“Machine learning-driven optimization of plasma-catalytic dry reforming of methane”. Cai Y, Mei D, Chen Y, Bogaerts A, Tu X, Journal of Energy Chemistry 96, 153 (2024). http://doi.org/10.1016/j.jechem.2024.04.022
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.
Keywords: A1 Journal Article; Plasma catalysis Machine learning Process optimization Dry reforming of methane Syngas production; Plasma, laser ablation and surface modeling Antwerp (PLASMANT) ;
Impact Factor: 13.1
DOI: 10.1016/j.jechem.2024.04.022
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“CO₂, conversion to CO via plasma and electrolysis : a techno-economic and energy cost analysis”. Osorio-Tejada J, Escriba-Gelonch M, Vertongen R, Bogaerts A, Hessel V, Energy &, environmental science (2024). http://doi.org/10.1039/D4EE00164H
Abstract: Electrification and carbon capture technologies are essential for achieving net-zero emissions in the chemical sector. A crucial strategy involves converting captured CO2 into CO, a valuable chemical feedstock. This study evaluates the feasibility of two innovative methods: plasma activation and electrolysis, using clean electricity and captured CO2. Specifically, it compares a gliding arc plasma reactor with an embedded novel carbon bed system to a modern zero-gap type low-temperature electrolyser. The plasma method stood out with an energy cost of 19.5 GJ per tonne CO, marking a 43% reduction compared to electrolysis and conventional methods. CO production costs for plasma- and electrolysis-based plants were $671 and $962 per tonne, respectively. However, due to high uncertainty regarding electrolyser costs, the CO production costs in electrolysis-based plants may actually range from $570 to $1392 per tonne. The carbon bed system in the plasma method was a key factor in facilitating additional CO generation from O-2 and enhancing CO2 conversion, contributing to its cost-effectiveness. Challenges for electrolysis included high costs of equipment and low current densities. Addressing these limitations could significantly decrease production costs, but challenges arise from the mutual relationship between intrinsic parameters, such as CO2 conversion, CO2 input flow, or energy cost. In a future scenario with affordable feedstocks and equipment, costs could drop below $500 per tonne for both methods. While this may be more challenging for electrolysis due to complexity and expensive catalysts, plasma-based CO production appears more viable and competitive.
Keywords: A1 Journal article; Engineering sciences. Technology; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
Impact Factor: 32.5
DOI: 10.1039/D4EE00164H
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“Plasma chemical looping : unlocking high-efficiency CO₂, conversion to clean CO at mild temperatures”. Long Y, Wang X, Zhang H, Wang K, Ong W-L, Bogaerts A, Li K, Lu C, Li X, Yan J, Tu X, Zhang H, JACS Au (2024). http://doi.org/10.1021/JACSAU.4C00153
Abstract: We propose a plasma chemical looping CO2 splitting (PCLCS) approach that enables highly efficient CO2 conversion into O-2-free CO at mild temperatures. PCLCS achieves an impressive 84% CO2 conversion and a 1.3 mmol g(-1) CO yield, with no O-2 detected. Crucially, this strategy significantly lowers the temperature required for conventional chemical looping processes from 650 to 1000 degrees C to only 320 degrees C, demonstrating a robust synergy between plasma and the Ce0.7Zr0.3O2 oxygen carrier (OC). Systematic experiments and density functional theory (DFT) calculations unveil the pivotal role of plasma in activating and partially decomposing CO2, yielding a mixture of CO, O-2/O, and electronically/vibrationally excited CO2*. Notably, these excited CO2* species then efficiently decompose over the oxygen vacancies of the OCs, with a substantially reduced activation barrier (0.86 eV) compared to ground-state CO2 (1.63 eV), contributing to the synergy. This work offers a promising and energy-efficient pathway for producing O-2-free CO from inert CO2 through the tailored interplay of plasma and OCs.
Keywords: A1 Journal article; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
DOI: 10.1021/JACSAU.4C00153
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“Coupled multi-dimensional modelling of warm plasmas: Application and validation for an atmospheric pressure glow discharge in CO2/CH4/O2”. Maerivoet S, Tsonev I, Slaets J, Reniers F, Bogaerts A, Chemical Engineering Journal 492, 152006 (2024). http://doi.org/10.1016/j.cej.2024.152006
Abstract: To support experimental research into gas conversion by warm plasmas, models should be developed to explain the experimental observations. These models need to describe all physical and chemical plasma properties in a coupled way. In this paper, we present a modelling approach to solve the complete set of assumed relevant equations, including gas flow, heat balance and species transport, coupled with a rather extensive chemistry set, consisting of 21 species, obtained by reduction of a more detailed chemistry set, consisting of 41 species. We apply this model to study the combined CO2 and CH4 conversion in the presence of O2, in a direct current atmospheric pressure glow discharge. Our model can predict the experimental trends, and can explain why higher O2 fractions result in higher CH4 conversion, namely due to the higher gas temperature, rather than just by additional chemical reactions. Indeed, our model predicts that when more O2 is added, the energy required to reach any set temperature (i.e., the enthalpy) drops, allowing the system to reach higher temperatures with similar amounts of energy. This is in turn related to the higher H2O fraction and lower H2 fraction formed in the plasma, as demonstrated by our model. Altogether, our new self-consistent model can capture the main physics and chemistry occurring in this warm plasma, which is an important step towards predictive modelling for plasma-based gas conversion.
Keywords: A1 Journal Article; Plasma, laser ablation and surface modeling Antwerp (PLASMANT) ;
Impact Factor: 15.1
DOI: 10.1016/j.cej.2024.152006
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“Improving the performance of gliding arc plasma-catalytic dry reforming via a new post-plasma tubular catalyst bed”. Xu W, Buelens LC, Galvita VV, Bogaerts A, Meynen V, Journal of CO2 Utilization 83, 102820 (2024). http://doi.org/10.1016/j.jcou.2024.102820
Abstract: A combination of a gliding arc plasmatron (GAP) reactor and a newly designed tubular catalyst bed (N-bed) was applied to investigate the post-plasma catalytic (PPC) effect for dry reforming of methane (DRM). As comparison, a traditional plasma catalyst bed (T-bed) was also utilized. The post-plasma catalytic effect of a Ni-based mixed oxide (Ni/MO) catalyst with a thermal catalytic performance of 77% CO2 and 86% CH4 conversion at 700 ℃ was studied. Although applying the T-bed had little effect on plasma based CO2 and CH4 conversion, an increase in selectivity to H2 was obtained with a maximum value of 89% at a distance of 2 cm. However, even when only α-Al2O3 packing material was used in the N-bed configuration, compared to the plasma alone and the T-bed, an increase of the CO2 and CH4 conversion from 53% and 53% to 69% and 69% to 83% was achieved. Addition of the Ni/MO catalyst further enhanced the DRM reaction, resulting in conversions of 79% for CO2 and 91% for
CH4. Hence, although no insulation nor external heating was applied to the N-bed post plasma, it provides a slightly better conversion than the thermal catalytic performance with the same catalyst, while being fully electrically driven. In addition, an enhanced CO selectivity to 96% was obtained and the energy cost was reduced from ~ 6 kJ/L (plasma alone) to 4.3 kJ/L. To our knowledge, it is the first time that a post-plasma catalytic system achieves this excellent catalytic performance for DRM without extra external heating or insulation.
Keywords: A1 Journal Article; Dry reforming Gliding arc plasma Plasma catalytic DRM Ni-based mixed oxide Post-plasma catalysis; Plasma, laser ablation and surface modeling Antwerp (PLASMANT) ;
Impact Factor: 7.7
DOI: 10.1016/j.jcou.2024.102820
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“Improving Molecule–Metal Surface Reaction Networks Using the Meta-Generalized Gradient Approximation: CO2Hydrogenation”. Cai Y, Michiels R, De Luca F, Neyts E, Tu X, Bogaerts A, Gerrits N, The Journal of Physical Chemistry C 128, 8611 (2024). http://doi.org/10.1021/acs.jpcc.4c01110
Abstract: Density functional theory is widely used to gain insights into molecule−metal surface reaction networks, which is important for a better understanding of catalysis. However, it is well-known that generalized gradient approximation (GGA)
density functionals (DFs), most often used for the study of reaction networks, struggle to correctly describe both gas-phase molecules and metal surfaces. Also, GGA DFs typically underestimate reaction barriers due to an underestimation of the selfinteraction energy. Screened hybrid GGA DFs have been shown to reduce this problem but are currently intractable for wide usage. In this work, we use a more affordable meta-GGA (mGGA) DF in combination with a nonlocal correlation DF for the first time to study and gain new insights into a catalytically important surface
reaction network, namely, CO2 hydrogenation on Cu. We show that the mGGA DF used, namely, rMS-RPBEl-rVV10, outperforms typical GGA DFs by providing similar or better predictions for metals and molecules, as well as molecule−metal surface adsorption
and activation energies. Hence, it is a better choice for constructing molecule−metal surface reaction networks.
Keywords: A1 Journal Article; Plasma, laser ablation and surface modeling Antwerp (PLASMANT) ;
Impact Factor: 3.7
DOI: 10.1021/acs.jpcc.4c01110
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Ahmadi Eshtehardi H (2024) Combined computational-experimental study on plasma and plasma catalysis for N2 fixation. 160 p
Abstract: Humanity feels the urge of shifting to a sustainable society more than at any other time in its history. Electrification of chemical industry plays a key role in this transition. The possibility of producing fertilizers from air using renewable electricity, and simultaneously, no greenhouse gas emission, resulted in an increasing interest toward plasma technology as a solution for electrification of a part of the chemical industry in the past few years. Additionally, the activation of nitrogen molecules by vibrational and electronic excitation reactions in plasma can lead to an energy-efficient process. Last but not least, the modularity (fast on/off characteristic) of plasma technology makes it capable of using intermittent renewable electricity on site for the production of fertilizers using air. All these advantages offered by plasma technology make it a potential solution for the on-site production of fertilizers in small and decentralized plants using air and renewable electricity, which leads to a considerable reduction in fertilizer production and transportation costs. However, industrialization of plasma-based NF suffers from several challenges, including challenges of plasma catalysis for the selective production of desired species, the high energy cost of plasma-based NF compared to current industrial processes, and the design and development of scaled up and energy-efficient plasma reactors for industrial purposes. In the framework of this thesis we have tried to add to the state-of-the-art (SOTA) in plasma-based NOx production and deal with its limitations using a combination of experimental and modelling work.
Keywords: Doctoral thesis; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
DOI: 10.63028/10067/2052460151162165141
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