TY - CHAP A1 - Shafiee, Parisa A1 - Arellano-Garcia, Harvey T1 - Photocatalysts in CO2 direct conversion to methanol T2 - Reference Module in Chemistry, Molecular Sciences and Chemical Engineering N2 - The escalating global industrialization has led to fossil fuel scarcity and environmental deterioration, with CO2 levels rising significantly. To combat climate change, researchers are focusing on renewable energy and carbon capture technologies. This chapter reviews recent progress on photocatalytic conversion of CO2 to methanol, a promising approach for greenhouse gas reduction and sustainable energy production. Methanol, a versatile chemical feedstock and potential renewable fuel, can be synthesized from CO2 using solar energy and semiconductor photocatalysts. This chapter covers the fundamentals, mechanisms, materials development, photocatalysts design strategies, and preparation processes for this technology. Despite challenges in achieving high efficiency, CO2 photocatalytic reduction to methanol offers an attractive green alternative to traditional fossil-based methanol production. This comprehensive overview consolidates the current research landscape, providing insights to guide future advancements towards scalable and economically viable CO2 photocatalytic methanol synthesis. Y1 - 2024 U6 - https://doi.org/https://doi.org/10.1016/B978-0-443-15740-0.00121-X VL - 2024 ER - TY - CHAP A1 - Shafiee, Parisa A1 - Arellano-Garcia, Harvey T1 - Heterogeneous and Homogeneous Catalysts in CO2 Direct Conversion to Methanol T2 - Reference Module in Chemistry, Molecular Sciences and Chemical Engineering N2 - Catalytic conversion of CO2 into valuable products offers a promising solution to mitigate climate change by closing the carbon cycle. However, activating the thermodynamically stable and kinetically inert CO2 molecule remains a significant scientific challenge. This chapter focuses on homogeneous and heterogeneous catalysts for the direct conversion of CO2 to methanol, a valuable chemical feedstock and potential fuel. It introduces the importance of this process for reducing carbon emissions and outlines the chapter's objectives. The fundamentals of heterogeneous catalysis and catalyst design principles for methanol synthesis from CO2 are discussed. Various types of heterogeneous catalysts are examined, along with the mechanisms involved in CO2 activation and hydrogenation to methanol. Strategies to enhance catalyst selectivity, product distribution, and performance are explored, as well as challenges and future research directions. This comprehensive chapter serves as a guide to understanding the pivotal role of heterogeneous catalysts in the direct catalytic conversion of CO2 to methanol. Y1 - 2024 U6 - https://doi.org/https://doi.org/10.1016/B978-0-443-15740-0.00119-1 VL - 2024 PB - Elsevier ER - TY - CHAP A1 - Jafari, Mitra A1 - Arellano-Garcia, Harvey T1 - CO2 sources and features for direct CO2 conversion to methanol T2 - Reference Module in Chemistry, Molecular Sciences and Chemical Engineering N2 - In recent years, global concern over climate change caused by the accumulation of atmospheric CO2 has intensified. While various technologies for capturing CO2 have been proposed, utilizing captured CO2 from power plants is gaining popularity due to the concerns about the safety and effectiveness of underground and ocean storage methods. This article explores several techniques for utilizing CO2 from exhaust gases emitted by power plants. It provides a comprehensive review of current and emerging technologies worldwide that aim to harness CO2 for beneficial purposes. The conversion of CO2 into chemicals and energy products represents a promising approach to not only mitigate CO2 emissions but also enhance economic value. However, since CO2 lacks hydrogen, which is essential for many chemical processes, the development of clean, sustainable, and cost-effective hydrogen sources is crucial. This chapter delves into the literature surrounding the production of biofuels derived from microalgae cultivated using captured CO2, the conversion of CO2 combined with hydrogen into various chemicals, specially methanol and the exploration of sustainable hydrogen sources. These efforts collectively underscore the potential of CO2 utilization as a pivotal strategy in the battle against climate change and for fostering sustainable industrial practices. Y1 - 2024 U6 - https://doi.org/https://doi.org/10.1016/B978-0-443-15740-0.00127-0 VL - 2024 ER - TY - CHAP A1 - Jafari, Mitra A1 - Arellano-Garcia, Harvey T1 - Shift from syngas to CO2 for methanol production T2 - Reference Module in Chemistry, Molecular Sciences and Chemical Engineering N2 - This chapter delves into diverse methodologies for converting carbon dioxide (CO2) into methanol, employing homogeneous and heterogeneous catalysts through hydrogenation, photochemical, electrochemical, and photo-electrochemical techniques. Given the significant contribution of CO2 to global warming, utilizing it for fuel and chemical production stands as a sustainable approach to environmental conservation. However, due to high stability and low reactivity of CO2, the development of appropriate methods and catalysts is crucial for breaking its bonds to yield valuable chemicals like methanol. Also, in this chapter various methods and their mechanisms for CO2 conversion to methanol are described. Finally, new types of catalyst and their characteristics for CO2 hydrogenation to methanol are introduced and discussed in detail. Y1 - 2024 U6 - https://doi.org/https://doi.org/10.1016/B978-0-443-15740-0.00126-9 VL - 2024 ER - TY - CHAP A1 - Shafiee, Parisa A1 - Arellano-Garcia, Harvey T1 - Electrocatalysts in CO2 direct conversion to methanol T2 - Reference Module in Chemistry, Molecular Sciences and Chemical Engineering N2 - By now, atmospheric CO2 levels necessitate new ways of reducing them more than ever with increasing global warming and climate change. Converting CO2 into valuable products like methanol fuel presents a solution by reducing atmospheric CO2 while creating economic opportunities. This chapter reviews the state-of-the-art in electrocatalytic CO2-to-methanol conversion technologies, covering basic electrocatalysis principles, electrocatalyst materials, design strategies, performance optimization, mechanistic pathways, catalyst compositions, technological hurdles, and potential solutions. It also examines environmental impacts, economic aspects, and scaling up possibilities, aiming to provide a comprehensive technological, economic and environmental overview of this sustainable energy solution for climate change mitigation, highlighting the critical role of innovation in addressing global challenges for a more sustainable future. Y1 - 2024 U6 - https://doi.org/https://doi.org/10.1016/B978-0-443-15740-0.00120-8 VL - 2024 ER - TY - GEN A1 - Mappas, Vassileios A1 - Dorneanu, Bogdan A1 - Vassiliadis, Vassilios S. A1 - Arellano-García, Harvey T1 - Multistage optimal control and nonlinear programming formulation for automated control loop selection T2 - Computer Aided Chemical Engineering N2 - 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. Y1 - 2024 U6 - https://doi.org/10.1016/B978-0-443-28824-1.50327-6 SN - 1570-7946 VL - 53 SP - 1957 EP - 1962 ER - TY - GEN A1 - Dorneanu, Bogdan A1 - Keykha, Mina A1 - Arellano-García, Harvey T1 - Assessment of parameter uncertainty in the maintenance scheduling of reverse osmosis networks via a multistage optimal control reformulation T2 - Computer Aided Chemical Engineering N2 - 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. Y1 - 2024 U6 - https://doi.org/10.1016/B978-0-443-28824-1.50326-4 SN - 1570-7946 VL - 53 SP - 1951 EP - 1956 ER - TY - GEN A1 - Dorneanu, Bogdan A1 - Zhang, Sushen A1 - Vassiliadis, Vassilios S. A1 - Arellano-García, Harvey T1 - Optimizing deep neural networks through hierarchical multiscale parameter tuning T2 - Computer Aided Chemical Engineering N2 - 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. Y1 - 2024 U6 - https://doi.org/10.1016/B978-0-443-28824-1.50155-1 SN - 1570-7946 VL - 53 SP - 925 EP - 930 ER - TY - GEN A1 - Vassiliadis, Vassilios S. A1 - Mappas, Vassileios A1 - Espaas, Tomas A. A1 - Dorneanu, Bogdan A1 - Isafiade, Adeniyi A1 - Möller, Klaus A1 - Arellano-García, Harvey T1 - Reloading process systems engineering within chemical engineering T2 - Chemical Engineering Research and Design N2 - 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. Y1 - 2024 UR - https://www.sciencedirect.com/science/article/pii/S0263876224004568?via%3Dihub U6 - https://doi.org/10.1016/j.cherd.2024.07.066 VL - 209 SP - 380 EP - 398 ER - TY - GEN A1 - Quinlan, Laura A1 - Brooks, Talia A1 - Ghaemi, Nasrin A1 - Arellano-García, Harvey A1 - Irandoost, Maryam A1 - Sharifianjazi, Fariborz A1 - Amini Horri, Bahman T1 - Synthesis and characterisation of nanocrystalline CoxFe1−xGDC powders as a functional anode material for the solid oxide fuel cell T2 - Materials N2 - 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. KW - Co KW - SOFC anode KW - solid oxide fuel cell KW - electrical conductivity KW - SOFC materials Y1 - 2024 U6 - https://doi.org/10.3390/ma17153864 SN - 1996-1944 VL - 17 IS - 15 PB - MDPI ER - TY - GEN A1 - Sohail, Norman A1 - Riedel, Ramona A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Prolonging the Life Span of Membrane in Submerged MBR by the Application of Different Anti-Biofouling Techniques T2 - Membranes N2 - 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. KW - Membrane bioreactor (MBR) KW - quorum sensing (QS) KW - quorum quenching (QQ) KW - moving bed biofilm reactor (MBBR) KW - moving bed biofilm membrane reactor (MBBMR) KW - model-based anti-fouling strategies Y1 - 2023 UR - https://www.mdpi.com/2077-0375/13/2/217 U6 - https://doi.org/10.3390/membranes13020217 SN - 2077-0375 VL - 13 IS - 2 ER - TY - GEN A1 - Dorneanu, Bogdan A1 - Heinzelmann, Norbert A1 - Schnitzlein, Klaus A1 - Arellano-García, Harvey T1 - BasMo - An interactive approach to modelling of trickle bed reactors T2 - Jahrestreffen der "Prozess-, Apparate- und Anlagentechnik", 21.–22. November 2022, Frankfurt am Main N2 - The trickle bed reactor (TBR), in which gas and liquid flow downward through a packed bed to undergo chemical reactions, is a frequently used solution for industrial multiphase exothermic catalytic reactions (e.g., hydrogenation, oxidation, etc.) due to flexibility and simplicity of operation and large annual throughput (Tan et al., 2021). They have significant advantages with respect to other solutions, but they also show complex behaviour, with uncertainties in catalyst heterogeneity, packing, fluid flow, and transport parameters, resulting in its modelling being highly challenging (Azarpour et al., 2021). In this contribution, the development of an interactive toolbox for the simulation of TBRs, based on the work of Schwidder & Schnitzlein (2012) is introduced. The implementation uses a modular and flexible setup, mirroring the multiscale nature of the phenomena tacking place in the reactor, from large scale of the reactor to the medium and low scale of the particle bed, fluid flow, as well as fluid-solid and fluid-fluid interactions, including chemical reactions. The toolbox enables implementation of complex geometries of the catalyst particles, enabled by a novel representation of the surface mesh. Validation using experimental data shows that the model is able to reliably predict the performance of the catalytic TBR. Y1 - 2022 UR - https://dechema.de/PAAT2022_Themen/_/_1_Programm_PAAT_2022_ezl.pdf ER - TY - GEN A1 - Straub, Adrian A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Towards a novel concept for solid energy storage T2 - Computer Aided Chemical Engineering N2 - 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. KW - Process design KW - Process modelling KW - Aspen Plus Y1 - 2023 U6 - https://doi.org/10.1016/B978-0-443-15274-0.50472-8 SN - 1570-7946 VL - Vol. 52 SP - 2965 EP - 2970 ER - TY - GEN A1 - Dorneanu, Bogdan A1 - Miah, Sayeef A1 - Mechleri, Evgenia A1 - Arellano-García, Harvey T1 - Multiobjective optimization of distributed energy systems design through 3E (economic, environmental and exergy) analysis T2 - Computer Aided Chemical Engineering N2 - 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. KW - Multiobjective optimization KW - Distributed energy systems KW - Exergy KW - Mixed-integer linear programming KW - Fuzzy-based methods Y1 - 2023 U6 - https://doi.org/10.1016/B978-0-443-15274-0.50473-X SN - 1570-7946 VL - Vol. 52 SP - 2971 EP - 2976 ER - TY - GEN A1 - Alves Amorim, Ana Paula A1 - Dorneanu, Bogdan A1 - Valverde Pontes, Karen A1 - Arellano-García, Harvey T1 - A framework for decision-making to encourage utilization of residential distributed energy systems in Brazil T2 - Computer Aided Chemical Engineering N2 - 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. KW - Distributeed energy systems KW - Microgrid KW - Mixed-integer non-linear programming KW - Net metering Y1 - 2023 U6 - https://doi.org/10.1016/B978-0-443-15274-0.50481-9 SN - 1570-7946 VL - Vol. 52 SP - 3019 EP - 3024 ER - TY - GEN A1 - Tarifa, Pilar A1 - Gonzalez-Castano, Miriam A1 - Cazana, Fernando A1 - Monzon, Antonio A1 - Arellano-García, Harvey T1 - Hydrophobic RWGS catalysts: valorization of CO2-rich streams in presence of CO/H2O T2 - Catalysis Today N2 - 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. Y1 - 2023 U6 - https://doi.org/10.1016/j.cattod.2023.114276 SN - 1873-4308 VL - Vol. 423 ER - TY - GEN A1 - Dorneanu, Bogdan A1 - Masham, Elliot A1 - Keykha, Mina A1 - Mechleri, Evgenia A1 - Cole, Rosanna A1 - Arellano-García, Harvey T1 - Assessment of centralised and localised ice cream supply chains using neighbourhood flow configuration models T2 - Supply Chain Analytics N2 - 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 £ 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. KW - supply chain management KW - flow configuration model KW - ice cream KW - Mixed-integer linear programming Y1 - 2023 UR - https://www.sciencedirect.com/science/article/pii/S2949863523000420 U6 - https://doi.org/10.1016/j.sca.2023.100043 VL - Vol. 4 ER - TY - GEN A1 - Cunha Cordeiro, José Luiz A1 - Safdar, Muddasar A1 - Aquino, Gabrielle S. A1 - Silva, Jefferson S. A1 - Paff, Jessica Sophie A1 - Valverde Pontes, Karen A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey A1 - Mascarenhas, Artur José T1 - Sustainable hydrogen production via biogas reforming over NiO-MxOy - Al2O3 catalysts (M = Na, K, Ca and Mg) T2 - 22 Congreso Brasileiro de Catalise N2 - A sustainable way to generate hydrogen is through dry biogas reforming, which uses methane gas and carbon dioxide to produce hydrogen. This study reveals partial results of the dry reforming of biogas in NiO-MxOy-Al2O3 catalysts (M=Na, K, Ca and Mg). The CO2 conversion varied between 79% and 94%, the CH4 conversion between 58% and 75%, the H2/CO ratio between 0.98 and 1.15 and the H2 yield between 37% and 45%. These values ​​surpass literary references and the industrial catalyst, highlighting the promise of these materials for sustainable hydrogen production. The catalyst with Ca stood out due to its higher surface basicity, exhibiting the best conversion results and yield in H2. Y1 - 2023 UR - https://submissao.cbcat.sbcat.org.br/index.php/2023-cbcat/article/view/409 ER - TY - GEN A1 - Safdar, Muddasar A1 - Shezad, Nasir A1 - Dorneanu, Bogdan A1 - Jafari, Mitra A1 - Shashank Bhat, Sharvendu A1 - Akhtar, Farid A1 - Arellano-García, Harvey T1 - Dry Reforming of Methane for the Syngas Production Catalyzed by Ni-doped Perovskites T2 - 15Th European Congress on Katakysis EUROPACAT2023 N2 - different perovskite-type supports considering ABO3 (such as A= Al, La with B=Ce and A=Mg, Mn with B=Zr) were prepared via the sol-gel method. Ni metal loading of 10 wt.% was deposited on prepared perovskite supports via the impregnation method. The catalysts were characterized using XRD and FTIR techniques. The DRM activity was carried out in a tubular reactor as described in our previous study [5]. The catalytic performance was assessed in the temperature range of 500–700 ◦C, CH4/CO2 = 1/1 and under GHSV of 12,000 h–1. Among the prepared catalysts, Ni-doped perovskite combination (i.e. A=Mg with B=Zr)O3-δ exhibited higher (CH4, CO2) conversion ca. (69, 59) percent and syngas yield of ca. (H2/CO =0.72) at 700 oC. This indicates that the magnesium zirconate perovskite catalyst established strong interfacial metal-support interaction, redox properties and surface basic sites that linked with good performance of the catalyst during DRM process. KW - Dry reforming of methane (DRM) KW - Ni-Perovskites KW - Syngas production KW - Greenhouse gases (GHGs) Y1 - 2023 ER - TY - GEN A1 - Mappas, Vassileios A1 - Vassiliadis, Vassilios S. A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Use of Multistage Optimal Control Principles for Novel Design and Implementation of Classical Controllers T2 - AIChE Annual Meeting N2 - Classical controllers, such as Proportional-Integral (PI) and Proportional-Integral Derivative (PID) controllers, are the most long-established and widely used in industry. Various methods for tuning these types of controllers exist (Ziegler et al., 1942; Blondin et al., 2018; Do et al., 2021), and up to this point, there is no fruitful avenue to improve their performance. In this contribution, a new approach for PI and PID controller implementation, based on a Multistage Optimal Control (MSOCP) approach is introduced. Our approach incorporates path and end-point constraints during its controller tuning phase, as well as parameter and disturbance uncertainty. The proposed framework is applied for different case studies and is able to reject any disturbances introduced to the examined systems, with or without uncertainty, satisfies end-point constraints and exhibits quicker response for switching steady states, compared to classical methods. Other aspects of controller design and incorporation within industrial process models, as related to using rigorous optimization methodologies and implementations, will further be highlighted within the context of the PI and PID controllers. Y1 - 2021 UR - https://aiche.confex.com/aiche/2021/meetingapp.cgi/Paper/630692 ER - TY - GEN A1 - Mappas, Vassileios A1 - Vassiliadis, Vassilios S. A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Automated Control Loop Selection Via Multistage Optimal Control Formulation and Nonlinear Programming T2 - Chemical Engineering Research and Design N2 - 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. KW - control loop selection KW - controller tuning KW - feasible path approach KW - multistage integer nonlinear optimal control problem (MSINOCP) KW - dynamic constraints Y1 - 2023 U6 - https://doi.org/10.1016/j.cherd.2023.05.041 SN - 1744-3563 VL - 195 SP - 76 EP - 95 ER - TY - GEN A1 - Jafari, Mitra A1 - Safdar, Muddasar A1 - Dorneanu, Bogdan A1 - Gonzalez-Castaño, Miriam A1 - Arellano-García, Harvey T1 - Green and sustainable fuel from syngas via the Fischer-Tropsch synthesis process: Bifunctional cobalt-based catalysts T2 - 14th European Congress of Chemical Engineering and 7th European Congress of Applied Biotechnology N2 - This paper reviews and compares state-of-the-art cobalt-based catalysts and catalytic systems used to produce green and sustainable fuels using FTS. Being focused on comparing the effect of the catalyst formulation and synthesis method, the reactor type and operating parameters, as well as the quality of the obtained fuels, the aim is to identify the research gaps between these relevant research areas concerning production of green and sustainable fuels. Y1 - 2023 UR - https://dechema.converia.de/frontend/index.php?page_id=15565&additions_conferenceschedule_action=detail&additions_conferenceschedule_controller=paperList&pid=44228&hash=be231d3139d7d89da32b1610b7a0d1af3770c06640f246348e3ca8cfa7dd324a ER - TY - GEN A1 - Plattfaut, Julia A1 - Suckow, Matthias A1 - Klepel, Olaf A1 - Erlitz, Marcel A1 - Arellano-García, Harvey T1 - Modellierung und Simulation der templatgestützten Synthese von porösen Kohlenstoffgerüsten mittels COMSOL Multiphysics T2 - Chemie Ingenieur Technik N2 - Mithilfe einer templatgestützten Synthese wurden poröse Kohlenstoffgerüste 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 zusätzliche Beschreibung der laminaren Strömung verbessert die Übereinstimmung deutlich. Y1 - 2023 U6 - https://doi.org/10.1002/cite.202300014 SN - 1522-2640 VL - 96(2024) IS - 3 SP - 318 EP - 328 ER - TY - GEN A1 - Zhang, Sushen A1 - Vassiliadis, Vassilios S. A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Hierarchical multi-scale parametric optimization of deep neural networks T2 - Applied Intelligence N2 - 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. KW - Deep neural networks KW - Hierarchical multi-scale search KW - Scaling factor KW - Sensitivity analysis KW - Finite difference KW - Automatic differentiation Y1 - 2023 U6 - https://doi.org/10.1007/s10489-023-04745-8 SN - 1573-7497 VL - 53 IS - 21 SP - 24963 EP - 24990 ER -