Machine learning-driven optimization of plasma-catalytic dry reforming of methane

This study investigates the dry reformation of methane(DRM)over Ni/Al_(2)O_(3)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),CO_(2)/CH_(4)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 plasma-catalytic 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.

Plasma-based CO_(2) conversion:How to correctly analyze the performance?

Plasma-based CO_(2)conversion is promising for carbon capture and utilization.However,inconsistent reporting of the performance metrics makes it difficult to compare plasma processes systematically,complicates elucidating the underlying mechanisms and compromises further development of this technology.Therefore,this critical review summarizes the correct definitions for gas conversion in plasma reactors and highlights common errors and inconsistencies observed throughout literature.This is done for pure CO_(2)splitting,dry reforming of methane and CO_(2)hydrogenation.We demonstrate that the change in volumetric flow rate is a critical aspect,inherent to these reactions,that is often not correctly taken into account.For dry reforming of methane and CO_(2)hydrogenation,we also demonstrate inconsistent reporting of energy efficiency,and through numerical examples,we show the significance of these deviations.Furthermore,we discuss how to measure changes in volumetric flow rate,supported by data from two experimental examples,showing that the sensitivity inherent to a standard component and a flow meter is essential to consider when deriving the performance metrics.Finally,some general recommendations and good practices are provided.This paper aims to be a comprehensive guideline for authors,to encourage more consistent calculations and stimulate the further development of this technology.

Meta-analysis of CO_(2) conversion,energy efficiency,and other performance data of plasma-catalysis reactors with the open access PIONEER database

This paper brings the comparison of performances of CO_(2)conversion by plasma and plasma-assisted catalysis based on the data collected from literature in this field,organised in an open access online database.This tool is open to all users to carry out their own analyses,but also to contributors who wish to add their data to the database in order to improve the relevance of the comparisons made,and ultimately to improve the efficiency of CO_(2)conversion by plasma-catalysis.The creation of this database and database user interface is motivated by the fact that plasma-catalysis is a fast-growing field for all CO_(2)conversion processes,be it methanation,dry reforming of methane,methanolisation,or others.As a result of this rapid increase,there is a need for a set of standard procedures to rigorously compare performances of different systems.However,this is currently not possible because the fundamental mechanisms of plasma-catalysis are still too poorly understood to define these standard procedures.Fortunately however,the accumulated data within the CO_(2)plasma-catalysis community has become large enough to warrant so-called“big data”studies more familiar in the fields of medicine and the social sciences.To enable comparisons between multiple data sets and make future research more effective,this work proposes the first database on CO_(2)conversion performances by plasma-catalysis open to the whole community.This database has been initiated in the framework of a H_(2)0_(2)0 European project and is called the“PIONEER Data Base”.The database gathers a large amount of CO_(2)conversion performance data such as conversion rate,energy efficiency,and selectivity for numerous plasma sources coupled with or without a catalyst.Each data set is associated with metadata describing the gas mixture,the plasma source,the nature of the catalyst,and the form of coupling with the plasma.Beyond the database itself,a data extraction tool with direct visualisation features or advanced filtering functionalities has been developed and is available online to the public.The simple and fast visualisation of the state of the art puts new results into context,identifies literal gaps in data,and consequently points towards promising research routes.More advanced data extraction illustrates the impact that the database can have in the understanding of plasma-catalyst coupling.Lessons learned from the review of a large amount of literature during the setup of the database lead to best practice advice to increase comparability between future CO_(2)plasma-catalytic studies.Finally,the community is strongly encouraged to contribute to the database not only to increase the visibility of their data but also the relevance of the comparisons allowed by this tool.

Is a catalyst always beneficial in plasma catalysis? Insights from the many physical and chemical interactions

Plasma-catalytic dry reforming of CH_(4)(DRM) is promising to convert the greenhouse gasses CH_(4) and CO_(2) 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, high-lighting 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.

Plasma for cancer treatment: How can RONS penetrate through the cell membrane? Answers from computer modeling

Plasma is gaining increasing interest for cancer treatment, but the underlying mechanisms are not yet fully understood. Using computer simulations at the molecular level, we try to gain better insight in how plasma-generated reactive oxygen and nitrogen species (RONS) can penetrate through the cell membrane. Specifically, we compare the permeability of various (hydrophilic and hydrophobic) RONS across both oxidized and nonoxidized cell membranes. We also study pore formation, and how it is hampered by higher concentrations of cholesterol in the cell membrane, and we illustrate the much higher permeability of H2O2 through aquaporin channels. Both mechanisms may explain the selective cytotoxic effect of plasma towards cancer cells. Finally, we also discuss the synergistic effect of plasma-induced oxidation and electric fields towards pore formation.

SF_(6)catalytic degradation in aγ-Al_(2)O_(3)packed bed plasma system:A combined experimental and theoretical study

Effective abatement of the greenhouse gas sulphur hexafluoride(SF_(6))waste is of great importance for the environment protection.This work investigates the size effect and the surface properties ofγ-Al_(2)O_(3)pellets on SF_(6)degradation in a packed bed dielectric barrier discharge(PB-DBD)system.Experimental results show that decreasing the packing size improves the filamentary discharges and promotes the ignition and the maintenance of plasma,enhancing the degradation performance at low input powers.However,too small packing pellets decrease the gas residence time and reduce the degradation efficiency,especially for the input power beyond 80 W.Besides,lowering the packing size promotes the generation of SO2,while reduces the yields of S-O-F products,corresponding to a better degradation.After the discharge,the pellet surface becomes smoother with the appearance of S and F elements.Density functional theory calculations show that SF_(6)is likely to be adsorbed at the AlIII site over theγ-Al_(2)O_(3)(110)surface,and it is much more easily to decompose than in the gas phase.The fluorine gaseous products can decompose and stably adsorb on the pellet surface to change the surface element composition.This work provides a better understanding of SF_(6)degradation in a PB-DBD system.