@misc{MedinaMendezDorneanuArellanoGarcia, author = {Medina M{\´e}ndez, Juan Ali and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {Homogeneous modeling for laminar flows in structured catalysts: CO2 methanation}, address = {Bochum}, pages = {1}, language = {en} } @misc{DorneanuHeinzelmannSchnitzleinetal., author = {Dorneanu, Bogdan and Heinzelmann, Norbert and Schnitzlein, Klaus and Arellano-Garc{\´i}a, Harvey}, title = {BasMo - An interactive approach to modelling of trickle bed reactors}, series = {Jahrestreffen der "Prozess-, Apparate- und Anlagentechnik", 21.-22. November 2022, Frankfurt am Main}, journal = {Jahrestreffen der "Prozess-, Apparate- und Anlagentechnik", 21.-22. November 2022, Frankfurt am Main}, abstract = {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.}, language = {en} } @misc{SafdarShezadDorneanuetal., author = {Safdar, Muddasar and Shezad, Nasir and Dorneanu, Bogdan and Jafari, Mitra and Shashank Bhat, Sharvendu and Akhtar, Farid and Arellano-Garc{\´i}a, Harvey}, title = {Dry Reforming of Methane for the Syngas Production Catalyzed by Ni-doped Perovskites}, series = {15Th European Congress on Katakysis EUROPACAT2023}, journal = {15Th European Congress on Katakysis EUROPACAT2023}, abstract = {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.}, language = {en} } @misc{DorneanuNolascoVassiliadisetal., author = {Dorneanu, Bogdan and Nolasco, Eduardo and Vassiliadis, Vassilios S. and Arellano-Garc{\´i}a, Harvey}, title = {Quantum annealing for global optimization in Chemical Engineering}, series = {Jahrestreffen "Prozess-, Apparate- und Anlagentechnik" - PAAT 2023, Frankfurt am Main}, journal = {Jahrestreffen "Prozess-, Apparate- und Anlagentechnik" - PAAT 2023, Frankfurt am Main}, pages = {15}, abstract = {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.}, language = {en} }