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  <doc>
    <id>30104</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>338</volume>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-01-19</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">In-Situ Drifts Steady-State Study of Co2 and Co Methanation Over Ni-Promoted Catalysts</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="eng">Fuel</parentTitle>
    <identifier type="url">https://www.sciencedirect.com/science/article/pii/S0016236122040650?via%3Dihub</identifier>
    <identifier type="doi">10.1016/j.fuel.2022.127241</identifier>
    <identifier type="issn">1873-7153</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="Artikelnummer">127241</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
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    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Miriam</firstName>
      <lastName>Gonzalez-Castaño</lastName>
    </author>
    <submitter>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </submitter>
    <author>
      <firstName>Judith</firstName>
      <lastName>Gonzalez-Arias</lastName>
    </author>
    <author>
      <firstName>Luis F.</firstName>
      <lastName>Bobadilla</lastName>
    </author>
    <author>
      <firstName>E.</firstName>
      <lastName>Ruiz-Lopez</lastName>
    </author>
    <author>
      <firstName>Jose Antonio</firstName>
      <lastName>Odriozola</lastName>
    </author>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
  <doc>
    <id>30184</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>56</volume>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-01-28</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Global sensitivity analysis for design and operation of distributed energy systems: A two-stage approach</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="eng">Sustainable Energy Technologies and Assessments</parentTitle>
    <identifier type="url">https://www.sciencedirect.com/science/article/pii/S2213138823000565?dgcid=author</identifier>
    <identifier type="doi">10.1016/j.seta.2023.103064</identifier>
    <identifier type="issn">2213-1388</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="Artikelnummer">103064</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Ishanki</firstName>
      <lastName>De Mel</lastName>
    </author>
    <submitter>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </submitter>
    <author>
      <firstName>Panagiotis</firstName>
      <lastName>Demis</lastName>
    </author>
    <author>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </author>
    <author>
      <firstName>Oleksiy</firstName>
      <lastName>Klymenko</lastName>
    </author>
    <author>
      <firstName>Evgenia</firstName>
      <lastName>Mechleri</lastName>
    </author>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
  <doc>
    <id>30263</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>1</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject_ref</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-02-03</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Towards smart distributed energy systems</title>
    <abstract language="eng">A distributed energy resource (DER) system is an energy generation system located in the vicinity of the end users, simultaneously providing electricity, cooling and heating to meet the demands of the local users1. Unlike conventional, centralized energy supply, a DER system typically employs a wide range of technologies such as photovoltaics, wind turbines, gas turbines, biomass boilers, combined heating and power, absorption chillers, etc. In addition, energy storage technologies (batteries, hot/cold water storage) are available as well. DER systems can potentially play a vital role as the energy sector faces unprecedented challenges to reduce emissions by increasing energy generation using renewable and low-carbon energy resources.&#13;
Different designs of the DER systems could lead to different performance in reducing the costs, the environmental impact or the use of primary energy. Hence, optimal design and management of complex DER systems are important tasks to promote their diffusion against the centralized grid. However, current operational models for DERs do not adequately analyse the complexity of such systems.&#13;
This contribution presents a set of models for the optimal design and operation of residential DER systems, which build up on previous work in this field, and aims to provide a more holistic overview of such systems. For each node in the DER system, there is an option of installing the following ten technologies: wind turbines, photovoltaics arrays, combined heating and power units, absorption chillers, air-conditioning units, gas boilers, biomass boilers, gas heaters, batteries and thermal storage. Only one of each item may be installed in each home. There is also the option to connect a house to another via a combined hot and cold water pipeline and/or a microgrid cable, to share thermal and electrical energy, respectively. Due to increased availability of government incentives such as the feed-in tariffs (FIT) and renewable heat incentives (RHI) payments, these are included in the model as well.&#13;
The increased penetration of Internet of Things technology and their potential to better control and optimize DER systems enable its use to help stabilize national grids. To this end, the models include the use of dynamic pricing, a strategy in which national grids publish in real time variable prices for electricity within given time periods.&#13;
Furthermore, as current literature’s focus on economic and environmental cost minimization, which do not satisfy long-term sustainability priorities through the rational use of energy resources, the introduction of a third criteria, exergy, is investigated. A third novelty of this contribution is the consideration of a multi-objective optimization which simultaneously includes the three objectives: the economic, the environmental and exergetic criteria in the design and operation of the residential DER system.&#13;
Additionally, a novel methodology to analyse the effect of uncertain input variables on the total daily cost of the DER operational models. The methodology combines the operational model with model predictive control to predict the current state of the model. A subset of the model inputs (i.e., electricity demand, heating demand, and insolation) are considered uncertain. Global sensitivity analysis is conducted to quantify and understand how the uncertain variables influence, both individually and through interactions, the total daily cost.&#13;
Finally, the implementation of blockchain technology and smart contracts within optimally designed and scheduled DER systems is investigated, to assess the advantages of smart technologies on the efficiency of residential DERs. Challenges, limitations and suggestions for improving the overall design and operation are also discussed in detail.&#13;
All models are developed as mixed-integer linear programming models implemented and solved in GAMS, and show significant reduction of costs for all considered criteria when compared to the centralised grid and the classical approach towards the modelling of DER systems.</abstract>
    <parentTitle language="eng">Jahrestreffen der ProcessNet-Fachgemeinschaften "Prozess-, Apparate- und Anlagentechnik" (PAAT)</parentTitle>
    <identifier type="url">https://www.researchgate.net/publication/388185482_Towards_smart_distributed_energy_systems</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </author>
    <submitter>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </submitter>
    <author>
      <firstName>Evgenia</firstName>
      <lastName>Mechleri</lastName>
    </author>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
  <doc>
    <id>30340</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue>2</issue>
    <volume>13</volume>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-02-09</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Prolonging the Life Span of Membrane in Submerged MBR by the Application of Different Anti-Biofouling Techniques</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="eng">Membranes</parentTitle>
    <identifier type="url">https://www.mdpi.com/2077-0375/13/2/217</identifier>
    <identifier type="doi">10.3390/membranes13020217</identifier>
    <identifier type="issn">2077-0375</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="Artikelnummer">217</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Norman</firstName>
      <lastName>Sohail</lastName>
    </author>
    <submitter>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </submitter>
    <author>
      <firstName>Ramona</firstName>
      <lastName>Riedel</lastName>
    </author>
    <author>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </author>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Membrane bioreactor (MBR)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>quorum sensing (QS)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>quorum quenching (QQ)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>moving bed biofilm reactor (MBBR)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>moving bed biofilm membrane reactor (MBBMR)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>model-based anti-fouling strategies</value>
    </subject>
    <collection role="institutes" number="2305">FG Biotechnologie der Wasseraufbereitung</collection>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
  <doc>
    <id>31109</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>2965</pageFirst>
    <pageLast>2970</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>Vol. 52</volume>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-06-23</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Towards a novel concept for solid energy storage</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="eng">Computer Aided Chemical Engineering</parentTitle>
    <identifier type="issn">1570-7946</identifier>
    <identifier type="doi">10.1016/B978-0-443-15274-0.50472-8</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Adrian</firstName>
      <lastName>Straub</lastName>
    </author>
    <submitter>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </submitter>
    <author>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </author>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process design</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process modelling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Aspen Plus</value>
    </subject>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
  <doc>
    <id>31110</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>2971</pageFirst>
    <pageLast>2976</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>Vol. 52</volume>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-06-23</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Multiobjective optimization of distributed energy systems design through 3E (economic, environmental and exergy) analysis</title>
    <abstract language="eng">Distributed energy systems (DES) are promising alternative to conventional centralized generation, with multiple financial incentives in many parts of the world. Current approaches&#13;
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.</abstract>
    <parentTitle language="eng">Computer Aided Chemical Engineering</parentTitle>
    <identifier type="issn">1570-7946</identifier>
    <identifier type="doi">10.1016/B978-0-443-15274-0.50473-X</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </author>
    <submitter>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </submitter>
    <author>
      <firstName>Sayeef</firstName>
      <lastName>Miah</lastName>
    </author>
    <author>
      <firstName>Evgenia</firstName>
      <lastName>Mechleri</lastName>
    </author>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Multiobjective optimization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Distributed energy systems</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Exergy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mixed-integer linear programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Fuzzy-based methods</value>
    </subject>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
  <doc>
    <id>31111</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>3019</pageFirst>
    <pageLast>3024</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>Vol. 52</volume>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-06-23</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A framework for decision-making to encourage utilization of residential distributed energy systems in Brazil</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="eng">Computer Aided Chemical Engineering</parentTitle>
    <identifier type="issn">1570-7946</identifier>
    <identifier type="doi">10.1016/B978-0-443-15274-0.50481-9</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Ana Paula</firstName>
      <lastName>Alves Amorim</lastName>
    </author>
    <submitter>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </submitter>
    <author>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </author>
    <author>
      <firstName>Karen</firstName>
      <lastName>Valverde Pontes</lastName>
    </author>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Distributeed energy systems</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Microgrid</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mixed-integer non-linear programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Net metering</value>
    </subject>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
  <doc>
    <id>31157</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>Vol. 423</volume>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-07-05</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Hydrophobic RWGS catalysts: valorization of CO2-rich streams in presence of CO/H2O</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="eng">Catalysis Today</parentTitle>
    <identifier type="doi">10.1016/j.cattod.2023.114276</identifier>
    <identifier type="issn">1873-4308</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="Artikelnummer">114276</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Pilar</firstName>
      <lastName>Tarifa</lastName>
    </author>
    <submitter>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </submitter>
    <author>
      <firstName>Miriam</firstName>
      <lastName>Gonzalez-Castano</lastName>
    </author>
    <author>
      <firstName>Fernando</firstName>
      <lastName>Cazana</lastName>
    </author>
    <author>
      <firstName>Antonio</firstName>
      <lastName>Monzon</lastName>
    </author>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
  <doc>
    <id>31391</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>Vol. 4</volume>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-10-06</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Assessment of centralised and localised ice cream supply chains using neighbourhood flow configuration models</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="eng">Supply Chain Analytics</parentTitle>
    <identifier type="url">https://www.sciencedirect.com/science/article/pii/S2949863523000420</identifier>
    <identifier type="doi">10.1016/j.sca.2023.100043</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="Artikelnummer">100043</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </author>
    <submitter>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </submitter>
    <author>
      <firstName>Elliot</firstName>
      <lastName>Masham</lastName>
    </author>
    <author>
      <firstName>Mina</firstName>
      <lastName>Keykha</lastName>
    </author>
    <author>
      <firstName>Evgenia</firstName>
      <lastName>Mechleri</lastName>
    </author>
    <author>
      <firstName>Rosanna</firstName>
      <lastName>Cole</lastName>
    </author>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>supply chain management</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>flow configuration model</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>ice cream</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mixed-integer linear programming</value>
    </subject>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
  <doc>
    <id>31406</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject_ref</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-10-09</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Sustainable hydrogen production via biogas reforming over NiO-MxOy - Al2O3 catalysts (M = Na, K, Ca and Mg)</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="eng">22 Congreso Brasileiro de Catalise</parentTitle>
    <identifier type="url">https://submissao.cbcat.sbcat.org.br/index.php/2023-cbcat/article/view/409</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>José Luiz</firstName>
      <lastName>Cunha Cordeiro</lastName>
    </author>
    <submitter>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </submitter>
    <author>
      <firstName>Muddasar</firstName>
      <lastName>Safdar</lastName>
    </author>
    <author>
      <firstName>Gabrielle S.</firstName>
      <lastName>Aquino</lastName>
    </author>
    <author>
      <firstName>Jefferson S.</firstName>
      <lastName>Silva</lastName>
    </author>
    <author>
      <firstName>Jessica Sophie</firstName>
      <lastName>Paff</lastName>
    </author>
    <author>
      <firstName>Karen</firstName>
      <lastName>Valverde Pontes</lastName>
    </author>
    <author>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </author>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <author>
      <firstName>Artur José</firstName>
      <lastName>Mascarenhas</lastName>
    </author>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
  <doc>
    <id>31407</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>image</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-10-09</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Dry Reforming of Methane for the Syngas Production Catalyzed by Ni-doped Perovskites</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="eng">15Th European Congress on Katakysis EUROPACAT2023</parentTitle>
    <identifier type="old">https://www.europacat2023.cz/Amca-Europacat2021/media/content/Program/Posters-MON-1.pdf</identifier>
    <identifier type="old">https://www.europacat2023.cz/</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Artikelnummer">DES-P-103</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Muddasar</firstName>
      <lastName>Safdar</lastName>
    </author>
    <submitter>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </submitter>
    <author>
      <firstName>Nasir</firstName>
      <lastName>Shezad</lastName>
    </author>
    <author>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </author>
    <author>
      <firstName>Mitra</firstName>
      <lastName>Jafari</lastName>
    </author>
    <author>
      <firstName>Sharvendu</firstName>
      <lastName>Shashank Bhat</lastName>
    </author>
    <author>
      <firstName>Farid</firstName>
      <lastName>Akhtar</lastName>
    </author>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Dry reforming of methane (DRM)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Ni-Perovskites</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Syngas production</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Greenhouse gases (GHGs)</value>
    </subject>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
  <doc>
    <id>30976</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>76</pageFirst>
    <pageLast>95</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>195</volume>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-05-30</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Automated Control Loop Selection Via Multistage Optimal Control Formulation and Nonlinear Programming</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="eng">Chemical Engineering Research and Design</parentTitle>
    <identifier type="doi">10.1016/j.cherd.2023.05.041</identifier>
    <identifier type="issn">1744-3563</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Vassileios</firstName>
      <lastName>Mappas</lastName>
    </author>
    <submitter>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </submitter>
    <author>
      <firstName>Vassilios S.</firstName>
      <lastName>Vassiliadis</lastName>
    </author>
    <author>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </author>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>control loop selection</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>controller tuning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>feasible path approach</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>multistage integer nonlinear optimal control problem (MSINOCP)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>dynamic constraints</value>
    </subject>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
  <doc>
    <id>31359</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject_ref</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-09-25</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Green and sustainable fuel from syngas via the Fischer-Tropsch synthesis process: Bifunctional cobalt-based catalysts</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="eng">14th European Congress of Chemical Engineering and 7th European Congress of Applied Biotechnology</parentTitle>
    <identifier type="url">https://dechema.converia.de/frontend/index.php?page_id=15565&amp;additions_conferenceschedule_action=detail&amp;additions_conferenceschedule_controller=paperList&amp;pid=44228&amp;hash=be231d3139d7d89da32b1610b7a0d1af3770c06640f246348e3ca8cfa7dd324a</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Artikelnummer">A1.10</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Mitra</firstName>
      <lastName>Jafari</lastName>
    </author>
    <submitter>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </submitter>
    <author>
      <firstName>Muddasar</firstName>
      <lastName>Safdar</lastName>
    </author>
    <author>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </author>
    <author>
      <firstName>Miriam</firstName>
      <lastName>Gonzalez-Castaño</lastName>
    </author>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
  <doc>
    <id>31360</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>318</pageFirst>
    <pageLast>328</pageLast>
    <pageNumber/>
    <edition/>
    <issue>3</issue>
    <volume>96(2024)</volume>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-09-25</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Modellierung und Simulation der templatgestützten Synthese von porösen Kohlenstoffgerüsten mittels COMSOL Multiphysics</title>
    <abstract language="deu">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.</abstract>
    <parentTitle language="deu">Chemie Ingenieur Technik</parentTitle>
    <identifier type="doi">10.1002/cite.202300014</identifier>
    <identifier type="issn">1522-2640</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Julia</firstName>
      <lastName>Plattfaut</lastName>
    </author>
    <submitter>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </submitter>
    <author>
      <firstName>Matthias</firstName>
      <lastName>Suckow</lastName>
    </author>
    <author>
      <firstName>Olaf</firstName>
      <lastName>Klepel</lastName>
    </author>
    <author>
      <firstName>Marcel</firstName>
      <lastName>Erlitz</lastName>
    </author>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <collection role="institutes" number="2205">FG Technische Chemie</collection>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
  <doc>
    <id>31218</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>24963</pageFirst>
    <pageLast>24990</pageLast>
    <pageNumber/>
    <edition/>
    <issue>21</issue>
    <volume>53</volume>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
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    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-07-31</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Hierarchical multi-scale parametric optimization of deep neural networks</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="eng">Applied Intelligence</parentTitle>
    <identifier type="doi">10.1007/s10489-023-04745-8</identifier>
    <identifier type="issn">1573-7497</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Sushen</firstName>
      <lastName>Zhang</lastName>
    </author>
    <submitter>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </submitter>
    <author>
      <firstName>Vassilios S.</firstName>
      <lastName>Vassiliadis</lastName>
    </author>
    <author>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </author>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Deep neural networks</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Hierarchical multi-scale search</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Scaling factor</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Sensitivity analysis</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Finite difference</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Automatic differentiation</value>
    </subject>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
  <doc>
    <id>32042</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>2</pageNumber>
    <edition/>
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    <completedDate>2023-11-27</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Synthesis and Characterizations of Ni-doped Perovskite-Type Oxides for Effective CO2 methanation</title>
    <abstract language="eng">This work proposes Ni metal supported over rare earth-based emerging perovskite-type oxides as potential catalysts for the CO2 methanation. Presence of oxygen vacancies in perovskite-like materials enable them to exhibit higher catalytic activity. Furthermore, to tune the surface basicity, metal-support interaction and to enhance the activation of CO2, rare earth metals (La, Ce, etc.) are considered best candidates. Moreover, different perovskite-type supports (AxMnxO3, A= La, Ce) based on A-side substitution of rare earth metals were prepared with Ni metal loading of 10 wt.% via impregnation method.</abstract>
    <parentTitle language="eng">14th European Congress of Chemical Engineering and 7th European Congress of Applied Biotechnology</parentTitle>
    <identifier type="url">https://dechema.converia.de/frontend/index.php?page_id=13659&amp;v=List&amp;do=15&amp;day=all&amp;ses=9628#</identifier>
    <identifier type="doi">10.5281/zenodo.10376612</identifier>
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    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <submitter>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </submitter>
    <author>
      <firstName>Muddasar</firstName>
      <lastName>Safdar</lastName>
    </author>
    <author>
      <firstName>Nasir</firstName>
      <lastName>Shezad</lastName>
    </author>
    <author>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </author>
    <author>
      <firstName>Farid</firstName>
      <lastName>Akhtar</lastName>
    </author>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
  <doc>
    <id>32044</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>15</pageFirst>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>image</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation>DECHEMA</contributingCorporation>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-11-27</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Quantum annealing for global optimization in Chemical Engineering</title>
    <abstract language="eng">Classical computing has experienced rapid growth in computational power, driven by the need to address increasingly complex industrial problems. The domain of global optimization plays a vital role in various applications, including optimal control, scheduling and assignment problems, or machine learning parameter selection. Currently, deterministic optimization techniques based on classical computing fail to deliver reasonable solutions within practical time constraints. Consequently, reliance on heuristic methods becomes common, albeit with no guarantee of solution quality. While ongoing algorithmic refinements lead to gradual enhancements in global optimization, they do little to address the fundamental issue of computational intractability. With the advent of quantum computing, a natural question arises: Can quantum methods offer advancements beyond classical approaches? Quantum annealing emerges as a promising subfield within quantum computing, necessitating the reformulation of problems as quadratic unconstrained binary optimization (QUBO) problems. In this contribution, a novel approach is introduced to transform relevant problems in Chemical Engineering into QUBO at two distinct levels of granularity. Subsequently, these problem systems are embedded within virtual quantum machines employing two different architectures. Additionally, a comparative analysis is performed, wherein the same problem is solved utilizing both classical global optimization methods based on metaheuristics and a hypothetical quantum annealer. The findings indicate that annealing-based solving methods exhibit the most potential, indicating their applicability to the transformed formulation Chemical Engineering problems.</abstract>
    <parentTitle language="deu">Jahrestreffen "Prozess-, Apparate- und Anlagentechnik" - PAAT 2023, Frankfurt am Main</parentTitle>
    <identifier type="url">https://dechema.de/PAAT2023_Prg/_/__Progr_PAAT_2023_final.pdf</identifier>
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    <enrichment key="opus.source">publish</enrichment>
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    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </author>
    <submitter>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </submitter>
    <author>
      <firstName>Eduardo</firstName>
      <lastName>Nolasco</lastName>
    </author>
    <author>
      <firstName>Vassilios S.</firstName>
      <lastName>Vassiliadis</lastName>
    </author>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
  <doc>
    <id>32005</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject_ref</type>
    <publisherName>Mining Engineering</publisherName>
    <publisherPlace>Falmouth (UK)</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation>Min-Eng Ltd.</contributingCorporation>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-11-17</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Comparative studies on the quality of recovered secondary graphites from the recycling of lithium-ion traction batteries</title>
    <abstract language="eng">Automotive technology is increasingly determined by drives based on electric motors in combination with batteries. The lithium-ion traction battery is a storage medium that combines high electrical efficiency with compact dimensions and relatively low weight. For the recycling of the cathode coatings (esp. Ni, Mn, Co) and peripheral battery components a variety of recycling options already exist. The graphite coating of the anodes has hardly been the focus of research activities to date. State of the art is currently the melting of the complete Copper-anode foils including graphite coating, whereby the graphite contributes only as a carbon carrier to the recycling of the copper. Separation and reuse of the very high-quality graphite on an industrial scale has not yet taken place.&#13;
At the BTU, a methodology has been developed, with which recovered anode graphites from traction batteries can be comprehensively characterised chemically and mechanically-physically. On this basis, targeted preparation for secondary applications is possible. The secondary graphites achieve a quality&#13;
that allows them to be reused as second-use anode material and for other applications.</abstract>
    <parentTitle language="eng">Sustainable Minerals</parentTitle>
    <identifier type="url">https://www.ceecthefuture.org/resource-center/comparative-studies-on-the-quality-of-recovered-secondary-graphites-from-the-recycling-of-lithium-ion-traction-batteries</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="RelationnotEU">16EM5006</enrichment>
    <enrichment key="BTUfunderNamenotEU">BMWK</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Jens</firstName>
      <lastName>Markowski</lastName>
    </author>
    <submitter>
      <firstName>Jens</firstName>
      <lastName>Markowski</lastName>
    </submitter>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <author>
      <firstName>André</firstName>
      <lastName>Meißner</lastName>
    </author>
    <author>
      <firstName>Jörg</firstName>
      <lastName>Acker</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Graphitrecycling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Li-Ionen-Traction Batteries</value>
    </subject>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
  <doc>
    <id>32027</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>Vol. 20</volume>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-11-23</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Superhydrophobic ZIF-67 with exceptional hydrostability</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="eng">Materials Today Advances</parentTitle>
    <identifier type="doi">10.1016/j.mtadv.2023.100448</identifier>
    <identifier type="issn">2590-0498</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Artikelnummer">100448</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <submitter>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </submitter>
    <author>
      <firstName>Muddasar</firstName>
      <lastName>Safdar</lastName>
    </author>
    <author>
      <firstName>Allana</firstName>
      <lastName>Lewis</lastName>
    </author>
    <author>
      <firstName>Norbert</firstName>
      <lastName>Radacsi</lastName>
    </author>
    <author>
      <firstName>Xianfeng</firstName>
      <lastName>Fan</lastName>
    </author>
    <author>
      <firstName>Yi</firstName>
      <lastName>Huang</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>ZIF-67</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Superhydrophobicity</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Hydrostability</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Cosolvent-stabilization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>CO2 methanation</value>
    </subject>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
  <doc>
    <id>32332</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>744</pageFirst>
    <pageLast>756</pageLast>
    <pageNumber/>
    <edition/>
    <issue>3</issue>
    <volume>8</volume>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-01-09</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Are Ni/ and Ni5Fe1/biochar catalysts suitable for synthetic natural gas production? A comparison with γ-Al2O3 supported catalysts</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="eng">Green Energy &amp; Environment</parentTitle>
    <identifier type="issn">2468-0257</identifier>
    <identifier type="doi">10.1016/j.gee.2021.05.007</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Miriam</firstName>
      <lastName>Gonzalez-Castãno</lastName>
    </author>
    <submitter>
      <firstName>Karsten</firstName>
      <lastName>Henkel</lastName>
    </submitter>
    <author>
      <firstName>Carlos</firstName>
      <lastName>Morales</lastName>
    </author>
    <author>
      <firstName>Juan Carlos</firstName>
      <lastName>Navarro de Miguel</lastName>
    </author>
    <author>
      <firstName>Jens-H.</firstName>
      <lastName>Boelte</lastName>
    </author>
    <author>
      <firstName>Olaf</firstName>
      <lastName>Klepel</lastName>
    </author>
    <author>
      <firstName>Jan Ingo</firstName>
      <lastName>Flege</lastName>
    </author>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Biochar catalysts</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Carbon catalysts</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Ni catalysts</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>NiFe alloy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Bimetallic catalysts</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Synthetic natural gas</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>CO2 methanation</value>
    </subject>
    <collection role="institutes" number="1503">FG Angewandte Physik und Halbleiterspektroskopie</collection>
    <collection role="institutes" number="2205">FG Technische Chemie</collection>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
</export-example>
