact of textural properties in Ni-Fe catalysts for CO2 methanation performance}, series = {Microporous and Mesoporous Materials}, volume = {327}, journal = {Microporous and Mesoporous Materials}, issn = {1387-1811}, doi = {10.1016/j.micromeso.2021.111405}, pages = {7}, abstract = {In heterogeneous catalysis, the benefits of employing adequate textural properties on the catalytic performances are usually stated. Nevertheless, the quantification of the extent of improvement is not an easy task since variations on the catalysts' specific areas and pore structures might involve modifications on a number of other surface catalytic features. This study establishes the impact of the catalyst textural properties on the CO2 methanation performance by investigating bimetallic Ni-Fe catalysts supported over carbon supports with different textural properties regarding surface area and pore structure. The comparable metal loading and dispersions attained for all systems enabled establishing forthright relationships between the catalyst textural properties and CO2 methanation rate. Once the influence of the external mass diffusions on the catalysts' performance was experimentally discarded, the estimated Thiele modulus and internal effectiveness (φ and ηEff) values showed that the catalyst performance was majorly governed by the surface reaction rate whilst the pore size affected in no significant manner within the examined range (Dpore = 10.2 to 5.8 nm). Therefore, the rapport between the catalyst performance and surface area was quantified for the CO2 methanation reaction over Ni-Fe catalysts: increasing the surface area from 572 to 802 m2/g permit obtaining ca. 10\% higher CO2 conversions.}, language = {en} } @misc{GonzalezCastanoHaniKourGonzalezAriasetal., author = {Gonz{\´a}lez-Casta{\~n}o, Miriam and Hani Kour, M. and Gonz{\´a}lez-Arias, Judith and Baena-Moreno, Francisco Manuel and Arellano-Garc{\´i}a, Harvey}, title = {Promoting bioeconomy routes: From food waste to green biomethane. A profitability analysis based on a real case study in eastern Germany}, series = {Journal of Environmental Management}, volume = {300}, journal = {Journal of Environmental Management}, issn = {0301-4797}, doi = {10.1016/j.jenvman.2021.113788}, abstract = {Profitability studies are needed to establish the potential pathways required for viable biomethane production in the Brandenburg region of Germany. This work study the profitability of a potential biomethane production plant in the eastern German region of Brandenburg, through a specific practical scenario with data collected from a regional biogas plant located in Alteno (Schradenbiogas GmbH \& Co. KG). Several parameters with potential economic influence such as distance of the production point to the grid, waste utilization percentage, and investment, were analyzed. The results illustrate a negative overall net present value with the scenario of no governmental investment, even when considering trading the CO2 obtained throughout the process. Subsidies needed to reach profitability varied with distance from 13.5 €/MWh to 19.3 €/MWh. For a fixed distance of 15 kms, the importance of percentage of waste utilization was examined. Only 100\% of waste utilization and 75\% of waste utilization would reach profitability under a reasonable subsidies scheme (16.3 and 18.8 €/MWh respectively). Concerning the importance of investment, a subsidized investment of at least 70\% is demanded for positive net present values. Besides, the sensitivity analysis remarks the energy consumption of the biogas upgrading stage, the electricity price, and the energy consumption of biogas production as major parameters to be tackled for the successful implementation of biogas upgrading plants. The results here obtained invite to ponder about potential strategies to further improve the economic viability of this kind of renewable projects. In this line, using the CO2 separated to produce added-value chemicals can be an interesting alternative.}, language = {en} } @misc{GonzalezAriasBaenaMorenoGonzalezCastanoetal., author = {Gonz{\´a}lez-Arias, Judith and Baena-Moreno, Francisco Manuel and Gonz{\´a}lez-Casta{\~n}o, Miriam and Arellano-Garc{\´i}a, Harvey}, title = {Economic approach for CO2 valorization from hydrothermal carbonization gaseous streams via reverse water-gas shift reaction}, series = {Fuel}, volume = {313}, journal = {Fuel}, issn = {0016-2361}, doi = {10.1016/j.fuel.2021.123055}, pages = {1 -- 7}, abstract = {In this work the economic performance of valorizing the gaseous stream coming from hydrothermal carbonization (HTC) of olive tree pruning is presented as a novel strategy to improve the competitiveness of HTC. The valorization of the commonly disregarded gaseous stream produced in this thermochemical treatment was proposed via the Reverse Water-Gas Shift reaction. This allows to obtain syngas for selling and therefore improving the overall economic performance of the process. To this end, three plant sizes were selected (312.5, 625 and 1250 kg/h of biomass processing). The parameters with a higher share in the total cost distribution along with the revenues from the hydrochar and the syngas selling were further evaluated. The results evidenced that with the assumptions taken, the overall process is still not profitable. To reach profitability, syngas selling prices between 2.2 and 3.4 €/m3 are needed, revealing that this proposal is not economically attractive. Alternatively, a lack of competitiveness in the current market is revealed with hydrochar selling prices between 0.41 and 0.64 €/kg to make the project profitable. The catalyst cost, sharing approximately 20\% of the total cost, is the parameter with the highest impact in the total economics of the process. The second one is the hydrogen price production, representing almost 16\% of the total. Investment subsidies are also examined as a potential tool to cover part of the initial investment. These results evidenced that further efforts and measures are needed to push forward in the path towards circular economy societies.}, language = {en} } @misc{TarifaGonzalezCastanoCazanaetal., author = {Tarifa, Pilar and Gonz{\´a}lez-Casta{\~n}o, Miriam and Caza{\~n}a, F. and Monz{\´o}n, Antonio and Arellano-Garc{\´i}a, Harvey}, title = {Development of one-pot Cu/cellulose derived carbon catalysts for RWGS reaction}, series = {Fuel}, volume = {Vol. 319}, journal = {Fuel}, issn = {0016-2361}, doi = {10.1016/j.fuel.2022.123707}, pages = {7}, abstract = {A series of Cu-based catalysts promoted with Fe, Ce and Al supported on cellulose derived carbon (CDC) was prepared by biomorphic mineralization technique for the RWGS reaction. The excellent Cu dispersions (7 nm at ca. 30 wt\% Cu) along with the resilience toward metal sintering attained in the entire catalysts series highlight one-pot decomposition of cellulose under reducing atmosphere as an excellent synthesis method which enable obtaining well-dispersed Cu nanoparticles. The influence of incorporating a second metal oxide over biomorphic mineralized Cu systems was also investigated. With the Cu-Ce system exhibiting the best catalyst performance of the catalysts' series, the enhanced catalyst performances were majorly ascribed to the catalysts redox properties. The lineal relationships stablished between oxygen exchange capacity and CO2 conversion rates remarks the employed sequential H2/CO2 cycles as an effective methodology for screening the catalytic performance of Cu catalysts for RWGS reaction.}, language = {en} } @misc{MahmoodGonzalezCastanoPenkovaetal., author = {Mahmood, Safdar and Gonz{\´a}lez-Casta{\~n}o, Miriam and Penkova, Anna and Centeno, Miguel Angel and Odriozola, Jos{\´e} Antonio and Arellano-Garc{\´i}a, Harvey}, title = {CO2 methanation on Ni/YMn1-xAlxO3 perovskite catalysts}, series = {Applied Materials Today}, volume = {29}, journal = {Applied Materials Today}, issn = {2352-9407}, doi = {10.1016/j.apmt.2022.101577}, pages = {1 -- 11}, abstract = {Seeking for advanced catalytic systems for the CO2 methanation reaction, the use of Ni supported catalysts over redox materials is often proposed. Profiting the superior redox properties described for layered perovskite systems, this work has investigated a series Ni supported YMn1-xAlxO3 (x = 0, 0.2, 0.5, 0.8, 1) perovskite catalysts. The obtained results evidenced the impact of the support nature on the systems redox properties and Ni-support interactions. Within the catalysts series, the greater methanation rates displayed by Ni/YMn0.5Al0.5O3 catalyst (0.748 mmolCO2,conv.s-1 gNi -1 at 400 ◦C and 60 L/gh) were associated to the interplay between the support redox properties and superior Ni dispersion. The improved redox behavior attained through the Al-incorporation (up to x = 0.5) was associated to the layered perovskite structures which, being distorted and constituted by smaller crystal sizes, facilitated the behavior of Mn redox couples as surface species readily interconverted. Exhibiting catalytic performances comparable to precious metals based catalysts, this work proposes the Ni/YMn0.5Al0.5O3 catalyst as an effective system for the CO2 methanation reaction.}, language = {en} } @misc{GonzalezCastanoBaenaMorenoNavarrodeMigueletal., author = {Gonz{\´a}lez-Casta{\~n}o, Miriam and Baena-Moreno, Francisco Manuel and Navarro de Miguel, Juan Carlos and Miah, Kamal Uddin Mohammad and Arroyo-Torralvo, F{\´a}tima and Ossenbrink, Ralf and Odriozola, Jos{\´e} Antonio and Benzinger, Walther and Hensel, Andreas and Wenka, Achim and Arellano-Garc{\´i}a, Harvey}, title = {3D-printed structured catalysts for CO2 methanation reaction: Advancing of gyroid-based geometries}, series = {Energy Conversion and Management}, volume = {258}, journal = {Energy Conversion and Management}, issn = {2590-1745}, doi = {10.1016/j.enconman.2022.115464}, pages = {8}, abstract = {This work investigates the CO2 methanation rate of structured catalysts by tuning the geometry of 3D-printed metal Fluid Guiding Elements (FGEs) structures based on periodically variable pseudo-gyroid geometries. The enhanced performance showed by the structured catalytic systems is mostly associated with the capability of the FGEs substrate geometries for efficient heat usages. Thus, variations on the channels diameter resulted in ca. 25\% greater CO2 conversions values at intermediate temperature ranges. The highest void fraction evidenced in the best performing catalyst (3D-1) favored the radial heat transfer and resulted in significantly enhanced catalytic activity, achieving close to equilibrium (75\%) conversions at 400 ◦C and 120 mL/min. For the 3D-1 catalyst, a mathematical model based on an experimental design was developed thus enabling the estimation of its behavior as a function of temperature, spatial velocity, hydrogen to carbon dioxide (H2/CO2) ratio, and inlet CO2 concentration. Its optimal operating conditions were established under 3 different scenarios: 1) no restrictions, 2) minimum H2:CO2 ratios, and 3) minimum temperatures and H2/CO2 ratio. For instance, for the lattest scenario, the best CO2 methanation conditions require operating at 431 ◦C, 200 mL/min, H2/CO2 = 3 M ratio, and inlet CO2 concentration = 10 \%.}, language = {en} } @misc{MappasVassiliadisDorneanuetal., author = {Mappas, Vassileios and Vassiliadis, Vassilios S. and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {Maintenance scheduling optimisation of Reverse Osmosis Networks (RONs) via a multistage Optimal Control reformulation}, series = {Desalination}, volume = {543}, journal = {Desalination}, issn = {1873-4464}, doi = {10.1016/j.desal.2022.116105}, abstract = {State-of-the-art approaches for membrane cleaning scheduling have focused on the Mixed-Integer Nonlinear Programming (MINLP) formulation so far, a strategy leading to a combinatorial problem that does not capture accurately the dynamic behaviour of the system. In this work, the Reverse Osmosis (RO) cleaning scheduling problem is solved using a novel approach based on the Multistage Integer Nonlinear Optimal Control Problem (MSINOCP) formulation. The approach produces an automated solution for the membrane cleaning scheduling, which also obviates the need for any form of combinatorial optimisation. Two different simulations, for 26 and 52 periods of operation (each period with a duration of one week), are carried out to illustrate the application of the proposed framework and the total cost is 1.17 and 2.48 10⁷ €, respectively. The RO network configuration considers 2 stages, each with 3 individual RO modules. The results show evidently that the new proposed solution framework can solve successfully this type of problems, even for large scale configurations, long time horizons and arbitrary realistic complexity of the underlying dynamic model of the RO process considered.}, language = {en} } @misc{CamposManriqueDorneanuetal., author = {Campos, Jean C. and Manrique, Jose and Dorneanu, Bogdan and Ipanaqu{\´e}, William and Arellano-Garc{\´i}a, Harvey}, title = {A smart decision framework for the prediction of thrips incidence in organic banana crops}, series = {Ecological Modelling}, volume = {473}, journal = {Ecological Modelling}, issn = {1872-7026}, doi = {10.1016/j.ecolmodel.2022.110147}, abstract = {Various pests which diminish the quality of the fruit have a big influence on the organic banana production in the Piura region of Peru (and not only) and prevent it from being sold on the international market. In this study, a framework for facilitating the prediction of the pest incidence in organic banana crops is developed. To achieve this, a data acquisition system with smart sensors is implemented to monitor the meteorological variables that influence the growth of the pests. The proposed framework is utilised for the assessment of various mathematical representations of the pest incidence. These models are adapted from population growth functions and built in such way as to predict the behaviour of the insects at non-regular time intervals. A hybrid approach, combining mechanistic and data-based methods is utilised for the development of the models. Both linear and nonlinear dynamic relationships with the temperature are assumed. The results show that nonlinear model representations have greater accuracy (a fit index of more than 70\%), which provides a basis for improving pest management actions on the organic banana farms.}, language = {en} } @misc{DorneanuZhangRuanetal., author = {Dorneanu, Bogdan and Zhang, Sushen and Ruan, Hang and Heshmat, Mohamed and Chen, Ruijuan and Vassiliadis, Vassilios S. and Arellano-Garc{\´i}a, Harvey}, title = {Big data and machine learning: A roadmap towards smart plants}, series = {Frontiers of Engineering Management}, volume = {9}, journal = {Frontiers of Engineering Management}, doi = {10.1007/s42524-022-0218-0}, pages = {623 -- 639}, abstract = {Industry 4.0 aims to transform chemical and biochemical processes into intelligent systems via the integration of digital components with the actual physical units involved. This process can be thought of as the addition of a central nervous system with a sensing and control monitoring of components and regulating the performance of the individual physical assets (processes, units, etc.) involved. Established technologies central to the digital integrating components are smart sensing, mobile communication, Internet of Things, modelling and simulation, advanced data processing, storage and analysis, advanced process control, artificial intelligence and machine learning, cloud computing, and virtual and augmented reality. An essential element to this transformation is the exploitation of large amounts of historical process data and large volumes of data generated in real-time by smart sensors widely used in industry. Exploitation of the information contained in these data requires the use of advanced machine learning and artificial intelligence technologies integrated with more traditional modelling techniques. The purpose of this paper is twofold: a) to present the state-of-the-art of the aforementioned technologies, and b) to present a strategic plan for their integration toward the goal of an autonomous smart plant capable of self-adaption and self-regulation for short- and long-term production management.}, language = {en} } @misc{DorneanuHeshmatMohamedetal., author = {Dorneanu, Bogdan and Heshmat, Mohamed and Mohamed, Abdelrahim and Arellano-Garc{\´i}a, Harvey}, title = {Monitoring of smart chemical processes: A Sixth Sense approach}, series = {Computer Aided Chemical Engineering}, volume = {49}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-323-85159-6.50226-8}, pages = {1357 -- 1362}, abstract = {This paper introduces the development of an intelligent monitoring and control framework for chemical processes, integrating the advantages of technologies such as Industry 4.0, cooperative control or fault detection via wireless sensor networks. The system described is able to detect faults using information on the process' structure and behaviour, information on the equipment and expert knowledge. Its integration with the monitoring system facilitates the detection and optimisation of controller actions. The results indicate that the proposed approach achieves high fault detection accuracy based on plant measurements, while the cooperative controller improves the operation of the process.}, language = {en} } @misc{YentumiDorneanuArellanoGarcia, author = {Yentumi, Richard and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {Mathematical modelling, simulation and optimisation of an indirect water bath heater at the Takoradi distribution station (TDS)}, series = {Computer Aided Chemical Engineering}, volume = {49}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-323-85159-6.50163-9}, pages = {979 -- 984}, abstract = {In this contribution, a dynamic first principles model of an existing 3.01 MW natural gas fired water bath heater (WBH) in operation at the Takoradi Distribution Station (TDS) in Ghana is developed primarily to predict the outlet temperature of the natural gas stream being heated. The model is intended to be applied during operations to provide useful data to optimise material and energy consumption, as well as minimise CO2 emissions. Due to the low thermal efficiencies of WBHs, even small improvements in efficiency can result in significant savings. The firetube and process coils are both modelled as onedimensional (1D) thin-walled tubes and the entire model incorporates mass and energy conservation equations, heat transfer rate relations and rigorous thermodynamic p-V-T relations. In contrast to what commonly exists in literature, this model accurately estimates the enthalpy change of the natural gas stream being heated by accounting for its enthalpy departure correction term due to pressure, in addition to the ideal gas heat capacity relation which is a function of only temperature. The coupled ordinary differential and algebraic equations are implemented using gPROMS® ModelBuilder® V4.2.0, a commercial modelling and simulation software. Verification of the model results showed good agreement between the model predictions and actual on field measurements. With excess air at 15\%, the simulation results closely approximate measured data with an absolute error of about 0.31 \%. More importantly, the results show that significant savings of up to 30\% per annum can be made through optimal operation of the water bath heater.}, language = {en} } @misc{DorneanuVassiliadisArellanoGarcia, author = {Dorneanu, Bogdan and Vassiliadis, Vassilios S. and Arellano-Garc{\´i}a, Harvey}, title = {Maintenance scheduling optimization for decaying performance nonlinear dynamic processes}, series = {Computer Aided Chemical Engineering}, volume = {49}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-323-85159-6.50084-1}, pages = {505 -- 510}, abstract = {A first contribution of this paper is an overview of the research efforts and contributions over several decades in the area of scheduling maintenance optimization for decaying performance dynamic processes. Following breakthrough ideas and implementation in the area of heat exchanger networks for optimal scheduling of cleaning actions subject to exchanger surface fouling, these concepts were transferred successfully to the area of scheduling catalyst replacement actions in catalytic reactor networks. This necessary overview leads to the main, second contribution aimed with this work: its application to restorative maintenance scheduling in the area of RON regeneration actions planning, as well as point to new areas where this approach can be fruitfully applied to and extended into in the near future - particularly enhancing model descriptions that include general types of planning uncertainty. The effectiveness and efficacy of the approach is demonstrated computationally in this work.}, language = {en} } @misc{SebastiaSaezHernandezArellanoGarciaetal., author = {Sebastia-Saez, Daniel and Hernandez, Leonor and Arellano-Garc{\´i}a, Harvey and Enrique Julia, Jose}, title = {Numerical and experimental characterization of the hydrodynamics and drying kinetics of a barbotine slurry spray}, series = {Chemical Engineering Science}, volume = {195}, journal = {Chemical Engineering Science}, issn = {1873-4405}, doi = {10.1016/j.ces.2018.11.040}, pages = {83 -- 94}, abstract = {Spray drying is a basic unit operation in several process industries such as food, pharmaceutical, ceramic, and others. In this work, a Eulerian-Lagrangian three-phase simulation is presented to study the drying process of barbotine slurry droplets for the production of ceramic tiles. To this end, the simulated velocity field produced by a spray nozzle located at the Institute of Ceramic Technology in Castell{\´o} (Spain) is benchmarked against measurements obtained by means of laser Doppler anemometry in order to validate the numerical model. Also, the droplet size distribution generated by the nozzle is obtained at operating conditions by means of laser diffraction and the data obtained are compared qualitatively to those found in the literature. The characteristic Rosin-Rammler droplet size from the distribution is introduced thereafter in the three-phase simulation to analyse the drying kinetics of individual droplets. The model predicts the theoretical linear evolution of the square diameter (D²-law), and the temperature and mass exchange with the environment. The proposed model is intended to support the design and optimization of industrial spray dryers.}, language = {en} } @misc{FosterSebastiaSaezArellanoGarcia, author = {Foster, Niall and Sebastia-Saez, Daniel and Arellano-Garc{\´i}a, Harvey}, title = {Fractal branch-like fractal shell-and-tube heat exchangers: A CFD study of the shell side performance}, series = {IFAC-PapersOnLine}, volume = {52}, journal = {IFAC-PapersOnLine}, number = {1}, issn = {2405-8963}, doi = {10.1016/j.ifacol.2019.06.044}, pages = {100 -- 105}, abstract = {Nature has provided some of the most ingenious and elegant solutions to complex problems over millions of years of refining through evolution. The adaptation of Nature´s solutions to engineering problems is a recent trend which has opened opportunities for improvement in many areas ranging from Architecture to Chemical Engineering. In particular, the use of fractal geometries on heat exchangers is a recent design trend. Recent investigations highlight the benefit of implementing fractal-based geometries on the tube side of shell and tube heat exchangers. A complete evaluation of such devices by assessing the performance of the shell side has not been undertaken, though. Here, we present a systematic numerical assessment of the shell side of a tree-like shaped heat exchanger. Key performance parameters, i.e. temperature change, pressure drop and coefficient of performance, are obtained and compared to those of a straight tube, in order to fully understand the potential of the application of fractal-based shapes to the design of heat exchangers.}, language = {en} } @misc{DorneanuMashamMechlerietal., author = {Dorneanu, Bogdan and Masham, Elliot and Mechleri, Evgenia and Arellano-Garc{\´i}a, Harvey}, title = {Centralised versus localised supply chain management using a flow configuration model}, series = {Computer Aided Chemical Engineering}, volume = {46}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-12-818634-3.50231-9}, pages = {1381 -- 1386}, abstract = {Traditional food supply chains are often centralised and global in nature. Moreover they require a large amount of resource which is an issue in a time with increasing need for more sustainable food supply chains. A solution is to use localised food supply chains, an option theorised to be more sustainable, yet not proven. Therefore, this paper compares the two systems to investigate which one is more environmentally friendly, cost efficient and resilient to disruption risks. This comparison between the two types of supply chains, is performed using MILP models for an ice cream supply chain for the whole of England over the period of a year. The results obtained from the models show that the localised model performs best environmentally and economically, whilst the traditional, centralised supply chain performs best for resilience.}, language = {en} } @misc{YentumiDorneanuArellanoGarcia, author = {Yentumi, Richard and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {Modelling and optimal operation of a natural gas fired natural draft heater}, series = {Computer Aided Chemical Engineering}, volume = {46}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-12-818634-3.50165-X}, pages = {985 -- 990}, abstract = {Current industrial trends promote reduction of material and energy consumption of fossil fuel burning, and energy-intensive process equipment. It is estimated that approximately 75\% of the energy consumption in hydrocarbon processing facilities is used by such equipment as fired heater, hence even small improvements in the energy conservation may lead to significant savings [1, 2]. In this work, a mathematical modelling and optimisation study is undertaken using gPROMS® ProcessBuilder® to determine the optimal operating conditions of an existing API 560 Type-E vertical-cylindrical type natural draft fired heater, in operation at the Atuabo Gas Processing Plant (GPP), in the Western Region of Ghana. It is demonstrated that the optimisation results in significant reduction of fuel gas consumption and operational costs.}, language = {en} } @misc{AlHmoudSebastiaSaezArellanoGarcia, author = {Al-Hmoud, Aya and Sebastia-Saez, Daniel and Arellano-Garc{\´i}a, Harvey}, title = {Comparative CFD analysis of thermal energy storage materials in photovoltaic/thermal panels}, series = {Computer Aided Chemical Engineering}, volume = {46}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-12-818634-3.50133-8}, pages = {793 -- 798}, abstract = {Photovoltaic/thermal systems are a novel renewable energy approach to transform incident radiation into electricity and simultaneously store the excess thermal energy produced. Both sensible and latent heat storage materials have been investigated in the past for thermal storage; with desert sand having been recently considered as an efficient and inexpensive alternative. In this work, we use a transient Computational Fluid Dynamics simulation to compare the performance of desert sand to that of well-established phase-change materials used in photovoltaic/thermal systems. The simulation gives as a result the temperature profiles within the device as well as the time evolution of the charge/discharge cycles when using PCMs. The results show the suitability of desert sand as a thermal storage material to be used in photovoltaic/thermal systems.}, language = {en} } @misc{MechleriSidnellDorneanuetal., author = {Mechleri, Evgenia and Sidnell, Tim and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {Optimisation and control of a distributed energy resource network using Internet-of-Things technologies}, series = {Computer Aided Chemical Engineering}, volume = {46}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-12-818634-3.50014-X}, pages = {79 -- 84}, abstract = {This work investigates the use of variable pricing to control electricity imported and exported to and from both fixed and unfixed distributed energy resource network designs within the UK residential sector. It was proven that networks which utilise much of their own energy and import little from the national grid are barely affected by variable import pricing, but are encouraged to export more energy to the grid by dynamic export pricing. Dynamic import and export pricing increased CO2 emissions due to feed-in tariffs which encourages CHP generation over lower-carbon technologies such as solar panels or wind turbines.}, language = {en} } @misc{ArellanoGarciaDorneanuMechleri, author = {Arellano-Garc{\´i}a, Harvey and Dorneanu, Bogdan and Mechleri, Evgenia}, title = {Devicification of Food Process Engineering}, series = {Reference Module in Chemistry, Molecular Sciences and Chemical Engineering}, volume = {2019}, journal = {Reference Module in Chemistry, Molecular Sciences and Chemical Engineering}, doi = {10.1016/B978-0-12-409547-2.14426-9}, abstract = {Food and beverages industry is facing major challenges in the years to come, as the world population is expected to grow, accompanied by a growing need for energy, feed and fuel. Much of the processing in the food industry is performed in small-scale decentralized plants, with relatively few possibilities of energy recovery. Innovation in areas such as process and product modeling, process intensification and process control enable the development of new manufacturing pathways, more efficient, versatile, selective and sustainable. Furthermore, the addition of Internet of Things elements and the way they connect to the physical process will ensure continuous communication between the various actors of the food value chain. This will enable the design of new compact, scalable, flexible, modular, and automated production equipment that will offer food manufacturers the ability to respond rapidly, economically, accurately and flexibly to the consumer demands.}, language = {en} } @misc{ArellanoGarciaIfeSanduketal., author = {Arellano-Garc{\´i}a, Harvey and Ife, Maximilian R. and Sanduk, Mohammed and Sebastia-Saez, Daniel}, title = {Hydrogen production via load-matched coupled solar-proton exchange membrane electrolysis using aqueous methanol}, series = {Chemical engineering \& technology}, volume = {42}, journal = {Chemical engineering \& technology}, number = {11}, issn = {1521-4125}, doi = {10.1002/ceat.201900285}, pages = {2340 -- 2347}, abstract = {This study investigates hydrogen production via a directly coupled solar-PEM electrolysis system using aqueous methanol instead of water. The effect of load matching and methanol concentration on hydrogen production rates, electrolysis efficiency, and solar-hydrogen efficiency was investigated. The electrolysis efficiencies were subsequently used in simulation studies to estimate production costs in scaled up systems. The results show that the added hydrogen production associated with the methanol solutions leads to favourable hydrogen production costs at smaller scales.}, language = {en} } @misc{SebastiaSaezRamirezReinaSilvaetal., author = {Sebastia-Saez, Daniel and Ramirez Reina, Tomas and Silva, Ravi and Arellano-Garc{\´i}a, Harvey}, title = {Synthesis and characterisation of n-octacosane@silica nanocapsules for thermal storage applications}, series = {International Journal of Energy Research}, volume = {44}, journal = {International Journal of Energy Research}, number = {3}, issn = {1099-114X}, doi = {10.1002/er.5039}, pages = {2306 -- 2315}, abstract = {This work reports the synthesis and characterisation of a core-shell n-octacosane@silica nanoencapsulated phase-change material obtained via interfacial hydrolysis and polycondensation of tetraethyl orthosilicate in miniemulsion. Silica has been used as the encapsulating material because of its thermal advantages relative to synthesised polymers. The material presents excellent heat storage potential, with a measured melting latent heat varying between 57.1 and 89.0 kJ kg-1 (melting point between 58.2°C and 59.9°C) and a small particle size (between 565 and 227 nm). Degradation of the n-octacosane core starts between 150°C and 180°C. Also, the use of silica as shell material gives way to a heat conductivity of 0.796 W m-1 K-1 (greater than that of nanoencapsulated materials with polymeric shell). Charge/discharge cycles have been successfully simulated at low pressure to prove the suitability of the nanopowder as phase-change material. Further research will be carried out in the future regarding the use of the synthesised material in thermal applications involving nanofluids.}, language = {en} } @misc{GehringDorneanuManriqueSilupuetal., author = {Gehring, Nicole and Dorneanu, Bogdan and Manrique-Silup{\´u}, Jos{\´e} and Ipanaqu{\´e}, William and Arellano-Garc{\´i}a, Harvey}, title = {Circular Economy in Banana Cultivation}, series = {Computer Aided Chemical Engineering}, volume = {48}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-12-823377-1.50262-7}, pages = {1567 -- 1572}, abstract = {This paper examines the most important approaches that could be applied for the introduction of circular economy strategies for the banana production process in the region of Piura (Peru). Based on this, a framework for an optimized economic cycle that is able to conserve resources and minimize the capital investments of farmers, while simultaneously increasing their production, can be created. Challenges and potential solutions are discussed for the production stages.}, language = {en} } @misc{HamdanSebastiaSaezHamdanetal., author = {Hamdan, Mustapha and Sebastia-Saez, Daniel and Hamdan, Malak and Arellano-Garc{\´i}a, Harvey}, title = {CFD Analysis of the Use of Desert Sand as Thermal Energy Storage Medium in a Solar Powered Fluidised Bed Harvesting Unit}, series = {Computer Aided Chemical Engineering}, volume = {48}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-12-823377-1.50059-8}, pages = {349 -- 354}, abstract = {This work presents an Euler-Euler hydrodynamic and heat transfer numerical analysis of the multiphase flow involving desert sand and a continuous gas phase in a compact-size fluidised bed. The latter is part of a novel conceptual solar power design intended for domestic use. Desert sand is a highly available and unused resource with suitable thermal properties to be employed as thermal energy storage medium. It also allows for high working temperatures owing to its high resistance to agglomeration. Computational Fluid Dynamics simulations are used here to assess the heat transfer between desert sand and several proposed working fluids (including air, argon, nitrogen and carbon dioxide) to justify the design in terms of equipment dimensions and suitability of the materials used. The results show that the device can provide up to 1,031 kW when using carbon dioxide as the heat transfer fluid.}, language = {en} } @misc{MenzhausenMerinoDorneanuetal., author = {Menzhausen, Robert and Merino, Manuel and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {A Fuzzy Control Approach for an Industrial Refrigeration System}, series = {Computer Aided Chemical Engineering}, volume = {48}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-12-823377-1.50210-X}, pages = {1255 -- 1260}, abstract = {This contribution presents the development of a model for the refrigeration plant used for mangos, which is able to simulate both the chamber and the fruit temperatures. The model is developed from energy balances for each section of the refrigeration system and the fruits, and is the basis for the setup of a fuzzy controller, capable of regulating continuously the compressor's frequency to achieve the desired temperature. The model is able to accurately predict the chamber temperature profiles, but is more sensitive when simulating the fruit temperature. The fuzzy controller is able to achieve the set-point more accurately and in a shorter time than the on/off control, achieving a decrease in energy consumption as well.}, language = {en} } @misc{ArellanoGarciaBarzDorneanuetal., author = {Arellano-Garc{\´i}a, Harvey and Barz, Tilman and Dorneanu, Bogdan and Vassiliadis, Vassilios S.}, title = {Real-time feasibility of nonlinear model predictive control for semi-batch reactors subject to uncertainty and disturbances}, series = {Computers \& Chemical Engineering}, volume = {133}, journal = {Computers \& Chemical Engineering}, issn = {1873-4375}, doi = {10.1016/j.compchemeng.2019.106529}, abstract = {This paper presents two nonlinear model predictive control based methods for solving closed-loop stochastic dynamic optimisation problems, ensuring both robustness and feasibility with respect to state output constraints. The first one is a new deterministic approach, using the wait-and-see strategy. The key idea is to specifically anticipate violation of output hard-constraints, which are strongly affected by instantaneous disturbances, by backing off of their bounds along the moving horizon. The second method is a stochastic approach to solve nonlinear chance-constrained dynamic optimisation problems under uncertainties. The key aspect is the explicit consideration of the stochastic properties of both exogenous and endogenous uncertainties in the problem formulation (here-and-now strategy). The approach considers a nonlinear relation between uncertain inputs and the constrained state outputs. The performance of the proposed methodologies is assessed via an application to a semi-batch reactor under safety constraints, involving strongly exothermic reactions.}, language = {en} } @misc{StephensonCarvalhoElleroSebastiaSaezetal., author = {Stephenson, Ted and Carvalho Ellero, Caio and Sebastia-Saez, Daniel and Klymenko, Oleksiy and Battley, Angela Maria and Arellano-Garc{\´i}a, Harvey}, title = {Numerical modelling of the interaction between eccrine sweat and textile fabric for the development of smart clothing}, series = {International Journal of Clothing Science and Technology}, volume = {32}, journal = {International Journal of Clothing Science and Technology}, number = {5}, issn = {0955-6222}, doi = {10.1108/IJCST-07-2019-0100}, pages = {761 -- 774}, abstract = {Purpose Live non-invasive monitoring of biomarkers is of great importance for the medical community. Moreover, some studies suggest that there is a substantial business gap in the development of mass-production commercial sweat-analysing wearables with great revenue potential. The objective of this work is to quantify the concentration of biomarkers that reaches the area of the garment where a sensor is positioned to advance the development of commercial sweat-analysing garments. Design/methodology/approach Computational analysis of the microfluidic transport of biomarkers within eccrine sweat glands provides a powerful way to explore the potential for quantitative measurements of biomarkers that can be related to the health and/or the physical activity parameters of an individual. The numerical modelling of sweat glands and the interaction of sweat with a textile layer remain however rather unexplored. This work presents a simulation of the production of sweat in the eccrine gland, reabsorption from the dermal duct into the surrounding skin and diffusion within an overlying garment. Findings The model represents satisfactorily the relationship between the biomarker concentration and the flow rate of sweat. The biomarker distribution across an overlying garment has also been calculated and subsequently compared to the minimum amount detectable by a sensor previously reported in the literature. The model can thus be utilized to check whether or not a given sensor can detect the minimum biomarker concentration threshold accumulated on a particular type of garment. Originality/value The present work presents to the best of our knowledge, the earliest numerical models of the sweat gland carried out so far. The model describes the flow of human sweat along the sweat duct and on to an overlying piece of garment. The model considers complex phenomena, such as reabsorption of sweat into the skin layers surrounding the duct, and the structure of the fibres composing the garment. Biomarker concentration maps are obtained to check whether sensors can detect the threshold concentration that triggers an electric signal. This model finds application in the development of smart textiles.}, language = {en} } @misc{BaenaMorenoCidCastilloArellanoGarciaetal., author = {Baena-Moreno, Francisco Manuel and Cid-Castillo, N. and Arellano-Garc{\´i}a, Harvey and Ramirez Reina, Tomas}, title = {Towards emission free steel manufacturing - Exploring the advantages of a CO2 methanation unit to minimize CO2 emissions}, series = {Science of The Total Environment}, volume = {781}, journal = {Science of The Total Environment}, issn = {1879-1026}, doi = {10.1016/j.scitotenv.2021.146776}, abstract = {This paper demonstrates the benefits of incorporating CO2 utilisation through methanation in the steel industry. This approach allows to produce synthetic methane, which can be recycled back into the steel manufacturing process as fuel and hence saving the consumption of natural gas. To this end, we propose a combined steel-making and CO2 utilisation prototype whose key units (shaft furnace, reformer and methanation unit) have been modelled in Aspen Plus V8.8. Particularly, the results showed an optimal performance of the shaft furnace at 800°C and 6 bar, as well as 1050°C and atmospheric pressure for the reformer unit. Optimal results for the methanation reactor were observed at 350°C. Under these optimal conditions, 97.8\% of the total CO2 emissions could be mitigated from a simplified steel manufacturing scenario and 89.4\% of the natural gas used in the process could be saved. A light economic approach is also presented, revealing that the process could be profitable with future technologic developments, natural gas prices and forthcoming increases of CO2 emissions taxes. Indeed, the cash-flow can be profitable (325 k€) under the future costs: methanation operational cost at 0.105 €/Nm³; electrolysis operational cost at 0.04 €kWh, natural gas price at 32 €/MWh; and CO2 penalty at 55€/MWh. Hence this strategy is not only environmentally advantageous but also economically appealing and could represent an interesting route to contribute towards steel-making decarbonisation.}, language = {en} } @misc{MechleriDorneanuArellanoGarcia, author = {Mechleri, Evgenia and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {A Model Predictive Control-Based Decision-Making Strategy for Residential Microgrids}, series = {Eng}, volume = {3}, journal = {Eng}, number = {1}, issn = {2673-4117}, doi = {10.3390/eng3010009}, pages = {100 -- 115}, abstract = {This work presents the development of a decision-making strategy for fulfilling the power and heat demands of small residential neighborhoods. The decision on the optimal operation of a microgrid is based on the model predictive control (MPC) rolling horizon. In the design of the residential microgrid, the new approach different technologies, such as photovoltaic (PV) arrays, micro-combined heat and power (micro-CHP) units, conventional boilers and heat and electricity storage tanks are considered. Moreover, electricity transfer between the microgrid components and the national grid are possible. The MPC problem is formulated as a mixed integer linear programming (MILP) model. The proposed novel approach is applied to two case studies: one without electricity storage, and one integrated microgrid with electricity storage. The results show the benefits of considering the integrated microgrid, as well as the advantage of including electricity storage.}, language = {en} } @misc{JurischkaDorneanuStollbergetal., author = {Jurischka, Constantin and Dorneanu, Bogdan and Stollberg, Christian and Arellano-Garc{\´i}a, Harvey}, title = {A novel approach to continuous extraction of active ingredients from essential oils through combined chromatography}, series = {Computer Aided Chemical Engineering}, volume = {51}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-323-95879-0.50129-6}, pages = {769 -- 774}, abstract = {This contribution introduces a combined liquid chromatography purification designed for a continuous and resource-efficient process, integrating the rotating columns and the simulated bed principles. The approach is demonstrated and validated based on bisabolol oxides A and B, which are effective ingredients with anti-inflammatory and spasmolytic effects, prepared from chamomile essential oil. The results show superior efficiency to the traditional selective methods for isolating ingredients from multicomponent mixtures, as well as reduction in resources and costs.}, language = {en} } @misc{EstradaManriqueSilupuIpanaqueetal., author = {Estrada, Carlos A. and Manrique-Silup{\´u}, Jos{\´e} and Ipanaqu{\´e}, William and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {A model-based approach for the prediction of banana rust thrips incidence from atmospheric variables}, series = {Computer Aided Chemical Engineering}, volume = {51}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-323-95879-0.50085-0}, pages = {505 -- 510}, abstract = {This work focuses on the development of a mathematical model for the population growth of banana red rust thrips (Chaetanaphothrips signipennis) based on a modified temperature-based growth rate with the addition of climatic variables, such as relative humidity, wind speed and rainfall rate. The aim is to enable better prediction of the pest incidence and improve decision making, productivity, as well as quantifying the influence of these variables on the development of red rust thrips. The developed model is then compared with current solutions for predicting the pest incidence, showing improved accuracy (higher than 67\%) versus experimental data, for which the state-of-the-art models indicate extremely poor fits.}, language = {en} } @misc{AmaoDorneanuArellanoGarcia, author = {Amao, Khalid and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {Economic Analysis of Novel Pathways for Recovery of Lithium Battery Waste}, series = {Computer Aided Chemical Engineering}, volume = {51}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-323-95879-0.50271-X}, pages = {1621 -- 1626}, abstract = {Using the Umicore process, a current state-of-the-art recycling in the metal recovery industry for lithium battery waste, as a baseline, this contribution examines economic and environmentally friendly solutions for effective metal recovery from spent LIBs. At the same time, possible synergies between existing resource use from other manufacturing and waste treatment industries are considered as valuable input to metal recycling, while also reducing the amount of atmospheric carbon. This further presents a case for possible integration of various waste management approaches as a single business unit for economic incentive and profitability for possible investment.}, language = {en} } @misc{DorneanuHeinzelmannSchnitzleinetal., author = {Dorneanu, Bogdan and Heinzelmann, Norbert and Schnitzlein, Klaus and Arellano-Garc{\´i}a, Harvey}, title = {A novel approach to modelling trickle bed reactors}, series = {Computer Aided Chemical Engineering}, volume = {51}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-323-95879-0.50047-3}, pages = {277 -- 282}, abstract = {In this contribution, the development of a toolbox for the simulation of trickle bed reactors based on a model able to account for the local properties of the liquid and gas flow in a packed bed at particle scale is introduced. The implementation uses a modular and flexible setup, with local liquid distribution considered as a function of the operating conditions and the physical properties of the three phases. Moreover, the impact of the local incomplete wetting on the conversion, as well as the mass transport and kinetics at both particle and reactor scale are accounted for. Furthermore, different particle geometries are considered, and the model is able to reliably predict the performance of the catalytic trickle bed reactors.}, language = {en} } @misc{CamposManriqueSilupuIpanaqueetal., author = {Campos, Jean C. and Manrique-Silup{\´u}, Jos{\´e} and Ipanaqu{\´e}, William and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {Mechanistic modelling for thrips incidence in organic banana}, series = {Computer Aided Chemical Engineering}, volume = {51}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-323-95879-0.50046-1}, pages = {271 -- 276}, abstract = {This contribution introduces a data acquisition and modelling framework for the prediction of banana pests' incidence. An IoT sensors-based system collects weather and micro-climate variables, such as temperature, relative humidity, and wind speed, which are uploaded in real time to a cloud storage space. The incidence of the red rust thrips (Chaetanaphothrips signipennis) is collected "manually" by periodic inspection. The mathematical model is adapted from population growth functions and a model of insect species development and allows predictions to be made at various time intervals with an accuracy greater than 80\%, improving decision-making capacity for agro-producers and enabling the improvement of pest management actions.}, language = {en} } @misc{KetabchiRamirezReinaDorneanuetal., author = {Ketabchi, Elham and Ramirez Reina, Tomas and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {An identification approach to a reaction network for an ABE catalytic upgrade}, series = {Computer Aided Chemical Engineering}, volume = {50}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-323-88506-5.50102-9}, pages = {643 -- 648}, abstract = {This contribution presents a kinetic study for the identification of the complex reaction mechanism occurring during the ABE upgrading, and the development of a kinetic model. Employing graph theory analysis, a directed bipartite graph is constructed to reduce the complexity of the reaction network, and the reaction rate constants and reaction orders are calculated using the initial rate method, followed by the calculation of the activation energy and frequency factor for an Arrhenius-type law. Subsequently, using general mass balancing a proposed mathematical model is produced to determine the apparent reaction rates, which are successfully in line with the experimental results.}, language = {en} } @misc{ClarkeDorneanuMechlerietal., author = {Clarke, Fiona and Dorneanu, Bogdan and Mechleri, Evgenia and Arellano-Garc{\´i}a, Harvey}, title = {Optimal design of heating and cooling pipeline networks for residential distributed energy resource systems}, series = {Energy}, volume = {235}, journal = {Energy}, issn = {1873-6785}, doi = {10.1016/j.energy.2021.121430}, abstract = {This paper presents a mixed integer linear programming model for the optimal design of a distributed energy resource (DER) system that meets electricity, heating, cooling and domestic hot water demands of a neighbourhood. The objective is the optimal selection of the system components among different technologies, as well as the optimal design of the heat pipeline network to allow heat exchange between different nodes in the neighbourhood. More specifically, this work focuses on the design, interaction and operation of the pipeline network, assuming the operation and maintenance costs. Furthermore, thermal and cold storage, transfer of thermal energy, and pipelines for transfer of cold and hot water to meet domestic hot water demands are additions to previously published models. The application of the final model is investigated for a case-study of a neighbourhood of five houses located in the UK. The scalability of the model is tested by also applying the model to a neighbourhood of ten and twenty houses, respectively. Enabling exchange of thermal power between the neighbours, including for storage purposes, and using separate hot and cold pipeline networks reduces the cost and the environmental impact of the resulting DER.}, language = {en} } @misc{SidnellDorneanuMechlerietal., author = {Sidnell, Tim and Dorneanu, Bogdan and Mechleri, Evgenia and Vassiliadis, Vassilios S. and Arellano-Garc{\´i}a, Harvey}, title = {Effects of Dynamic Pricing on the Design and Operation of Distributed Energy Resource Networks}, series = {Processes}, volume = {9}, journal = {Processes}, number = {8}, issn = {2227-9717}, doi = {https://doi.org/10.3390/pr9081306}, abstract = {This paper presents a framework for the use of variable pricing to control electricity im-ported/exported to/from both fixed and unfixed residential distributed energy resource (DER) network designs. The framework shows that networks utilizing much of their own energy, and importing little from the national grid, are barely affected by dynamic import pricing, but are encouraged to sell more by dynamic export pricing. An increase in CO2 emissions per kWh of energy produced is observed for dynamic import and export, against a baseline configuration utilizing constant pricing. This is due to feed-in tariffs (FITs) that encourage CHP generation over lower-carbon technologies. Furthermore, batteries are shown to be expensive in systems receiving income from FITs and grid exports, but for the cases when they sell to/buy from the grid using dynamic pricing, their use in the networks becomes more economical. Keywords: distributed energy resource (DER); dynamic pricing; mixed-integer linear programming (MILP); renewable heat incentive (RHI); feed-in tariff (FIT); electricity storage in batteries.}, language = {en} } @misc{SidnellClarkeDorneanuetal., author = {Sidnell, Tim and Clarke, Fiona and Dorneanu, Bogdan and Mechleri, Evgenia and Arellano-Garc{\´i}a, Harvey}, title = {Optimal design and operation of distributed energy resources systems for residential neighbourhoods}, series = {Smart Energy}, volume = {4}, journal = {Smart Energy}, issn = {2666-9552}, doi = {10.1016/j.segy.2021.100049}, abstract = {Different designs of distributed energy resources (DER) systems could lead to different performance in reducing cost, environmental impact or use of primary energy in residential networks. Hence, optimal design and management are important tasks to promote diffusion against the centralised grid. However, current operational models for such systems do not adequately analyse their complexity. This paper presents the results of a mixed-integer linear programming (MILP) model of distributed energy systems in the residential sector which builds up on previous work in this field. A superstructure optimisation model for design and operation of DER systems is obtained, providing a more holistic overview of such systems by including the following novel elements: a) Design and utilisation of a network with integrated heating/cooling pipelines and microgrid connections between neighbourhoods; b) Exploration of use of feed-in tariffs (FITs), renewable heat incentives (RHIs) and the ability to buy/sell from/to the national grid. It is shown that the (DER network mitigates around 30-40\% of the CO2 emissions per household, compared with "traditional generation". Money from FITs, RHIs and sales to the grid, as well as reduced grid purchases, make DER networks far more economical, and even profitable, compared to the traditional energy consumption.}, language = {en} } @misc{AnagnostopoulosSebastiaSaezCampbelletal., author = {Anagnostopoulos, Argyrios and Sebastia-Saez, Daniel and Campbell, Alasdair N. and Arellano-Garc{\´i}a, Harvey}, title = {Finite element modelling of the thermal performance of salinity gradient solar ponds}, series = {Energy}, volume = {203}, journal = {Energy}, issn = {1873-6785}, doi = {10.1016/j.energy.2020.117861}, abstract = {Solar ponds are a promising technology to capture and store solar energy. Accurate, reliable and versatile models are thus needed to assess the thermal performance of salinity gradient solar ponds. A CFD simulation set-up has been developed in this work to obtain a fully versatile model applicable to any practical scenario. Also, a comparison between the results obtained with an existing one-dimensional MATLAB model and the two- and three-dimensional CFD models developed in this work has been carried out to quantify the gain in accuracy and the increase in computational resources needed. The two and three-dimensional models achieve considerably higher accuracy than the 1-D model. They are subsequently found to accurately evaluate the heat loss to the surroundings, the irradiance absorbed by the solar pond and the thermal performance of the pond throughout the year. Two geographic locations: Bafgh (Iran) and Kuwait City, have been evaluated.}, language = {en} } @misc{DeMelDemisDorneanuetal., author = {De Mel, Ishanki and Demis, Panagiotis and Dorneanu, Bogdan and Klymenko, Oleksiy and Mechleri, Evgenia and Arellano-Garc{\´i}a, Harvey}, title = {Global Sensitivity Analysis for Design and Operation of Distributed Energy Systems}, series = {Computer Aided Chemical Engineering}, volume = {48}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-12-823377-1.50254-8}, pages = {1519 -- 1524}, abstract = {Distributed Energy Systems (DES) are set to play a vital role in achieving emission targets and meeting higher global energy demand by 2050. However, implementing these systems has been challenging, particularly due to uncertainties in local energy demand and renewable energy generation, which imply uncertain operational costs. In this work we are implementing a Mixed-Integer Linear Programming (MILP) model for the operation of a DES, and analysing impacts of uncertainties in electricity demand, heating demand and solar irradiance on the main model output, the total daily operational cost, using Global Sensitivity Analysis (GSA). Representative data from a case study involving nine residential areas at the University of Surrey are used to test the model for the winter season. Distribution models for uncertain variables, obtained through statistical analysis of raw data, are presented. Design results show reduced costs and emissions, whilst GSA results show that heating demand has the largest influence on the variance of total daily operational cost. Challenges and design limitations are also discussed. Overall, the methodology can be easily applied to improve DES design and operation.}, language = {en} } @misc{YusufFlagielloWardetal., author = {Yusuf, Ifrah and Flagiello, Fabio and Ward, Niel I. and Arellano-Garc{\´i}a, Harvey and Avignone-Rossa, Claudio and Felipe-Sotelo, Monica}, title = {Valorisation of banana peels by hydrothermal carbonisation: Potential use of the hydrochar and liquid by-product for water purification and energy conversion}, series = {Bioresource Technology Reports}, volume = {12}, journal = {Bioresource Technology Reports}, issn = {2589-014X}, doi = {10.1016/j.biteb.2020.100582}, abstract = {Banana peels were used as feedstock to produce a carbon dense hydrochar for the removal of toxic metals from wastewater. Compared to the biomass feedstock (41.3\% mass C), the banana peel hydrochar possesses higher carbon (54-72\% mass C) and lower ash contents. The carbonised banana peels treated between 150 and 300 °C (1-2h) demonstrated an excellent ability to remove Cd²⁺ (5-100 mg L⁻¹), achieving 99\% removal, in comparison with 75\% for the raw peel. The liquid by-product generated in the carbonisation process was tested as feedstock in microbial electrochemical devices, showing significant reduction in the chemical oxygen demand levels (initially 10-25 10³ mg L⁻¹), associated with the production of electrical outputs; 81-85\% reduction with microbial communities from compost, and 53-85\% with anaerobic sludge. The results demonstrate the complete utilization of waste from mass cultivation of banana, providing a full-cycle solution for the pollution associated to this important crop.}, language = {en} } @misc{DeCarvalhoMirandaFloresPonceArellanoGarciaetal., author = {De Carvalho Miranda, Julio Cesar and Flores Ponce, Gustavo Henrique Santos and Arellano-Garc{\´i}a, Harvey and Maciel Filho, Rubens and Wolf Maciel, Maria Regina}, title = {Process design and evaluation of syngas-to-ethanol conversion plants}, series = {Journal of Cleaner Production}, volume = {269}, journal = {Journal of Cleaner Production}, issn = {0959-6526}, doi = {10.1016/j.jclepro.2020.122078}, abstract = {Synthesis gas (syngas) is mostly known by its use on ammonia (Harber-Bosch process) and hydrocarbons (Fischer-Tropsch process) production processes. However, a less explored route to produce chemical products, among them alcohols and other oxygenates, from syngas has been gaining attention over the last few years. In this route, an initial feedstock as biomass is firstly gasified to synthesis gas, which is reformed, cleaned, compressed and finally catalytically converted into a mixture of alcohols and oxygenated products. After separation steps, these products attain sufficient purity to be sold. In this work, the thermochemical route, is used aiming ethanol production from syngas. Using the commercial simulator ASPEN Plus, were proposed four study cases using 3 different categories of catalysts in 4 different process layouts. All the cases were evaluated regarding their productivity, energy consumption, and aspects of economic importance. The results show the technical viability to produce ethanol from syngas, proving an energy surplus of all processes and a reasonable production of the main product.}, language = {en} } @misc{GonzalezCastanoGonzalezAriasBobadillaetal., author = {Gonzalez-Casta{\~n}o, Miriam and Gonzalez-Arias, Judith and Bobadilla, Luis F. and Ruiz-Lopez, E. and Odriozola, Jose Antonio and Arellano-Garc{\´i}a, Harvey}, title = {In-Situ Drifts Steady-State Study of Co2 and Co Methanation Over Ni-Promoted Catalysts}, series = {Fuel}, volume = {338}, journal = {Fuel}, issn = {1873-7153}, doi = {10.1016/j.fuel.2022.127241}, abstract = {Promoting the performance of catalytic systems by incorporating small amount of alkali has been proved effective for several reactions whilst controversial outcomes are reported for the synthetic natural gas production. This work studies a series of Ni catalysts for CO2 and CO methanation reactions. In-situ DRIFTS spectroscopy evidenced similar reaction intermediates for all evaluated systems and it is proposed a reaction mechanism based on: i) formate decomposition and ii) hydrogenation of lineal carbonyl species to methane. Compared to bare Ni, the enhanced CO2 methanation rates attained by NiFe/Al and NiFeK/Al systems are associated to promoted formates decomposition into lineal carbonyl species. Also for CO methanation, the differences in the catalysts' performances were associated to the relative concentration of lineal carbonyl species. Under CO methanation conditions and opposing the CO2 methanation results where the incorporation of K delivered promoted catalytic behaviours, worsened CO methanation rates were discerned for the NiFeK/Al system.}, language = {en} } @misc{TarifaRamirezReinaGonzalezCastanoetal., author = {Tarifa, Pilar and Ramirez Reina, Tomas and Gonz{\´a}lez-Casta{\~n}o, Miriam and Arellano-Garc{\´i}a, Harvey}, title = {Catalytic Upgrading of Biomass-Gasification Mixtures Using Ni-Fe/MgAl₂O₄ as a Bifunctional Catalyst}, series = {Energy and Fuels}, volume = {36}, journal = {Energy and Fuels}, number = {15}, issn = {1520-5029}, doi = {10.1021/acs.energyfuels.2c01452}, pages = {8267 -- 8273}, abstract = {Biomass gasification streams typically contain a mixture of CO, H2, CH4, and CO2 as the majority components and frequently require conditioning for downstream processes. Herein, we investigate the catalytic upgrading of surrogate biomass gasifiers through the generation of syngas. Seeking a bifunctional system capable of converting CO2 and CH4 to CO, a reverse water gas shift (RWGS) catalyst based on Fe/MgAl2O4 was decorated with an increasing content of Ni metal and evaluated for producing syngas using different feedstock compositions. This approach proved efficient for gas upgrading, and the incorporation of adequate Ni content increased the CO content by promoting the RWGS and dry reforming of methane (DRM) reactions. The larger CO productivity attained at high temperatures was intimately associated with the generation of FeNi3 alloys. Among the catalysts' series, Ni-rich catalysts favored the CO productivity in the presence of CH4, but important carbon deposition processes were noticed. On the contrary, 2Ni-Fe/MgAl2O4 resulted in a competitive and cost-effective system delivering large amounts of CO with almost no coke deposits. Overall, the incorporation of a suitable realistic application for valorization of variable composition of biomass-gasification derived mixtures obtaining a syngas-rich stream thus opens new routes for biosyngas production and upgrading.}, language = {en} } @misc{RuanDorneanuArellanoGarciaetal., author = {Ruan, Hang and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey and Xiao, Pei and Zhang, Li}, title = {Deep Learning-Based Fault Prediction in Wireless Sensor Network Embedded Cyber-Physical Systems for Industrial Processes}, series = {IEEE Access}, volume = {10}, journal = {IEEE Access}, issn = {2169-3536}, doi = {10.1109/ACCESS.2022.3144333}, pages = {10867 -- 10879}, abstract = {This paper investigates the challenging fault prediction problem in process industries that adopt autonomous and intelligent cyber-physical systems (CPS), which is in line with the emerging developments of industrial internet of things (IIoT) and Industry 4.0. Particularly, we developed an end-to-end deep learning approach based on a large volume of real-time sensory data collected from a chemical plant equipped with wireless sensors. Firstly, a novel recursive architecture with multi-lookback inputs is proposed to perform autoregression on imbalanced time-series data as a preliminary prediction. In this process, a novel learning algorithm named recursive gradient descent (RGD) is developed for the proposed architecture to reduce cumulative prediction uncertainties. Subsequently, a classification model based on temporal convolutions over multiple channels with decay effect is proposed to perform multi-class classification for fault root cause identification and localization. The overall network is named the cumulative uncertainty reduction network (CURNet), for its superior capacity in reducing prediction uncertainties accumulated over multiple prediction steps. Performance evaluations show that CURNet is able to achieve superior performance especially in terms of fault prediction recall and fault type classification accuracy, compared to the existing techniques.}, language = {en} } @misc{SaavedraAlejandroParedesFloresSantosetal., author = {Saavedra, Stephy and Alejandro-Paredes, Luis and Flores-Santos, Juan Carlos and Flores-Fern{\´a}ndez, Carol Nathali and Arellano-Garc{\´i}a, Harvey and Zavaleta, Amparo Iris}, title = {Optimization of lactic acid production by Lactobacillus plantarum strain Hui1 in a medium containing sugar cane molasses}, series = {Agronom{\´i}a Colombiana}, volume = {39}, journal = {Agronom{\´i}a Colombiana}, number = {1}, issn = {0120-9965}, doi = {10.15446/agron.colomb.v39n1.89674}, pages = {98 -- 107}, abstract = {The aim of this study was to optimize lactic acid production by a native strain (Huil) of Lactobacillus plantarum isolated from a Peruvian Amazon fruit (Genipa americana) in a medium supplemented with an agroindustrial by-product such as sugar cane molasses. Optimization was performed though one-factor-at-a-time studies followed by the Placket-Burman and central composite designs. The data were analyzed by using the Statistica® 10 software. Several carbon, nitrogen and ion sources were tested, and the optimum concentration of lactic acid achieved was 84.2 g L-1 in a medium containing as follows (in g L-1): meat extract, 18.69; tryptone, 7.88; sugar cane molasses, 140; calcium carbonate, 15; dipotassium phosphate, 1; manganese phosphate, 0.03; sodium acetate, 5, and magnesium sulphate, 0.2. In addition, a high degree of conversion from sugar cane molasses to lactic acid was obtained (Yp/e 0.898 g g-1). These results indicate the potential of Lactobacil-lus plantarum strain Hui1 to produce lactic acid in a medium supplemented with sugar cane molasses, an underutilized industrial by-product.}, language = {en} } @misc{KetabchiMechleriArellanoGarcia, author = {Ketabchi, Elham and Mechleri, Evgenia and Arellano-Garc{\´i}a, Harvey}, title = {Increasing operational efficiency through the integration of an oil refinery and an ethylene production plant}, series = {Chemical Engineering Research and Design}, volume = {152}, journal = {Chemical Engineering Research and Design}, issn = {1744-3563}, doi = {10.1016/j.cherd.2019.09.028}, pages = {85 -- 94}, abstract = {In this work, the optimal integration between an oil refinery and an ethylene production plant has been investigated. Both plants are connected using intermediate materials aiming to remove, at least partially, the reliance on external sourcing. This integration has been proven to be beneficial in terms of quality and profit increase for both production systems. Thus, three mathematical models have been formulated and implemented for each plant individually as well as for the integrated system as MINLP models aiming to optimise all three systems. Moreover, a case study using practical data is presented to verify the feasibility of the integration within an industrial environment. Promising results have been obtained demonstrating significant profit increase in both plants.}, language = {en} } @misc{KetabchiPastorPerezArellanoGarciaetal., author = {Ketabchi, Elham and Pastor-Perez, Laura and Arellano-Garc{\´i}a, Harvey and Ramirez Reina, Tomas}, title = {Influence of Reaction Parameters on the Catalytic Upgrading of an Acetone, Butanol and Ethanol (ABE) Mixture: Exploring New Routes for Modern Biorefineries}, series = {Frontiers in Chemistry}, volume = {7}, journal = {Frontiers in Chemistry}, issn = {2296-2646}, doi = {10.3389/fchem.2019.00906}, abstract = {Here we present a comprehensive study on the effect of reaction parameters on the upgrade of an acetone, butanol and ethanol mixture - key molecules and platform products of great interest within the chemical sector. Using a selected high performing catalyst, Fe/MgO-Al2O3, the variation of temperature, reaction time, catalytic loading and reactant molar ratio have been examined in this reaction. This work is aiming to not only optimise the reaction conditions previously used, but to step towards using less energy, time and material by testing those conditions and analysing the sufficiency of the results. Herein we demonstrate that this reaction is favoured at higher temperatures and longer reaction time. Also, we observe that increasing the catalyst loading had a positive effect on the product yields, while reactant ratios have shown to produce varied results due to the role of each reactant in the complex reaction network. In line with the aim of reducing energy and costs, this work showcases that the products from the upgrading route have significantly higher market value than the reactants; highlighting that this process represents an appealing route to be implemented in modern biorefineries.}, language = {en} } @misc{KetabchiPastorPerezRamirezReinaetal., author = {Ketabchi, Elham and Pastor-Perez, Laura and Ramirez Reina, Tomas and Arellano-Garc{\´i}a, Harvey}, title = {Catalytic upgrading of acetone, butanol and ethanol (ABE): A step ahead for the production of added value chemicals in bio-refineries}, series = {Renewable Energy}, volume = {156}, journal = {Renewable Energy}, issn = {1879-0682}, doi = {10.1016/j.renene.2020.04.152}, pages = {1065 -- 1075}, abstract = {With the aim of moving towards sustainability and renewable energy sources, we have studied the production of long chain hydrocarbons from a renewable source of biomass to reduce negative impacts of greenhouse gas emissions while providing a suitable alternative for fossil fuel-based processes. Herein we report a catalytic strategy for Acetone, Butanol and Ethanol (ABE) upgrading using economically viable catalysts with potential impact in modern bio-refineries. Our catalysts based on transition metals such as Ni, Fe and Cu supported on MgO-Al2O3 have been proven to perform exceptionally with outstanding conversions towards the production of a broad range of added value chemicals from C2 to C15. Although all catalysts displayed meritorious performance, the Fe catalyst has shown the best results in terms conversion (89\%). Interestingly, the Cu catalyst displays the highest selectivity towards long chain hydrocarbons (14\%). Very importantly, our approach suppresses the utilization of solvents and additives resulting directly in upgraded hydrocarbons that are of use in the chemical and/or the transportation industry. Overall, this seminal work opens the possibility to consider ABE upgrading as a viable route in bio-refineries to produce renewably sourced added value products in an economically favorable way. In addition, the described process can be envisaged as a cross-link stream among bio and traditional refineries aiming to reduce fossil fuel sources involved and incorporate "greener" solutions.}, language = {en} } @misc{YentumiDorneanuArellanoGarcia, author = {Yentumi, Richard and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {Optimal Operation of an Industrial Natural Gas Fired Natural Draft Heater}, series = {Chemical Engineering Journal Advances}, volume = {11}, journal = {Chemical Engineering Journal Advances}, issn = {2666-8211}, doi = {10.1016/j.ceja.2022.100354}, abstract = {In this work, a custom dynamic mathematical model of an industrial vertical-cylindrical type natural gas fired natural draft heater is developed using gPROMS® ProcessBuilder®. The integrated model comprises sub-models for each of the distinct sections of the fired heater which are connected by mass and energy flows. The temperature profiles of the tubular coils and the process fluid, a heat transfer fluid (HTF) are modelled using the distributed parameter system (DPS) in the axial direction (1D). The flue gas temperature in each section is modelled using the lumped parameter approach. Published empirical methods and correlations are used for estimating some unknown model parameters. The resulting model is a system of partial differential-algebraic equations (PDAEs) and serves as a basis for conducting an optimisation study to aid decision-making and to identify the best operating conditions within the specified constraints that minimise the daily operational costs. Through process simulation studies, the model predictions are adjusted to closely approximate collected actual plant data. It is demonstrated through the optimisation study that significant reduction in fuel gas consumption can be achieved compared to the current operating consumption levels. The developed models can be extended for use by other hydrocarbon processing plant operators with slight modifications, by specifying geometric parameters, HTF thermophysical properties, fuel gas composition and properties, among others.}, language = {en} } @misc{DeMelDemisDorneanuetal., author = {De Mel, Ishanki and Demis, Panagiotis and Dorneanu, Bogdan and Klymenko, Oleksiy and Mechleri, Evgenia and Arellano-Garc{\´i}a, Harvey}, title = {Global sensitivity analysis for design and operation of distributed energy systems: A two-stage approach}, series = {Sustainable Energy Technologies and Assessments}, volume = {56}, journal = {Sustainable Energy Technologies and Assessments}, issn = {2213-1388}, doi = {10.1016/j.seta.2023.103064}, abstract = {Distributed Energy Systems (DES) can play a vital role as the energy sector faces unprecedented changes to reduce carbon emissions by increasing renewable and low-carbon energy generation. However, current operational DES models do not adequately reflect the influence of uncertain inputs on operational outputs, resulting in poor planning and performance. This paper details a methodology to analyse the effects of uncertain model inputs on the primary output, the total daily cost, of an operational model of a DES. Global Sensitivity Analysis (GSA) is used to quantify these effects, both individually and through interactions, on the variability of the output. A Mixed-Integer Linear Programming model for the DES design is presented, followed by the operational model, which incorporates Rolling Horizon Model Predictive Control. A subset of model inputs, which include electricity and heating demand, and solar irradiance, is treated as uncertain using data from a case study. Results show reductions of minimum 25\% in the total annualised cost compared to a traditional design that purchases electricity from the centralised grid and meets heating demand using boilers. In terms of carbon emissions, the savings are much smaller, although the dependency on the national grid is drastically reduced. Limitations and suggestions for improving the overall DES design and operation are also discussed in detail, highlighting the importance of incorporating GSA into the DES framework.}, language = {en} } @misc{ArellanoGarciaElBariKalibeFanezouneetal., author = {Arellano-Garc{\´i}a, Harvey and El Bari, Hassan and Kalibe Fanezoune, Casimir and Dorneanu, Bogdan and Majozi, Thokozani and Elhenawy, Yasser and Bayssi, Oussama and Hirt, Ayoub and Peixinho, Jorge and Dhahak, Asma and Gadalla, Mamdouh A. and Khashaba, Nourhan H. and Ashour, Fatma}, title = {Catalytic Fast Pyrolysis of Lignocellulosic Biomass: Recent Advances and Comprehensive Overview}, series = {Journal of Analytical and Applied Pyrolysis}, volume = {Vol. 178}, journal = {Journal of Analytical and Applied Pyrolysis}, issn = {0165-2370}, doi = {10.1016/j.jaap.2024.106390}, abstract = {Using biomass as a renewable resource to produce biofuels and high-value chemicals through fast pyrolysis offers significant application value and wide market possibilities, especially in light of the current energy and environmental constraints. Bio-oil from fast-pyrolysis has various conveniences over raw biomass, including simpler transportation and storage and a higher energy density. The catalytic fast pyrolysis (CFP) is a complex technology which is affected by several parameters, mainly the biomass type, composition, and the interaction between components, process operation, catalysts, reactor types, and production scale or pre-treatment techniques. Nevertheless, due to its complicated makeup, high water and oxygen presence, low heating value, unstable nature, elevated viscosity, corrosiveness, and insolubility within conventional fuels, crude bio-oil has drawbacks. In this context, catalysts are added to reactor to decrease activation energy, substitute the output composition, and create valuable compounds and higher-grade fuels. The study aim is to explore the suitability of lignocellulosic biomasses as an alternative feedstock in CFP for the optimization of bio-oil production. Furthermore, we provide an up-to-date review of the challenges in bio-oil production from CFP, including the factors and parameters that affect its production and the effect of used catalysis on its quality and yield. In addition, this work describes the advanced upgrading methods and applications used for products from CFP, the modeling and simulation of the CFP process, and the application of life cycle assessment. The complicated fluid dynamics and heat transfer mechanisms that take place during the pyrolysis process have been better understood due to the use of CFD modeling in studies on biomass fast pyrolysis. Zeolites have been reported for their superior performance in bio-oil upgrading. Indeed, Zeolites as catalyses have demonstrated significant catalytic effects in boosting dehydration and cracking process, resulting in the production of final liquid products with elevated H/C ratios and small C/O ratios. Combining ex-situ and in-situ catalytic pyrolysis can leverage the benefits of both approaches. Recent studies recommend more and more the development of pyrolysis-based bio-refinery processes where these approaches are combined in an optimal way, considering sustainable and circular approaches.}, language = {en} } @misc{ArellanoGarciaSafdarShezadetal., author = {Arellano-Garc{\´i}a, Harvey and Safdar, Muddasar and Shezad, Nasir and Akhtar, Farid}, title = {Development of Ni-doped A-site lanthanides-based perovskite-type oxide catalysts for CO2 methanation by auto-combustion method}, series = {RSC Advances}, volume = {2024}, journal = {RSC Advances}, number = {14}, doi = {10.1039/d4ra02106a}, pages = {20240 -- 20253}, abstract = {Engineering the interfacial interaction between the active metal element and support material is a promising strategy for improving the performance of catalysts toward CO2 methanation. Herein, the Ni-doped rare-earth metal-based A-site substituted perovskite-type oxide catalysts (Ni/AMnO3; A = Sm, La, Nd, Ce, Pr) were synthesized by auto-combustion method, thoroughly characterized, and evaluated for CO2 methanation reaction. The XRD analysis confirmed the perovskite structure and the formation of nano-size particles with crystallite sizes ranging from 18 to 47 nm. The Ni/CeMnO3 catalyst exhibited a higher CO2 conversion rate of 6.6 × 10-5 molCO2 gcat-1 s-1 and high selectivity towards CH4 formation due to the surface composition of the active sites and capability to activate CO2 molecules under redox property adopted associative and dissociative mechanisms. The higher activity of the catalyst could be attributed to the strong metal-support interface, available active sites, surface basicity, and higher surface area. XRD analysis of spent catalysts showed enlarged crystallite size, indicating particle aggregation during the reaction; nevertheless, the cerium-containing catalyst displayed the least increase, demonstrating resilience, structural stability, and potential for CO2 methanation reaction.}, language = {en} } @misc{MedinaMendezDorneanuSchmidtetal., author = {Medina M{\´e}ndez, Juan Ali and Dorneanu, Bogdan and Schmidt, Heiko and Arellano-Garc{\´i}a, Harvey}, title = {Revisiting homogeneous modeling with volume averaging theory: structured catalysts for steam reforming and CO2 methanation}, series = {Journal of Physics: Conference Series}, volume = {2899/2024}, journal = {Journal of Physics: Conference Series}, issn = {1742-6596}, doi = {10.1088/1742-6596/2899/1/012004}, pages = {8}, abstract = {Progress in the modeling of structured catalysts is crucial for enhancing efficiency and scalability in industrial applications. Extensive research has investigated reactive flows over catalyst surfaces, covering chemical kinetics analysis and (direct) numerical simulations of the complete fluid flow in fixed-bed or structured catalysts. Nonetheless, this comes at a high computational cost. This study focuses on the homogeneous modeling of structured catalysts utilizing volume-averaging theory (VAT) as a more efficient method for representing the behaviour of such systems. We discuss modeling strategies for both 1-D and 3-D simulations. For steady 1-D flow simulations, we assess the influence of simplified gas chemical kinetics versus detailed surface chemistry, comparing with experimental data from the literature for a CO2 methanation processes. We also simulate 3-D flows of a steam reforming process, previously studied in the literature, using models which rely on different assumptions regarding the nature of the porous catalyst. Our findings reveal significant discrepancies based on different modeling assumptions, underscoring the necessity for accurate modeling of permeability and diffusivity tensors in homogeneous models.}, language = {en} } @misc{AlvesAmorimValverdePontesDorneanuetal., author = {Alves Amorim, Ana Paula and Valverde Pontes, Karen and Dorneanu, Bogdan and Arellano-Garcia, Harvey}, title = {Optimizing microgrid design and operation : a decision-making framework for residential distributed energy systems in Brazil}, series = {Chemical Engineering Research and Design}, volume = {214 (2025)}, journal = {Chemical Engineering Research and Design}, number = {February 2025}, publisher = {Elsevier}, issn = {0263-8762}, doi = {https://doi.org/10.1016/j.cherd.2024.12.033}, pages = {251 -- 268}, abstract = {This paper explores the optimization of microgrid design and operation for residential distributed energy systems in Brazil, addressing the growing demand for sustainable energy in the context of climate change. A decision-making framework based on Mixed-Integer Nonlinear Programming (MINLP) is proposed to integrate distributed energy resources (DERs) such as solar, wind, and biogas. Key challenges include managing the variability of renewable resources and complying with local regulations, while also addressing gaps in literature, particularly the impact of time-dependent efficiency profiles on energy sharing within microgrids. By employing innovative analyses and clustering techniques, the research optimizes microgrid configurations, accounting for seasonal demand fluctuations and the influence of incentive policies on system feasibility. The findings reveal that incorporating a time-dependent efficiency model can reduce total costs by 45 \%. This reduction underscores the importance of accurate efficiency predictions, as the model captures variations in energy generation and utilization efficiency over time, improving system optimization. Additionally, the findings reveal that a well-structured optimization model can meet 100 \% of electricity and hot water demands across all scenarios, with customized incentives playing a crucial role in reducing costs and promoting sustainability.}, language = {en} } @misc{ShafieeDorneanuArellanoGarcia, author = {Shafiee, Parisa and Dorneanu, Bogdan and Arellano-Garcia, Harvey}, title = {Towards Machine Learning-driven Catalyst Design and Optimization of Operating Conditions for the Production of Jet Fuel Via Fischer-Tropsch Synthesis}, series = {Chemical Engineering Transactions}, volume = {114}, journal = {Chemical Engineering Transactions}, issn = {2283-9216}, doi = {10.3303/CET24114098}, pages = {583 -- 588}, abstract = {Fischer-Tropsch synthesis (FTS) offers a promising route for producing sustainable jet fuels from syngas. However, optimizing the catalyst design and operating conditions to maximize the desired C8-C16 jet fuel range is a challenging task. This study introduces the application of a machine learning (ML) framework to guide the design of Co/Fe-supported FTS catalysts and operating conditions for enhanced fuel selectivity. A comprehensive dataset was constructed with 21 input features spanning catalyst structure, preparation method, activation procedure, and FTS operating parameters. The random forest ML algorithm was evaluated for predicting CO conversion and C8-C16 selectivity using this dataset. Feature engineering identified the most significant descriptors influencing performance. A principal component analysis reduced the dataset dimensionality prior to ML modelling. The random forest algorithm achieved high prediction accuracy for the conversion of CO (R2 = 0.92) and C8-C16 selectivity (R2 = 0.90). In addition to confirming the known effects of operating conditions, key roles of Co/Fe-supported properties were elucidated. This ML framework provides a powerful tool for the rational design of FTS catalysts and operating windows to maximize jet fuel productivity}, language = {en} } @misc{MappasDorneanuHeinzelmannetal., author = {Mappas, Vasileios K. and Dorneanu, Bogdan and Heinzelmann, Norbert and Arellano-Garcia, Harvey}, title = {Multiphase Catalytic Reactors: a Modular Approach}, series = {Chemical Engineering Transactions}, volume = {114}, journal = {Chemical Engineering Transactions}, issn = {2283-9216}, doi = {10.3303/CET24114097}, pages = {577 -- 582}, abstract = {Currently, state-of-the-art approaches to simulating the behaviour of trickle-bed reactors (TBRs) have focused solely on methods requiring high computational time and are unable to tackle systems with a large number of particles. In this work, a modular methodology based on a Lagrangian approach to TBR modelling is presented, which overcomes these drawbacks by implementing a simulation framework where different modules are interconnected and relevant information is transferred between them. The novelty of this framework stems from its adaptable configuration and its modular and unified setup, enabling it to accommodate both local and global multiscale events. The proposed methodology includes modules for the packing generation, liquid flow simulation, and of reaction system modelling within the reactor. To illustrate the procedure, a case study is discussed while demonstrating the potential of the presented approach. The results were validated against data obtained from a purpose-built experimental setup showing good agreement. The main advantages of this approach lie in its efficiency, the interrelation between different modules, and its ability to capture a wide range of information and phenomena.}, language = {en} } @misc{MappasDorneanuVassiliadisetal., author = {Mappas, Vassileios and Dorneanu, Bogdan and Vassiliadis, Vassilios S. and Arellano-Garc{\´i}a, Harvey}, title = {Multistage optimal control and nonlinear programming formulation for automated control loop selection}, series = {Computer Aided Chemical Engineering}, volume = {53}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-443-28824-1.50327-6}, pages = {1957 -- 1962}, abstract = {Control loop design, as well as controller tuning, constitute the pillars of process control to achieve design specifications and smooth process operation, and to meet predefined performance criteria. Currently, state-of-the-art approaches have focused on methods that yield only the pairings between input and output methods, and are not able to incorporate path and end-point constraints. This work introduces a novel strategy based on the multistage optimal control formulation of the control loop selection problem. This approach overcomes the drawbacks of traditional methods by producing an automated integrated solution for the task of control loop design. Furthermore, it obviates the need for any form of combinatorial optimization and incorporating path and terminal constraints. The results show that the proposed solution framework produces the same control loops as in the case of traditional approaches, however the inclusion of path and end-point constraints improves the performance of the control profiles.}, language = {en} } @misc{DorneanuKeykhaArellanoGarcia, author = {Dorneanu, Bogdan and Keykha, Mina and Arellano-Garc{\´i}a, Harvey}, title = {Assessment of parameter uncertainty in the maintenance scheduling of reverse osmosis networks via a multistage optimal control reformulation}, series = {Computer Aided Chemical Engineering}, volume = {53}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-443-28824-1.50326-4}, pages = {1951 -- 1956}, abstract = {In this work, the influence of uncertain parameters on the maintenance scheduling of Reverse Osmosis Networks (RONs) is explored. Based on a foundation of successful applications in various maintenance optimization domains, this paper extends the methodology to the domain of RON regeneration actions planning, highlighting its adaptability to diverse areas of dynamic processes with planning uncertainty. Traditional approaches in membrane cleaning scheduling have predominantly relied on MixedInteger Nonlinear Programming (MINLP), often leading to combinatorial problems that fail to capture the dynamic nature of the system. As part of this study, a novel approach based on the Multistage Integer Nonlinear Optimal Control Problem (MSINOCP) formulation is used to automate and optimize membrane cleaning scheduling without requiring combinatorial optimization. To evaluate the consequences of parameter uncertainty, 26 scenarios are considered in which the cost of the energy unit is considered as variable based on a random distribution, and these results are compared to a scenario where a fixed cost parameter is assumed. The findings show that when the cost of energy is considered as an uncertain parameter, the optimization process requires more frequent cleaning measures.}, language = {en} } @misc{DorneanuZhangVassiliadisetal., author = {Dorneanu, Bogdan and Zhang, Sushen and Vassiliadis, Vassilios S. and Arellano-Garc{\´i}a, Harvey}, title = {Optimizing deep neural networks through hierarchical multiscale parameter tuning}, series = {Computer Aided Chemical Engineering}, volume = {53}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-443-28824-1.50155-1}, pages = {925 -- 930}, abstract = {Deep neural networks (DNNs) are frequently employed for information extraction in big data applications across various domains; however, their application in real-time industrial systems is hindered by constraints such as limited computational, storage capacity, energy availability, and time constraints. This contribution introduces the development of a novel hierarchical multiscale framework for the training of DNNs that incorporates neural sensitivity analysis for the automatic and selective training of neurons evaluated to be the most effective. This alternative training methodology generates local minima that closely match or surpass those achieved by traditional approaches, such as the backpropagation method, utilizing identical starting points for comparative purposes.}, language = {en} } @misc{VassiliadisMappasEspaasetal., author = {Vassiliadis, Vassilios S. and Mappas, Vassileios and Espaas, Tomas A. and Dorneanu, Bogdan and Isafiade, Adeniyi and M{\"o}ller, Klaus and Arellano-Garc{\´i}a, Harvey}, title = {Reloading process systems engineering within chemical engineering}, series = {Chemical Engineering Research and Design}, volume = {209}, journal = {Chemical Engineering Research and Design}, doi = {10.1016/j.cherd.2024.07.066}, pages = {380 -- 398}, abstract = {Established as a sub-discipline of Chemical Engineering in the 1960s by the late Professor R.W.H. Sargent at Imperial College London, Process Systems Engineering (PSE) has played a significant role in advancing the field, positioning it as a leading engineering discipline in the contemporary technological landscape. Rooted in Applied Mathematics and Computing, PSE aligns with the key components driving advancements in our modern, information-centric era. Sargent's visionary foresight anticipated the evolution of early computational tools into fundamental elements for future technological and scientific breakthroughs, all while maintaining a central focus on Chemical Engineering. This paper aims to present concise and concrete ideas for propelling PSE into a new era of progress. The objective is twofold: to preserve PSE's extensive and diverse knowledge base and to reposition it more prominently within modern Chemical Engineering, while also establishing robust connections with other data-driven engineering and applied science domains that play important roles in industrial and technological advancements. Rather than merely reacting to contemporary challenges, this article seeks to proactively create opportunities to lead the future of Chemical Engineering across its vital contributions in education, research, technology transfer, and business creation, fully leveraging its inherent multidisciplinarity and versatile character.}, language = {en} } @misc{QuinlanBrooksGhaemietal., author = {Quinlan, Laura and Brooks, Talia and Ghaemi, Nasrin and Arellano-Garc{\´i}a, Harvey and Irandoost, Maryam and Sharifianjazi, Fariborz and Amini Horri, Bahman}, title = {Synthesis and characterisation of nanocrystalline CoxFe1-xGDC powders as a functional anode material for the solid oxide fuel cell}, series = {Materials}, volume = {17}, journal = {Materials}, number = {15}, publisher = {MDPI}, issn = {1996-1944}, doi = {10.3390/ma17153864}, pages = {26}, abstract = {The necessity for high operational temperatures presents a considerable obstacle to the commercial viability of solid oxide fuel cells (SOFCs). The introduction of active co-dopant ions to polycrystalline solid structures can directly impact the physiochemical and electrical properties of the resulting composites including crystallite size, lattice parameters, ionic and electronic conductivity, sinterability, and mechanical strength. This study proposes cobalt-iron-substituted gadolinium-doped ceria (CoxFe1-xGDC) as an innovative, nickel-free anode composite for developing ceramic fuel cells. A new co-precipitation technique using ammonium tartrate as the precipitant in a multi-cationic solution with Co2+, Gd3+, Fe3+, and Ce3+ ions was utilized. The physicochemical and morphological characteristics of the synthesized samples were systematically analysed using a comprehensive set of techniques, including DSC/TGA for a thermal analysis, XRD for a crystallographic analysis, SEM/EDX for a morphological and elemental analysis, FT-IR for a chemical bonding analysis, and Raman spectroscopy for a vibrational analysis. The morphological analysis, SEM, showed the formation of nanoparticles (≤15 nm), which corresponded well with the crystal size determined by the XRD analysis, which was within the range of ≤10 nm. The fabrication of single SOFC bilayers occurred within an electrolyte-supported structure, with the use of the GDC as the electrolyte layer and the CoO-Fe2O3/GDC composite as the anode. SEM imaging and the EIS analysis were utilized to examine the fabricated symmetrical cells.}, language = {en} } @misc{SohailRiedelDorneanuetal., author = {Sohail, Norman and Riedel, Ramona and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {Prolonging the Life Span of Membrane in Submerged MBR by the Application of Different Anti-Biofouling Techniques}, series = {Membranes}, volume = {13}, journal = {Membranes}, number = {2}, issn = {2077-0375}, doi = {10.3390/membranes13020217}, abstract = {The membrane bioreactor (MBR) is an efficient technology for the treatment of municipal and industrial wastewater for the last two decades. It is a single stage process with smaller footprints and a higher removal efficiency of organic compounds compared with the conventional activated sludge process. However, the major drawback of the MBR is membrane biofouling which decreases the life span of the membrane and automatically increases the operational cost. This review is exploring different anti-biofouling techniques of the state-of-the-art, i.e., quorum quenching (QQ) and model-based approaches. The former is a relatively recent strategy used to mitigate biofouling. It disrupts the cell-to-cell communication of bacteria responsible for biofouling in the sludge. For example, the two strains of bacteria Rhodococcus sp. BH4 and Pseudomonas putida are very effective in the disruption of quorum sensing (QS). Thus, they are recognized as useful QQ bacteria. Furthermore, the model-based anti-fouling strategies are also very promising in preventing biofouling at very early stages of initialization. Nevertheless, biofouling is an extremely complex phenomenon and the influence of various parameters whether physical or biological on its development is not completely understood. Advancing digital technologies, combined with novel Big Data analytics and optimization techniques offer great opportunities for creating intelligent systems that can effectively address the challenges of MBR biofouling.}, language = {en} } @misc{StraubDorneanuArellanoGarcia, author = {Straub, Adrian and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {Towards a novel concept for solid energy storage}, series = {Computer Aided Chemical Engineering}, volume = {Vol. 52}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-443-15274-0.50472-8}, pages = {2965 -- 2970}, abstract = {In this contribution, the model-based development of a novel process concept for the storage and release of ammonia in solids is proposed. The concept is validated by means of the Aspen Plus® process simulator. As a promising prospect, Hexaaminenickel(II) chloride is selected. After a preparative stage, the process can cycle between the storage and release of energy. The process is split in a reaction and a separation section, in such a way that the same equipment is used for both storage and release steps. Sensitivity analysis and design parameter optimization are used to determine key process parameters. The operation ranges from standard conditions (25 °C and 1 atm) to temperatures not higher than 120 °C. Moreover, the simulation results show that it is possible to store over 50\% of the base material in form of ammonia, equivalent to almost 10 wt.\% hydrogen, placing the concept within the specific system targets set by the U.S. Department of Energy.}, language = {en} } @misc{DorneanuMiahMechlerietal., author = {Dorneanu, Bogdan and Miah, Sayeef and Mechleri, Evgenia and Arellano-Garc{\´i}a, Harvey}, title = {Multiobjective optimization of distributed energy systems design through 3E (economic, environmental and exergy) analysis}, series = {Computer Aided Chemical Engineering}, volume = {Vol. 52}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-443-15274-0.50473-X}, pages = {2971 -- 2976}, abstract = {Distributed energy systems (DES) are promising alternative to conventional centralized generation, with multiple financial incentives in many parts of the world. Current approaches focus on the design optimization of a DES through economic and environmental cost minimization. However, these two criteria alone do not satisfy long-term sustainability priorities of the system. The novelty of this paper is the simultaneous investigation of economic, environmental and exergetic criteria in the modelling of DES through the two most commonly used solution methodologies for solving multi-objective optimization problems - the weighted sum and the epsilon-constraint methods. Out of the set of Pareto optimal solutions, a best-compromised solution is chosen using the fuzzy-based method. Numerical results reveal reduction of around 93\% and 89-91\% in environmental and primary exergy input, respectively.}, language = {en} } @misc{AlvesAmorimDorneanuValverdePontesetal., author = {Alves Amorim, Ana Paula and Dorneanu, Bogdan and Valverde Pontes, Karen and Arellano-Garc{\´i}a, Harvey}, title = {A framework for decision-making to encourage utilization of residential distributed energy systems in Brazil}, series = {Computer Aided Chemical Engineering}, volume = {Vol. 52}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-443-15274-0.50481-9}, pages = {3019 -- 3024}, abstract = {The Distributed Energy Systems (DES) or microgrid arose from the need to reduce greenhouse gases (GHG) emitted into the atmosphere by burning fossil fuels to generate energy. Reduction of energy losses, reconfiguration of the protection system and reduction of costs, and optimizing the configuration of these systems is recommended. Despite new research in literature, there is still a lack of optimization models that address the Brazilian reality. Therefore, the objective of this work is to introduce a decision-making framework for the design and operation of residential DES that takes into account the particularities of Brazil, based on mixed-integer programming models. The applicability of the framework is tested on a case study of a residential DES of 5 houses, located in Salvador, and used to compare scenarios pre- and post-COVID-19. The results show significant reduction in total annual cost and GHG emissions versus the base case without DES. This indicates that, although the country has a mostly "clean" energy matrix due to the use of hydroelectric plants, DES can enable improvement in residential electricity generation.}, language = {en} } @misc{TarifaGonzalezCastanoCazanaetal., author = {Tarifa, Pilar and Gonzalez-Castano, Miriam and Cazana, Fernando and Monzon, Antonio and Arellano-Garc{\´i}a, Harvey}, title = {Hydrophobic RWGS catalysts: valorization of CO2-rich streams in presence of CO/H2O}, series = {Catalysis Today}, volume = {Vol. 423}, journal = {Catalysis Today}, issn = {1873-4308}, doi = {10.1016/j.cattod.2023.114276}, abstract = {Nowadays, the majority of the Reverse Water Gas Shift (RWGS) studies assume somehow model feedstock (diluted CO2/H2) for syngas production. Nonetheless, biogas streams contain certain amounts of CO/H2O which will decrease the obtained CO2 conversion values by promoting the forward WGS reaction. Since the rate limiting step for the WGS reaction concerns the water splitting, this work proposes the use of hydrophobic RWGS catalysts as an effective strategy for the valorization of CO2-rich feedstock in presence of H2O and CO. Over Fe-Mg catalysts, the different hydrophilicities attained over pristine, N- and B-doped carbonaceous supports accounted for the impact on the activity of the catalyst in presence of CO/H2O. Overall, the higher CO productivity (4.12 μmol/(min·m2)) attained by Fe-Mg/CDC in presence of 20\% of H2O relates to hindered water adsorption and unveil the use of hydrophobic surfaces as a suitable approach for avoiding costly pre-conditioning units for the valorization of CO2-rich streams based on RWGS processes in presence of CO/H2O.}, language = {en} } @misc{DorneanuMashamKeykhaetal., author = {Dorneanu, Bogdan and Masham, Elliot and Keykha, Mina and Mechleri, Evgenia and Cole, Rosanna and Arellano-Garc{\´i}a, Harvey}, title = {Assessment of centralised and localised ice cream supply chains using neighbourhood flow configuration models}, series = {Supply Chain Analytics}, volume = {Vol. 4}, journal = {Supply Chain Analytics}, doi = {10.1016/j.sca.2023.100043}, abstract = {Traditional food supply chains are often centralised and global in nature, entailing substantial resource consumption. However, in the face of growing demand for sustainability, this strategy faces significant challenges. Adoption of localised supply chains is deemed a more sustainable option, yet its efficacy requires verification. Supply chain analytics methodologies provide invaluable tools to guide decisions regarding inventory management, demand forecasting and distribution optimisation. These solutions not only enhance facilitate operational efficiency, but also pave the way for cost reduction, further aligning with sustainability objectives. This research introduces a novel decision-making approach anchored in mixed integer linear programming (MILP) and neighbourhood flow models defined in cellular automata to compare the environmental benefits and vulnerability to disruption of these two chain configurations. Additionally, a comprehensive cost analysis is integrated to assess the economic feasibility of incorporating layout changes that enhance supply chain sustainability. The proposed framework is applied on an ice cream supply chain across England over a one-year timeframe. The findings indicate the superiority of the localised configuration in terms of economic benefits, leading to savings exceeding \pounds 1 million, alongside important reductions in environmental impact. However, in terms of resilience, the traditional configuration remains superior in three out of the four examined scenarios.}, language = {en} } @misc{MappasVassiliadisDorneanuetal., author = {Mappas, Vassileios and Vassiliadis, Vassilios S. and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {Automated Control Loop Selection Via Multistage Optimal Control Formulation and Nonlinear Programming}, series = {Chemical Engineering Research and Design}, volume = {195}, journal = {Chemical Engineering Research and Design}, issn = {1744-3563}, doi = {10.1016/j.cherd.2023.05.041}, pages = {76 -- 95}, abstract = {In this work, a novel approach based on the multistage optimal control formulation of the control loop selection problem is introduced. Currently, state-of-the-art approaches for controller loop design have been focused on data that yield only the pairings between input-output variables, and are not able to incorporate path and end-point constraints. Thus, they only produce the optimal loops for control purposes, without the simultaneous consideration of their optimal tuning. This formulation overcomes these drawbacks by producing an automated integrated solution for the task of control loop design, which also obviates the need for any form of combinatorial optimisastion to be used. To illustrate the procedure, as well as the advantages of the proposed scheme, different practical case studies are discussed and the results compared with those obtained with standard controller loop selection methods and their tuning. The results of the proposed approach show improved performance over previous methodologies found in the literature. Furthermore, the framework is extended to the selection of the control loops that must obey path and end-point constraints imposed by the underlying dynamical process. This task is usually difficult for classical methods, which violate them or exhibit underdamped response in some cases.}, language = {en} } @misc{PlattfautSuckowKlepeletal., author = {Plattfaut, Julia and Suckow, Matthias and Klepel, Olaf and Erlitz, Marcel and Arellano-Garc{\´i}a, Harvey}, title = {Modellierung und Simulation der templatgest{\"u}tzten Synthese von por{\"o}sen Kohlenstoffger{\"u}sten mittels COMSOL Multiphysics}, series = {Chemie Ingenieur Technik}, volume = {96(2024)}, journal = {Chemie Ingenieur Technik}, number = {3}, issn = {1522-2640}, doi = {10.1002/cite.202300014}, pages = {318 -- 328}, abstract = {Mithilfe einer templatgest{\"u}tzten Synthese wurden por{\"o}se Kohlenstoffger{\"u}ste unter Verwendung von Silicagel als Templat hergestellt. Die chemische Gasphaseninfiltration (CVI) wurde hierbei als Synthese verwendet. Unter Variation verschiedener Reaktionsparameter zur Optimierung der Kohlenstoffabscheidung wurde dieser Prozess mathematisch modelliert and simuliert. Dabei konnten die experimentellen Ergebnisse gut mit den Modellen nachgebildet werden. Die zus{\"a}tzliche Beschreibung der laminaren Str{\"o}mung verbessert die {\"U}bereinstimmung deutlich.}, language = {de} } @misc{ZhangVassiliadisDorneanuetal., author = {Zhang, Sushen and Vassiliadis, Vassilios S. and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {Hierarchical multi-scale parametric optimization of deep neural networks}, series = {Applied Intelligence}, volume = {53}, journal = {Applied Intelligence}, number = {21}, issn = {1573-7497}, doi = {10.1007/s10489-023-04745-8}, pages = {24963 -- 24990}, abstract = {Traditionally, sensitivity analysis has been utilized to determine the importance of input variables to a deep neural network (DNN). However, the quantification of sensitivity for each neuron in a network presents a significant challenge. In this article, a selective method for calculating neuron sensitivity in layers of neurons concerning network output is proposed. This approach incorporates scaling factors that facilitate the evaluation and comparison of neuron importance. Additionally, a hierarchical multi-scale optimization framework is proposed, where layers with high-importance neurons are selectively optimized. Unlike the traditional backpropagation method that optimizes the whole network at once, this alternative approach focuses on optimizing the more important layers. This paper provides fundamental theoretical analysis and motivating case study results for the proposed neural network treatment. The framework is shown to be effective in network optimization when applied to simulated and UCI Machine Learning Repository datasets. This alternative training generates local minima close to or even better than those obtained with the backpropagation method, utilizing the same starting points for comparative purposes within a multi-start optimization procedure. Moreover, the proposed approach is observed to be more efficient for large-scale DNNs. These results validate the proposed algorithmic framework as a rigorous and robust new optimization methodology for training (fitting) neural networks to input/output data series of any given system.}, language = {en} } @misc{ArellanoGarciaSafdarLewisetal., author = {Arellano-Garc{\´i}a, Harvey and Safdar, Muddasar and Lewis, Allana and Radacsi, Norbert and Fan, Xianfeng and Huang, Yi}, title = {Superhydrophobic ZIF-67 with exceptional hydrostability}, series = {Materials Today Advances}, volume = {Vol. 20}, journal = {Materials Today Advances}, issn = {2590-0498}, doi = {10.1016/j.mtadv.2023.100448}, abstract = {In this work, cosolvent-stabilized superhydrophobic, highly hydrostable ZIF-67 was synthesized at room temperature using a facile, one-pot hydrothermal synthesis route, and the effect of cosolvent concentration on ZIF-67 crystal structure properties and hydrostability was studied systematically. The underlying mechanism for the cosolvent-supported hydrostability improvement was also proposed. Furthermore, the influence of hydrotreatment on the resultant ZIF-67s' catalytic performance was studied in the 'Sabatier reaction' for CO2 to synthetic natural gas (CH4) conversion.}, language = {en} } @misc{GonzalezCastanoMoralesNavarrodeMigueletal., author = {Gonzalez-Cast{\~a}no, Miriam and Morales, Carlos and Navarro de Miguel, Juan Carlos and Boelte, Jens-H. and Klepel, Olaf and Flege, Jan Ingo and Arellano-Garc{\´i}a, Harvey}, title = {Are Ni/ and Ni5Fe1/biochar catalysts suitable for synthetic natural gas production? A comparison with γ-Al2O3 supported catalysts}, series = {Green Energy \& Environment}, volume = {8}, journal = {Green Energy \& Environment}, number = {3}, issn = {2468-0257}, doi = {10.1016/j.gee.2021.05.007}, pages = {744 -- 756}, abstract = {Among challenges implicit in the transition to the post-fossil fuel energetic model, the finite amount of resources available for the technological implementation of CO2 revalorizing processes arises as a central issue. The development of fully renewable catalytic systems with easier metal recovery strategies would promote the viability and sustainability of synthetic natural gas production circular routes. Taking Ni and NiFe catalysts supported over γ-Al2O3 oxide as reference materials, this work evaluates the potentiality of Ni and NiFe supported biochar catalysts for CO2 methanation. The development of competitive biochar catalysts was found dependent on the creation of basic sites on the catalyst surface. Displaying lower Turn Over Frequencies than Ni/Al catalyst, the absence of basic sites achieved over Ni/C catalyst was related to the depleted catalyst performances. For NiFe catalysts, analogous Ni5Fe1 alloys were constituted over both alumina and biochar supports. The highest specific activity of the catalyst series, exhibited by the NiFe/C catalyst, was related to the development of surface basic sites along with weaker NiFe-C interactions, which resulted in increased Ni0:NiO surface populations under reaction conditions. In summary, the present work establishes biochar supports as a competitive material to consider within the future low-carbon energetic panorama.}, language = {en} } @misc{ShafieeDorneanuArellanoGarcia, author = {Shafiee, Parisa and Dorneanu, Bogdan and Arellano-Garcia, Harvey}, title = {Improving catalysts and operating conditions using machine learning in Fischer-Tropsch synthesis of jet fuels (C8-C16)}, series = {Chemical Engineering Journal Advances}, volume = {21 (2025)}, journal = {Chemical Engineering Journal Advances}, publisher = {Elsevier}, doi = {10.1016/j.ceja.2024.100702}, pages = {25}, abstract = {Fischer-Tropsch synthesis (FTS) offers a promising route for producing sustainable jet fuels from syngas. However, optimizing catalyst design and operating conditions for the ideal C8-C16 jet fuel range is challenging. Thus, this work introduces a machine learning (ML) framework to enhance Co/Fe-supported FTS catalysts and optimize their operating conditions for a better jet fuel selectivity. For this purpose, a dataset was implemented with 21 features, including catalyst structure, preparation method, activation procedure, and FTS operating parameters. Moreover, various machine-learning models (Random Forest (RF), Gradient Boosted, CatBoost, and artificial neural networks (ANN)) were evaluated to predict CO conversion and C8-C16 selectivity. Among these, the CatBoost model achieved the highest accuracy (R2 = 0.99). Feature analysis revealed that FTS operational conditions mainly affect CO conversion (37.9 \%), while catalyst properties were primarily crucial for C8-C16 selectivity (40.6 \%). The proposed ML framework provides a first powerful tool for the rational design of FTS catalysts and operating conditions to maximize jet fuel productivity.}, language = {en} } @misc{ShezadSafdarArellanoGarciaetal., author = {Shezad, Nasir and Safdar, Muddasar and Arellano-Garcia, Harvey and Tai, Cheuk-Wai and Chen, Shaojiang and Seo, Dong-Kyun and You, Shujie and Vomiero, Alberto and Akhtar, Farid}, title = {Deciphering the role of APTES in tuning the metal support interaction of NiO nanolayers over hierarchical zeolite 13X for CO2 methanation}, series = {Carbon Capture Science \& Technology}, volume = {15}, journal = {Carbon Capture Science \& Technology}, publisher = {Elsevier}, address = {Amsterdam}, doi = {10.1016/j.ccst.2025.100424}, pages = {1 -- 11}, abstract = {The development of robust nickel catalysts on porous substrates offers great potential for converting carbon dioxide (CO2) into methane, thereby helping to address the global warming and sustainability challenges. This study investigates the dispersion and stability of Ni nanolayers by grafting bifunctional groups over the hierarchical zeolite 13X (h13X) support using (3-aminopropyl)triethoxysilane (APTES). The Ni nanolayers, with a thickness of 1.5-7 nm, were deposited around the edges of h13X and analyzed using STEM imaging. A clear shift in the binding energies was observed by XPS analysis, substantiating the enhanced metalsupport interaction (MSI) between NiO and h13X. The influence of reaction temperature on APTES incorporation into h13X was revealed by H2-TPR and CO2-TPD, with notable variations in the reducibility and surface basicity profiles of the catalysts. The optimized catalyst exhibited CO2 conversion of 61\% with CH4 selectivity of 97\% under GHSV of 60,000 mlgCat-1h-1 at 400 oC and 1 bar and demonstrated robust stability over a period of 150 h without discernible degradation. The enhanced performance could be attributed to the strengthened MSI and reduced size of Ni nanolayers over h13X. These findings highlight the development of robust heterogeneous catalysts by changing the surface chemistry of support material for various catalytic applications.}, language = {en} } @misc{MappasDorneanuNolascoetal., author = {Mappas, Vasileios and Dorneanu, Bogdan and Nolasco, Eduardo and Vassiliadis, Vassilios and Arellano-Garcia, Harvey}, title = {Towards scalable quantum annealing for pooling and blending problems : a methodological proof-of-concept}, series = {Chemical engineering research and design}, volume = {221}, journal = {Chemical engineering research and design}, publisher = {Elsevier BV}, address = {Amsterdam}, issn = {1744-3563}, doi = {10.1016/j.cherd.2025.08.031}, pages = {560 -- 576}, abstract = {Industrial optimization challenges, such as the pooling and blending problem (PBP), require advanced computational methods to address non-convexity and scalability limitations in classical solvers. This work introduces a novel methodological framework for solving PBPs using quantum annealing (QA) that transforms the PBP into quadratic unconstrained binary optimization (QUBO) formulations at two resolution levels, enabling direct deployment on quantum annealers. Key innovations include a discretization technique tailored for PBP's bilinear constraints and an embedding method optimized for current quantum hardware. Benchmarking against classical solvers focuses on Haverly's classical three-stream PBP, enabling transparent comparison and development of quantum embedding and solution techniques. The proposed framework offers a scalable template for adapting similar engineering systems to quantum annealing architectures. Addressing genuine industrial-scale instances will require future advances in quantum hardware and embedding algorithms. The results demonstrate that QA exhibits the best performance among the examined alternatives, providing foundational insights towards leveraging QA in Process Systems Engineering.}, language = {en} } @misc{SchowarteRiedelSafdaretal., author = {Schowarte, Julia and Riedel, Ramona and Safdar, Muddasar and Helle, Sven and Fischer, Thomas and Arellano-Garc{\´i}a, Harvey}, title = {Photocatalytic degradation of PFOA with porous lanthanoid perovskites nano catalyst}, series = {Chemie - Ingenieur - Technik : CIT}, journal = {Chemie - Ingenieur - Technik : CIT}, publisher = {Wiley-VCH GmbH}, address = {Weinheim}, issn = {1522-2640}, doi = {10.1002/cite.70027}, pages = {1 -- 11}, abstract = {Perfluorooctanoic acid (PFOA), a persistent environmental pollutant, poses significant health and ecological risks. This study investigates for the first time the photocatalytic degradation of PFOA using novel doped perovskite catalysts under polychromatic UV-VIS irradiation with a peak emission at 366 nm. A series of nickel- and lanthanide-doped perovskites (NiMn2O4, LaMnO3, NdMnO3, and their nickel-doped variants) were synthesized via a facile co-precipitation technique and characterized using X-ray diffraction (XRD), UV-VIS diffuse reflectance spectroscopy (UV-VIS-DRS), scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX), N2-physisorption, and microwave plasma atomic emission spectroscopy (MP-AES). Photocatalytic experiments revealed that Ni/NdMnO3 exhibited the highest degradation efficiency toward PFOA, likely due to its small band gap energy of 1.5 eV, facilitating efficient C-C bond cleavage.}, language = {en} } @misc{YentumiJurischkaDorneanuetal., author = {Yentumi, Richard and Jurischka, Constantin and Dorneanu, Bogdan and Arellano-Garcia, Harvey}, title = {Optimal design and analysis of thermochemical storage and release of hydrogen via the reversible redox of iron oxide/iron}, series = {Systems and control transactions}, volume = {4}, journal = {Systems and control transactions}, publisher = {PSE Press}, address = {Notre Dame, IN}, isbn = {978-1-7779403-3-1}, issn = {2818-4734}, doi = {10.69997/sct.121492}, pages = {631 -- 636}, abstract = {In this contribution, a thermodynamic model-based approach for the optimal design of a solid-state hydrogen storage and release system utilizing the reversible iron oxide/iron thermochemical redox mechanism is presented. Existing storage processes using this mechanism face significant limitations, including low hydrogen conversion, high energy input requirements, limited storage density, and slow charging/discharging kinetics. To address these challenges, a custom thermodynamic model using NIST thermochemistry data is developed, enabling an in-depth analysis of redox reaction equilibria under different conditions. Unlike previous studies, this approach integrates a multi-objective optimization framework that explicitly balances competing objectives: maximizing hydrogen yield while minimizing thermal energy demand. By systematically identifying optimal trade-offs, the study provides new insights into improving process efficiency and reactor design for thermochemical hydrogen storage. These findings contribute to advancing energy-efficient and scalable hydrogen storage technologies.}, language = {en} } @misc{MappasDorneanuArellanoGarcia, author = {Mappas, Vasileios K. and Dorneanu, Bogdan and Arellano-Garcia, Harvey}, title = {Solving complex combinatorial optimization problems using quantum annealing approaches}, series = {Systems and control transactions}, volume = {4}, journal = {Systems and control transactions}, publisher = {PSE Press}, address = {Notre Dame, IN}, isbn = {978-1-7779403-3-1}, issn = {2818-4734}, doi = {10.69997/sct.188358}, pages = {1561 -- 1566}, abstract = {Currently, state-of-the-art approaches to solving complex optimization problems have focused solely on methods requiring high computational time and unable to find the global optimal solution. In this work, a methodology based on quantum computing is presented to overcome these drawbacks. The novelty of this framework stems from the quantum computer's architecture and taking into consideration the quantum phenomena that take place to solve optimization problems with specific structure. The proposed methodology includes steps for the transformation of the initial optimization problem into an unconstrainted optimization problem with binary variables and its embedding onto a quantum device. Moreover, different resolution levels for the transformation step and different architectures for the embedding process are utilized. To illustrate the procedure, a case study based on Haverly's pooling and blending problem is examined while demonstrating the potential of the proposed approach. The results indicate that the succinct formulation exhibited higher success rate during the embedding procedure for the different examined architectures, and the quantum annealing solver exhibited the best performance among the various solvers investigated. This highlights the potential of the approach for solving this type of problems with the rapid development and improvement of quantum hardware and expanding it to more complex chemical engineering optimization systems.}, language = {en} } @misc{ShafieeJafariSchowarteetal., author = {Shafiee, Parisa and Jafari, Mitra and Schowarte, Julia and Dorneanu, Bogdan and Arellano-Garcia, Harvey}, title = {Streamlining catalyst development through machine learning : insights from heterogeneous catalysis and photocatalysis}, series = {Systems and control transactions}, volume = {4}, journal = {Systems and control transactions}, publisher = {PSE Press}, address = {Notre Dame, IN}, isbn = {978-1-7779403-3-1}, issn = {2818-4734}, doi = {10.69997/sct.135551}, pages = {1866 -- 1871}, abstract = {Catalysis design and reaction condition optimization are considered the heart of many chemical and petrochemical processes and industries; however, there are still significant challenges in these fields. Advances in machine learning (ML) have provided researchers with new tools to address some of these obstacles, offering the ability to predict catalyst behaviour, optimal reaction conditions, and product distributions without the need for extensive laboratory experimentation. In this contribution, the potential applications of ML in heterogeneous catalysis and photocatalysis are explored by analysing datasets from different reactions, including Fischer-Tropsch synthesis and photocatalytic pollutant degradation. First, datasets were collected from literature. After cleaning and preparing the datasets, they were employed to train and test several models. The best model for each dataset was selected and applied for optimization.}, language = {en} } @misc{ParkLeeDorneanuetal., author = {Park, Haryn and Lee, Joowha and Dorneanu, Bogdan and Arellano-Garcia, Harvey and Kim, Jin-Kuk}, title = {Cost-effective process design and optimization for decarbonized utility systems integrated with renewable energy and carbon capture systems}, series = {Systems and control transactions}, volume = {4}, journal = {Systems and control transactions}, publisher = {PSE Press}, address = {Notre Dame, IN}, isbn = {978-1-7779403-3-1}, issn = {2818-4734}, doi = {10.69997/sct.107403}, pages = {1175 -- 1180}, abstract = {Industrial decarbonization is considered one of the key objectives in mitigating global climate change. To achieve a net-zero industry requires actively transitioning from fossil fuel-based energy sources to renewable alternatives. However, the intermittent nature of renewable energy sources poses challenges to a reliable and robust supply of energy for industrial sites. Therefore, the integration of renewable energy systems with existing industrial processes, subject to energy storage solutions and main grid interconnections, is essential to enhance operational reliability and overall energy resilience. This study proposes a novel framework for the design and optimization of industrial utility systems integrated with renewable energy sources. A monthly-based analysis is adopted to consider variable demand and non-constant availability in renewable energy supply. Moreover, carbon capture is considered in this work as a viable decarbonization measure, which can be strategically combined with renewable-based electrification. The proposed optimization model evaluates the economic trade-offs of integrating carbon capture, renewable energy, and energy storage. By applying this approach, systematic design guidelines are developed for the transition of a conventional steady-state utility system toward renewable energy integration, ensuring economically viable and sustainable energy management in process industries.}, language = {en} } @misc{MappasDorneanuHeinzelmannetal., author = {Mappas, Vasileios K. and Dorneanu, Bogdan and Heinzelmann, Norbert and Schnitzlein, Klaus and Arellano-Garcia, Harvey}, title = {An efficient and unified modeling framework for trickle bed reactors : a modular approach}, series = {Chemie - Ingenieur - Technik : CIT}, volume = {97}, journal = {Chemie - Ingenieur - Technik : CIT}, number = {11-12}, publisher = {Wiley}, address = {Weinheim}, issn = {1522-2640}, doi = {10.1002/cite.70035}, pages = {1110 -- 1126}, abstract = {Trickle bed reactors (TBRs) involve complex and multiscale dynamics that challenge their design, modeling, and optimization. Current approaches often suffer from high computational cost and limited scalability, restricting their applicability in large-scale cases. This work introduces a modular, computationally efficient framework to address these issues by systematically capturing key transport and reaction phenomena. Furthermore, it provides a critical review of existing modeling strategies for TBRs, outlining their strengths and limitations and highlighting opportunities for enhancement through modularization. By offering a structured and scalable approach, the proposed framework improves predictive capabilities and supports the development of optimized and adaptable reactor designs.}, language = {en} } @misc{MbuyaPawarJafarietal., author = {Mbuya, Christel Olivier Lenge and Pawar, Kunal and Jafari, Mitra and Shafiee, Parisa and Okoye Chine, Chike George and Tarifa, Pilar and Dorneanu, Bogdan and Arellano-Garcia, Harvey}, title = {Tuning catalyst performance in methane dry reforming via microwave irradiation of Nickel-Silicon carbide systems}, series = {Journal of CO2 utilization}, volume = {102}, journal = {Journal of CO2 utilization}, publisher = {Elsevier BV}, address = {Amsterdam}, issn = {2212-9839}, doi = {10.1016/j.jcou.2025.103270}, pages = {1 -- 9}, abstract = {The dry reforming of methane (DRM) is a promising route for converting greenhouse gases such as methane (CH4) and carbon dioxide (CO2) into valuable syngas, hydrogen (H2) and carbon monoxide (CO). However, traditional nickel (Ni)-based catalysts suffer from rapid deactivation due to carbon deposition and sintering, especially when supported on low thermal conductivity materials. In this work, a novel post-synthesis microwave irradiation (MIR) treatment is introduced to systematically optimize the performance of Ni - β - SiC and Ni - Ti - Cβ - SiC catalysts for DRM. Unlike previous studies that have used MIR during reaction or with different supports, this approach tunes the metal - support interactions and textural properties of Ni - β - SiC and Ni - Ti - Cβ - SiC catalysts by varying the MIR exposure time after catalyst synthesis. MIR post-treatment (10-25 s) increased the CH4 conversion to 65 \% and the CO2 conversions to 62 \% for Ni-β-SiC catalysts and improved the H₂/CO ratio to 0.80, with stable performance over 20 h. For Ni-Ti-Cβ-SiC, MIR (10-20 s) maintained CH4 conversion up to 60 \% and CO2 conversion to 58 \% over 20 h, while the untreated catalyst, though initially higher, deactivated rapidly. Excessive MIR (30 s) reduced performance for both catalyst types, underscoring the need for optimal exposure time. These findings demonstrate post-synthesis MIR provides a tuneable approach for enhancing both the activity and durability of Ni/SiC - based DRM catalysts through controlled modification of metal - support interactions. This work offers new insights for the design of robust catalysts aimed at greenhouse gas utilization and sustainable syngas production, with activity and stability enhancements linked to controlled changes in metal - support interactions.}, language = {en} } @misc{CunhaCordeiroSafdarSantosdaSilvaetal., author = {Cunha Cordeiro, Jos{\´e} Luiz and Safdar, Muddasar and Santos da Silva, Jefferson and Silva de Aquino, Gabrielle and Vaz dos Santos Rios, Jo{\~a}o Gabriel and Brand{\~a}o dos Santos, Maur{\´i}cio and Teixeira Cruz, Fernanda and Alves Fiuza-Junio, Raildo and Dorneanu, Bogdan and Arellano-Garcia, Harvey and Valverde Pontes, Karen and Santos Mascarenhas, Artur Jos{\´e}}, title = {Effect of support on Ni catalysts prepared by the combustion method applied in the dry reforming of biogas for production of sustainable hydrogen}, series = {International journal of hydrogen energy}, volume = {204}, journal = {International journal of hydrogen energy}, publisher = {Elsevier BV}, address = {Amsterdam}, issn = {1879-3487}, doi = {10.1016/j.ijhydene.2025.153150}, pages = {1 -- 25}, abstract = {This work investigated Ni catalysts on different supports (MgO, ZrO2, NiAl2O4, CeO2 and La2O3) prepared by the combustion method aiming for sustainable hydrogen production via simulated biogas dry reforming. The Ni/NiAl2O4 catalyst stood out among the materials due to its high Ni dispersion, low crystallite size and strong metal-support interaction, being stable for 8 h of reaction with high H2 yield and low coke deposition. The Ni/CeO2 catalyst showed good catalytic activity, but with high coke deposition (11.7 \%). The Ni/La2O3 catalyst showed an increase over the reaction time, due to the dynamic reconstruction of the surface. The Ni/MgO and Ni/ZrO2 catalysts did not present satisfactory performance when compared to the other catalysts, due to the low Ni dispersion and high crystallite size. The Ni/NiAl2O4 catalyst is very promising, due to the high production of H2, low coke deposition, thermal stability, but new studies on durability and economic viability are necessary.}, language = {en} } @misc{LeeParkDorneanuetal., author = {Lee, Joohwa and Park, Haryn and Dorneanu, Bogdan and Kim, Jin-Kuk and Arellano-Garcia, Harvey}, title = {Decarbonized hydrogen production : integrating renewable energy into electrified SMR process with CO₂ capture}, series = {Systems and control transactions}, volume = {4}, journal = {Systems and control transactions}, publisher = {PSE Press}, address = {Notre Dame, IN}, isbn = {978-1-7779403-3-1}, issn = {2818-4734}, doi = {10.69997/sct.152295}, pages = {613 -- 618}, abstract = {Electrified steam methane reforming has emerged as a promising technology for electrifying the hydrogen production process industries. Unlike conventional fossil fuel-based steam methane reforming, the electrified steam methane reforming process relies exclusively on electrical heating, eliminating the need for fossil fuel combustion. Beyond that, however, significant amounts of electricity required for the electrified process should be imported from the renewable energy-based system rather than fossil fuel-based grid electricity to have an environmental advantage over the conventional process. This study suggests a framework for integrating renewable energy systems into the electrified process for decarbonized hydrogen production. Considering the variability of renewable energy, wind and solar power are supplemented by battery storage, to facilitate a stable electricity supply to the electrified hydrogen production process. A Mixed-Integer Linear Programming (MILP) model is developed to optimally size and operate both the renewable system and potential grid imports. Case studies under various carbon tax scenarios, using historical weather data from a region in Germany, are conducted, followed by a techno-economic assessment to estimate the Cost of Hydrogen (COH). The results show that higher carbon taxes and reduced capital costs for wind, solar, and storage technologies significantly increase the share of renewable-based electricity. These findings highlight the importance of more stringent carbon taxation and improvements in the technology readiness level (TRL) of renewable energy are critical for accelerating large-scale, clean hydrogen production and industrial decarbonization.}, language = {en} } @misc{DorneanuMappasArellanoGarcia, author = {Dorneanu, Bogdan and Mappas, Vasileios K. and Arellano-Garcia, Harvey}, title = {A novel approach to gradient evaluation and efficient deep learning : a hybrid method}, series = {Systems and control transactions}, volume = {4}, journal = {Systems and control transactions}, publisher = {PSE Press}, address = {Notre Dame, IN}, isbn = {978-1-7779403-3-1}, issn = {2818-4734}, doi = {10.69997/sct.120349}, pages = {1872 -- 1877}, abstract = {Deep learning faces significant challenges in efficiently training large-scale models. These issues are closely linked, as efficient training often depends on precise and computationally feasible gradient calculations. This work introduces innovative methodologies to improve deep learning network (DLN) training in complex systems. A novel approach to DLN training is proposed by adapting the block coordinate descent (BCD) method, which optimizes individual layers sequentially. This is combined with traditional batch-based training to create a hybrid method that harnesses the strengths of both techniques. Additionally, the study explores Iterated Control Random Search (ICRS) for initializing parameters and applies quasi-Newton methods like L-BFGS with restricted iterations to enhance optimization. By tackling DLN training efficiency, this contribution offers a comprehensive framework to address key challenges in modern machine learning. The proposed methods improve scalability and effectiveness, especially for handling complex real-world problems. Examples from Process Systems Engineering illustrate how these advancements can directly enhance the training of large-scale systems.}, language = {en} } @misc{ShezadSamikannuSafdaretal., author = {Shezad, Nasir and Samikannu, Ajaikumar and Safdar, Muddasar and Arellano-Garcia, Harvey and Mikkola, Jyri-Pekka and Seo, Dong-Kyun and Akhtar, Farid}, title = {Nickel supported over hierarchical zeolite 13X catalysts for enhanced conversion of carbon dioxide into methane}, series = {International journal of energy research}, volume = {2025}, journal = {International journal of energy research}, publisher = {Wiley}, address = {Hoboken, NJ}, issn = {1099-114X}, doi = {10.1155/er/4728304}, pages = {1 -- 14}, abstract = {Catalytic conversion of carbon dioxide (CO2) into useful chemicals such as methane (CH4) is a promising carbon utilization method that effectively mitigates CO2 and partially meets energy needs. The characteristics of commonly used nickel (Ni) supported meso/microporous catalysts for CO2 methanation can be tailored by tuning the structural properties of the support and adding promoters. This work investigated the Ni supported over hierarchical zeolite 13X (h13X) and incorporated with different promoters (Mg, Ca, Ce, and La) developed using the wet-impregnation method. The catalysts were thoroughly characterized using SEM, EDS, XRD, H2-TPR, CO2-TPD, thermogravimetric analysis (TGA), X-ray photoelectron spectroscopy (XPS), and N2 sorption and desorption techniques and evaluated for CO2 methanation. The impact of promoters on the characteristics of the catalysts was observed with improved surface basicity in CO2-TPD and metal-support interaction in H2-TPR analysis. Among the promoted catalysts, the NiLa/h13X catalyst exhibited the highest catalytic activity with a maximum conversion of 76\% and CH4 selectivity of 98.5\% at 400°C and 20 bar at GHSV of 60,000 mL gcat-1 h-1, respectively. Regarding stability, the Mg-promoted catalyst exhibited better stability during 24 h of reaction than other catalysts, demonstrating better resilience against deactivation. The enhanced performance of the NiLa/h13X catalyst could be credited to the increased surface basicity, high surface area, and dispersion. This study highlights the potential of hierarchical porous zeolites for CO2 methanation and other heterogeneous reactions.}, language = {en} } @misc{SafdarSherArellanoGarcia, author = {Safdar, Muddasar and Sher, Farooq and Arellano-Garcia, Harvey}, title = {Perovskite materials for catalytic CO₂ valorisation : structural characteristics, synthesis and lattice substitutions for gas-phase reactions}, series = {Journal of environmental chemical engineering}, volume = {14}, journal = {Journal of environmental chemical engineering}, number = {2}, publisher = {Elsevier BV}, address = {Amsterdam}, issn = {2213-3437}, doi = {10.1016/j.jece.2026.121473}, pages = {1 -- 35}, abstract = {Perovskites are emerging materials that are being extensively investigated for converting greenhouse gases (GHGs) through thermochemical processes due to their versatile properties. Given their distinct physical and chemical characteristics and their unique structure (ABO3, general formula), they are desirable candidates for designing state-of-the-art catalytic systems. For instance, they can be prepared with modified oxygen vacancies, enhanced redox potential, and tailored nanoparticle formulations for use in various catalytic gas-phase CO2 conversion processes, thereby facilitating the formation of valuable, renewable raw materials such as fuels and chemicals. This comprehensive review explains the perovskite structures, including their crystallographic properties, standard synthesis methods, recent advancements in A, B, and X-site substitutions, and their effectiveness in upgrading CO2 to produce valuable commodities via different synthetic routes in gas-phase reactions via methanation, reverse water gas shift reaction (rWGS), and dry reforming of methane (DRM). To achieve a sustainable clean energy supply, application-oriented, efficient, and advanced catalytic systems that support the necessary reaction conditions and serve as the most active and selective catalysts are reported in each synthetic gas-phase production section. This study highlights current advancements and optimised research efforts to design potential catalytic materials that meet future requirements for developing efficient decarbonised energy systems. The proposed synthesis methods are the most effective techniques for conserving time and energy. They can also yield favourable morphology and allow manipulation of nanoparticle size, both of which are essential for designing innovative catalysts. To address concerns about CO2 emissions harming the environment, this study focuses on adaptable, sustainable gas-phase reaction methods with diverse industrial applications. The primary emphasis is on effective, robust perovskite-based catalysts that enable the efficient conversion of CO2 into value-added chemicals and fuels, thereby supporting low-carbon energy and chemical technologies. This review delineates explicit correlations among synthesis, structure, properties, performance, and stability by relating perovskite lattice design, defect chemistry, and compositional flexibility to catalytic activity, selectivity, and durability in heterogeneous catalytic reactions.}, language = {en} } @misc{SchowarteRiedelSafdaretal., author = {Schowarte, Julia and Riedel, Ramona and Safdar, Muddasar and Helle, Sven and Fischer, Thomas and Arellano-Garcia, Harvey}, title = {Photocatalytic degradation of PFOA with porous lanthanoid perovskites nano catalyst}, series = {Chemie Ingenieur Technik}, volume = {98}, journal = {Chemie Ingenieur Technik}, number = {1-2}, publisher = {Wiley-VCH}, address = {Weinheim}, issn = {1522-2640}, doi = {10.1002/cite.70027}, pages = {7 -- 17}, abstract = {Perfluorooctanoic acid (PFOA), a persistent environmental pollutant, poses significant health and ecological risks. Thisstudy investigates for the first time the photocatalytic degradation of PFOA using novel doped perovskite catalysts underpolychromatic UV-VIS irradiation with a peak emission at 366 nm. A series of nickel- and lanthanide-doped perovskites(NiMn2 O 4 , LaMnO 3 , NdMnO 3 , and their nickel-doped variants) were synthesized via a facile co-precipitation techniqueand characterized using X-ray diffraction (XRD), UV-VIS diffuse reflectance spectroscopy (UV-VIS-DRS), scanning elec-tron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX), N2 -physisorption, and microwave plasma atomicemission spectroscopy (MP-AES). Photocatalytic experiments revealed that Ni/NdMnO3 exhibited the highest degradationefficiency toward PFOA, likely due to its small band gap energy of 1.5 eV, facilitating efficient C-C bond cleavage.}, language = {en} } @misc{JafariSantosdaSilvaDorneanuetal., author = {Jafari, Mitra and Santos da Silva, Jefferson and Dorneanu, Bogdan and Valverde Pontes, Karen and Arellano-Garcia, Harvey}, title = {Towards digitalization of catalysis design and reaction engineering : data-driven insights into methanol to DME}, series = {58. Jahrestreffen Deutscher Katalytiker}, journal = {58. Jahrestreffen Deutscher Katalytiker}, pages = {1 -- 2}, abstract = {Dimethyl ether (DME, methoxymethane) is a clean-burning fuel and a promising alternative to conventional fossil fuels, especially in transportation and power generation. Its production from methanol through dehydration offers a viable pathway toward energy sustainability, not only because of its environmental benefits but also due to the high purity of the resulting products and the efficient conversion rate of methanol [1]. However, optimizing this process requires understanding the intricate dependencies among reaction parameters, including temperature, pressure, catalyst type, and feedstock composition [2]. Machine learning offers transformative potential in this context by identifying complex, non-linear interactions among variables and providing predictive insights that can improve reaction efficiency, yield, and product quality. Through predictive modeling, machine learning can significantly reduce the need for experimental trial-and-error by identifying optimal reaction conditions quickly, thereby decreasing costs, enhancing scalability, and supporting continuous, real-time process optimization [3, 4]. In this study, first a dataset is generated including different descriptors like catalyst formulation, pretreatment, characteristics, activation, and reaction conditions. This dataset is then preprocessed by encoding, imputation, and normalization to make it ready for modelling, followed by data analysis to identify patterns and dependencies. Different models, including Gradient Boosting Regressor, XGBoost, LightGBM, and neural networks, are applied to predict methanol conversion and DME yield based on input variables. The models were evaluated through cross-validation, achieving highaccuracy and underscoring the potential of data-driven optimization in enhancing DME production. These steps are illustrated in Figure 1. Finally, the prediction accuracy of each model is investigated, and the best algorithm is selected. The effect of different descriptors on the respond have also been assessed to find out the most effective parameters on the catalyst performance. The best model is then used to predict DME yield and optimize the catalyst and reaction parameters.}, language = {en} }