TY - GEN A1 - Arellano-García, Harvey A1 - Safdar, Muddasar A1 - Lewis, Allana A1 - Radacsi, Norbert A1 - Fan, Xianfeng A1 - Huang, Yi T1 - Superhydrophobic ZIF-67 with exceptional hydrostability T2 - Materials Today Advances N2 - 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. KW - ZIF-67 KW - Superhydrophobicity KW - Hydrostability KW - Cosolvent-stabilization KW - CO2 methanation Y1 - 2023 U6 - https://doi.org/10.1016/j.mtadv.2023.100448 SN - 2590-0498 VL - Vol. 20 ER - TY - GEN A1 - Gonzalez-Castãno, Miriam A1 - Morales, Carlos A1 - Navarro de Miguel, Juan Carlos A1 - Boelte, Jens-H. A1 - Klepel, Olaf A1 - Flege, Jan Ingo A1 - Arellano-García, Harvey T1 - Are Ni/ and Ni5Fe1/biochar catalysts suitable for synthetic natural gas production? A comparison with γ-Al2O3 supported catalysts T2 - Green Energy & Environment N2 - 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. KW - Biochar catalysts KW - Carbon catalysts KW - Ni catalysts KW - NiFe alloy KW - Bimetallic catalysts KW - Synthetic natural gas KW - CO2 methanation Y1 - 2023 U6 - https://doi.org/10.1016/j.gee.2021.05.007 SN - 2468-0257 VL - 8 IS - 3 SP - 744 EP - 756 ER - TY - CHAP A1 - González-Castaño, Miriam A1 - Tarifa, Pilar A1 - Monzon, Antonio A1 - Arellano-García, Harvey T1 - Valorization of unconventional CO2-rich feedstock via Reverse Water Gas Shift reaction T2 - Circular Economy Processes for CO2 Capture and Utilization : Strategies and Case Studies N2 - The implementation of novel CO2 valorization technologies is one of the most promising approaches towards the achievement of sustainable energy models. This chapter highlights the importance of carbon capture and utilization technologies and proposes novel approaches for the valorization of CO2-rich feedstock derived from thermochemical biomass conversion through the production of syngas mixtures via the Reverse Water Gas Shift reaction. After, this classification of the different types of nonconventional gases and biomass-treatment processes, we have also revised the fundamentals of the Reverse Water Gas Shift reaction and the impact of species commonly present in CO2-rich streams on the performance of the catalytic systems are also reviewed. Finally, a catalytic bi-functionalization approach that ensures larger CO productivity from simulated biomass-derived CO2-rich feedstock is demonstrated. KW - Reverse Water Gas Shift KW - Valorization of CO2 KW - Syngas KW - Catalysts Y1 - 2024 SN - 9780323956697 U6 - https://doi.org/10.1016/B978-0-323-95668-0.00001-1 SP - 307 EP - 323 PB - Woodhead Publishing ER - TY - GEN A1 - Safdar, Muddasar A1 - Dorneanu, Bogdan A1 - Paff, Jessica Sophie A1 - Arellano-García, Harvey T1 - Structural formability of perovskite ABO3 oxide system synthesized via autocombustion technique, ruled by geometric factors T2 - 18th International Congress on Catalysis Y1 - 2024 UR - https://www.researchgate.net/publication/388109875_Structural_formability_of_perovskite_ABO3_oxide_system_synthesized_via_auto-_combustion_technique_ruled_by_geometric_factors ER - TY - GEN A1 - Jafari, Mitra A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Machine learning application in kinetic studies: A review T2 - 18th International Congress on Catalysis N2 - Machine learning (ML) brings new opportunities in the field of heterogenous catalysis and reaction engineering. Here, the advancements brought by ML in the field of kinetic studies are reviewed. Y1 - 2024 UR - https://www.researchgate.net/publication/388109595_Machine_learning_application_in_kinetic_studies_A_review ER - TY - GEN A1 - Shafiee, Parisa A1 - Mbuya, Christel-Olivier Lenge A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Novel approaches for preparation of 3D Ni-Al2O3 core with zeolite shell catalysts for dry reforming of methane T2 - 18th International Congress on Catalysis Y1 - 2024 UR - https://www.researchgate.net/publication/388109598_Novel_Approaches_for_Preparation_of_3D_Ni-Al2O3_Core_with_Zeolite_Shell_Catalysts_for_Dry_Reforming_of_Methane ER - TY - GEN A1 - Cunha Cordeiro, José Luiz A1 - Silva de Aquino, Gabrielle A1 - Santos da Silva, Jefferson A1 - Safdar, Muddasar A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey A1 - Valverde Pontes, Karen A1 - Santos Mascarenhas, Artur José T1 - Estudo do efeito do suporte em catalisadores de Ni preparados pelo método da combustão aplicados na reforma a seco do biogás para produção de hidrogênio sustentável T2 - 63rd Brazilian Chemistry Congress Y1 - 2024 UR - https://www.researchgate.net/publication/388109502_Estudo_do_efeito_do_suporte_em_catalisadores_de_Ni_preparados_pelo_metodo_da_combustao_aplicados_na_reforma_a_seco_do_biogas_para_producao_de_hidrogenio_sustentavel ER - TY - GEN A1 - Dorneanu, Bogdan A1 - Farhadi, Maryam A1 - Arellano-García, Harvey T1 - Conceptual design of a reactive distillation column for the catalytic upgrade of ABE T2 - Jahrestreffen der DECHEMA-Fachgruppe Fluidverfahresntechnik Y1 - 2024 UR - https://www.researchgate.net/publication/388143625_Conceptual_design_of_a_reactive_distillation_column_for_the_catalytic_upgrade_of_ABE ER - TY - GEN A1 - Dorneanu, Bogdan A1 - Mappas, Vassileios A1 - Vassiliadis, Vassilios S. A1 - Arellano-García, Harvey T1 - A second-order linesearch procedure within Newton’s method for highly nonlinear steady-state systems simulation T2 - 2024 AIChE Annual Meeting N2 - Linesearch, a crucial component of Newton’s method, ensures global convergence, guaranteeing convergence to a local solution from any starting point while satisfying all simultaneous nonlinear equations (Bellavia and Morini, 2003). Despite Newton’s method being considered established both theoretically and algorithmically, leaving little room for further improvements, this contribution focuses on enhancing the linesearch procedure and revealing significant advancements over existing methods. Specifically, this study aims to incorporate second-order information in a computationally efficient manner to improve the performance of the linesearch procedure, especially for highly nonlinear equation systems. Nonlinearity, particularly near the starting point, can substantially hinder algorithmic efficiency, necessitating frequent step reductions at the expense of function evaluations and major iterations involving Jacobian evaluations and factorizations (Gill and Zhang, 2024). The proposed approach leverages a a higher-order Taylor series expansion around the operating point of a major iteration in Newton’s algorithm, coupled with a custom Jacobian vector product finite difference scheme. This combination requires only one additional Jacobian evaluation to construct a locally accurate fourth-degree polynomial approximating the merit function along the search direction. In addition to the theoretical advancements, this contribution provides computational evidence supporting the claim that for highly nonlinear systems, significant computational savings and enhanced solution procedure stability can be achieved. Utilizing a Python implementation, linear subsets of equations are treated separately to boost the efficiency of function and Jacobian evaluations, aligning with standard practices in professional software development. While Python may not be a high-performance language, its suitability for rapid algorithm prototyping and validation precedes potential transfer to higher-performance languages like C++. Moreover, given Newton’s method central roles in various iterative solution tools, such as its repeated use within a Differential-Algebraic Equations (DAEs) integrators and potentially Partial Differential-Algebraic Equations (PDAEs) solvers, the significance of this work extends even further. Future research endeavors will explore these areas, building upon the foundations laid by this study. Y1 - 2024 UR - https://aiche.confex.com/aiche/2024/meetingapp.cgi/Paper/689676 ER - TY - GEN A1 - Shafiee, Parisa A1 - Dorneanu, Bogdan A1 - Arellano-Garcia, Harvey T1 - Improving catalysts and operating conditions using machine learning in Fischer-Tropsch synthesis of jet fuels (C8-C16) T2 - Chemical Engineering Journal Advances N2 - Fischer-Tropsch synthesis (FTS) offers a promising route for producing sustainable jet fuels from syngas. However, optimizing catalyst design and operating conditions for the ideal C8-C16 jet fuel range is challenging. Thus, this work introduces a machine learning (ML) framework to enhance Co/Fe-supported FTS catalysts and optimize their operating conditions for a better jet fuel selectivity. For this purpose, a dataset was implemented with 21 features, including catalyst structure, preparation method, activation procedure, and FTS operating parameters. Moreover, various machine-learning models (Random Forest (RF), Gradient Boosted, CatBoost, and artificial neural networks (ANN)) were evaluated to predict CO conversion and C8-C16 selectivity. Among these, the CatBoost model achieved the highest accuracy (R2 = 0.99). Feature analysis revealed that FTS operational conditions mainly affect CO conversion (37.9 %), while catalyst properties were primarily crucial for C8-C16 selectivity (40.6 %). The proposed ML framework provides a first powerful tool for the rational design of FTS catalysts and operating conditions to maximize jet fuel productivity. KW - Jet fuels (C8-C16) KW - Machine learning (ML) KW - Fischer-Tropsch synthesis (FTS) KW - Operational conditions KW - Catalyst preparation Y1 - 2025 U6 - https://doi.org/10.1016/j.ceja.2024.100702 VL - 21 (2025) PB - Elsevier ER -