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	Author	Cai, Y.; Mei, D.; Chen, Y.; Bogaerts, A.; Tu, X.
	Title	Machine learning-driven optimization of plasma-catalytic dry reforming of methane			Type	A1 Journal Article
	Year	2024	Publication	Journal of Energy Chemistry	Abbreviated Journal	Journal of Energy Chemistry
	Volume	96	Issue		Pages	153-163
	Keywords	A1 Journal Article; Plasma catalysis Machine learning Process optimization Dry reforming of methane Syngas production; Plasma, laser ablation and surface modeling Antwerp (PLASMANT) ;
	Abstract	This study investigates the dry reformation of methane (DRM) over Ni/Al2O3 catalysts in a dielectric barrier discharge (DBD) non-thermal plasma reactor. A novel hybrid machine learning (ML) model is developed to optimize the plasma-catalytic DRM reaction with limited experimental data. To address the non-linear and complex nature of the plasma-catalytic DRM process, the hybrid ML model integrates three well-established algorithms: regression trees, support vector regression, and artificial neural networks. A genetic algorithm (GA) is then used to optimize the hyperparameters of each algorithm within the hybrid ML model. The ML model achieved excellent agreement with the experimental data, demonstrating its efficacy in accurately predicting and optimizing the DRM process. The model was subsequently used to investigate the impact of various operating parameters on the plasma-catalytic DRM performance. We found that the optimal discharge power (20 W), CO2/CH4 molar ratio (1.5), and Ni loading (7.8 wt%) resulted in the maximum energy yield at a total flow rate of 51 mL/min. Furthermore, we investigated the relative significance of each operating parameter on the performance of the plasmacatalytic DRM process. The results show that the total flow rate had the greatest influence on the conversion, with a significance exceeding 35% for each output, while the Ni loading had the least impact on the overall reaction performance. This hybrid model demonstrates a remarkable ability to extract valuable insights from limited datasets, enabling the development and optimization of more efficient and selective plasma-catalytic chemical processes.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Wos		Publication Date	2024-04-25
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2095-4956	ISBN		Additional Links
	Impact Factor	13.1	Times cited		Open Access
	Notes	This project received funding from the European Union’s Hori- zon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 813393.			Approved	Most recent IF: 13.1; 2024 IF: 2.594
	Call Number	PLASMANT @ plasmant @			Serial	9124
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	Author	Wanten, B.; Vertongen, R.; De Meyer, R.; Bogaerts, A.
	Title	Plasma-based CO2 conversion: How to correctly analyze the performance?			Type	A1 journal article
	Year	2023	Publication	Journal of Energy Chemistry	Abbreviated Journal	Journal of Energy Chemistry
	Volume	86	Issue		Pages	180-196
	Keywords	A1 journal article; Plasma, laser ablation and surface modeling Antwerp (PLASMANT) ;
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Wos	001070885000001	Publication Date	2023-07-22
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2095-4956	ISBN		Additional Links	UA library record; WoS full record; WoS citing articles
	Impact Factor	13.1	Times cited		Open Access	Not_Open_Access
	Notes	We acknowledge financial support from the Fund for Scientific Research (FWO) Flanders (Grant ID 110221N), the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation Program (grant agreement No 810182 – SCOPE ERC Synergy project), and the Methusalem funding of the University of Antwerp. We acknowledge the icons from the graphical abstract made by dDara, geotatah, Spashicons and Freepik on www.flaticon.com. We also thank Stein Maerivoet, Joachim Slaets, Elizabeth Mercer, Colín Ó’Modráin, Joran Van Turnhout, Pepijn Heirman, dr. Yury Gorbanev, dr. Fanny Girard-Sahun and dr. Sean Kelly for the interesting discussions and feedback.			Approved	Most recent IF: 13.1; 2023 IF: 2.594
	Call Number	PLASMANT @ plasmant @c:irua:198709			Serial	8816
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	Author	Loenders, B.; Michiels, R.; Bogaerts, A.
	Title	Is a catalyst always beneficial in plasma catalysis? Insights from the many physical and chemical interactions			Type	A1 Journal Article
	Year	2023	Publication	Journal of Energy Chemistry	Abbreviated Journal	Journal of Energy Chemistry
	Volume	85	Issue		Pages	501-533
	Keywords	A1 Journal Article; Plasma, laser ablation and surface modeling Antwerp (PLASMANT) ;
	Abstract	Plasma-catalytic dry reforming of CH4 (DRM) is promising to convert the greenhouse gasses CH4 and CO2 into value-added chemicals, thus simultaneously providing an alternative to fossil resources as feedstock for the chemical industry. However, while many experiments have been dedicated to plasma-catalytic DRM, there is no consensus yet in literature on the optimal choice of catalyst for targeted products, because the underlying mechanisms are far from understood. Indeed, plasma catalysis is very complex, as it encompasses various chemical and physical interactions between plasma and catalyst, which depend on many parameters. This complexity hampers the comparison of experimental results from different studies, which, in our opinion, is an important bottleneck in the further development of this promising research field. Hence, in this perspective paper, we describe the important physical and chemical effects that should be accounted for when designing plasma-catalytic experiments in general, highlighting the need for standardized experimental setups, as well as careful documentation of packing properties and reaction conditions, to further advance this research field. On the other hand, many parameters also create many windows of opportunity for further optimizing plasma-catalytic systems. Finally, various experiments also reveal the lack of improvement in plasma catalysis compared to plasma-only, specifically for DRM, but the underlying mechanisms are unclear. Therefore, we present our newly developed coupled plasma-surface kinetics model for DRM, to provide more insight in the underlying reasons. Our model illustrates that transition metal catalysts can adversely affect plasmacatalytic DRM, if radicals dominate the plasma-catalyst interactions. Thus, we demonstrate that a good understanding of the plasma-catalyst interactions is crucial to avoiding conditions at which these interactions negatively affect the results, and we provide some recommendations for improvement. For instance, we believe that plasma-catalytic DRM may benefit more from higher reaction temperatures, at which vibrational excitation can enhance the surface reactions.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Wos		Publication Date	2023-06-30
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2095-4956	ISBN		Additional Links	UA library record
	Impact Factor	13.1	Times cited		Open Access	Not_Open_Access
	Notes	This research was supported by the FWO-SBO project PlasMa- CatDESIGN (FWO grant ID S001619N), the FWO fellowship of R. Michiels (FWO grant ID 1114921N), and the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 810182 – SCOPE ERC Synergy project). The computational resources and services used in this work were provided by the HPC core facility CalcUA of the Universiteit Antwerpen, and VSC (Flemish Supercomputer Center), funded by the Research Foundation – Flanders (FWO) and the Flemish Government.			Approved	Most recent IF: 13.1; 2023 IF: 2.594
	Call Number	PLASMANT @ plasmant @c:irua:198159			Serial	8806
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