My name is Yuxiang and I am from Guiyang, China. I worked on plasma catalysis for air pollution control and obtained my bachelor and master degree at College of Energy Engineering, Zhejiang University. My postgraduate study not only gave me valuable research experience, general knowledge of non-thermal plasma, and the ability to develop plasma systems, but also matured and deepened my enthusiasm for and curiosity towards energy and environment science, which has also led me to pursue a career researching in the field of plasma catalysis.
Now I am a PhD student under the supervision of Prof. Xin Tu at University of Liverpool and co-supervision of Prof. Annemie Bogaerts at University of Antwerp. My goal is to develop a plasma-catalytic process for CO2 into value-added chemicals at low temperatures and atmospheric pressure, which requires a hybrid of advanced catalyst material and conjugate plasma system. I cannot help feeling excited when it come to my mind that there will be a chance to cope with both energy and environment challenges in one method – PIONEER.
| Overview |  |
| ESR: | 10 |
| Title: | Plasma-catalytic CO2 hydrogenation for the production of molecules for green chemistry |
| Home Institution: | University of Liverpool (UoL) |
| 1st Supervisor: | Xin Tu |
| Host Institution: | University of Antwerp (UAntwerpen) |
| 2nd Supervisor: | Annemie Bogaerts |
| Industrial Partner: | Johnson Matthey |
| Industrial Contact: | Peter Hinde |
| Defence: | February 7 2025 |
Abstract
Controlling carbon dioxide (CO2) emissions and converting CO2 into valuable chemicals remains a significant challenge due to its high stability and the high temperatures required for thermal activation. Plasma technology, with its potent activation capabilities, offers a promising alternative, yet its energy efficiency and mechanistic understanding still require improvement. This thesis combines experimental work and multi-scale simulations to advance plasma-catalytic CO2 conversion: (1) Perovskite catalysts with various B-site elements were synthesized and evaluated for plasma-catalytic reverse water-gas shift (RWGS) reactions. Among these, an Fe-based perovskite catalyst exhibited 22.7% CO2 conversion and 94.3% CO selectivity. Partial B-site substitution further improved performance, with the optimal catalyst, La0.5Sr0.5Fe0.9Cu0.1O3, achieving 25.9% conversion and 94.3% selectivity. Enhanced plasma discharge facilitated CO2 excitation and C=O bond activation. Kinetics simulations and catalyst characterisations revealed that Cu substitution increased surface area, redox capability, and oxygen vacancies, thereby boosting CO2 and H2 adsorption and decomposition. (2) A comparative investigation on catalyst supports was conducted to target value-added chemicals from plasma-catalytic CO2 conversion. The Si/Al ratio in ZSM-5 significantly affected the properties of Cu/ZSM-5 catalysts. A Si/Al ratio of 38 yielded the highest percentage of strong basic sites, enhancing the electron-donating ability and promoting CO2 adsorption on active Cu sites. Combined characterisation and in situ diagnostics elucidated the underlying mechanism. (3) The meta-generalized gradient approximation (mGGA) density functional rMS-RPBEl-rVV10 was evaluated to predict reaction networks for plasma-catalytic CO2 hydrogenation on Cu. This functional accurately described metal properties, thermodynamics, adsorption processes, and dissociation barriers on Cu(111) and Cu(211) surfaces. On Cu(111), formate and CO2 dissociation pathways were equally favorable, whereas on Cu(211), the CO2 dissociation pathway prevailed with lower barriers. The Eley–Rideal mechanism, enhanced by plasma species, significantly reduced energy barriers and provided key intermediates, leading to high CH3OH selectivity at low temperatures and atmospheric pressures. (4) A hybrid machine learning model combining artificial neural networks, support vector regression, and regression trees, with genetic algorithm optimization, was developed to predict plasma-catalytic dry reforming of methane. Trained on 100 data points across four reaction parameters and performance indicators, the model achieved high predictive accuracy and identified significant interactions between discharge power and total flow rate, pinpointing optimal conditions for maximum energy yield and fuel production efficiency. This study provides valuable insights into plasma-catalytic CO2 conversion mechanisms and optimization strategies for efficient chemical utilisation.
Links with other ESR
- ESRs 6-9: Efficiency comparison
Expected Results
- Understand the role of energetic electrons and reactive species in the plasma-catalytic CO2 hydrogenation
- Obtain the cost-effective and optimal catalysts for the production of target chemicals with special focus on chemical nature of active metal and support materials
- Understand the roles of catalysts in the plasma-catalytic CO2 hydrogenation
- Insight into the reaction mechanisms and pathways from catalyst characterisation and plasma diagnostics
Secondments
- UAntwerp: Support by modeling work and understanding the underlying mechanisms
- Johnson Matthey: Production of catalytic materials