The kinetics of coke solution loss reaction with and without sodium carbonate were investigated under the reaction atmosphere of carb on dioxide. The variables of gas flow rate and coke particle size were explored to ...The kinetics of coke solution loss reaction with and without sodium carbonate were investigated under the reaction atmosphere of carb on dioxide. The variables of gas flow rate and coke particle size were explored to eliminate the external and inteirial diffusion, respectively. Then, the improved method combining with the least square and the genetic algorithm was proposed to solve the homogeneous model and the shrinking core model. It was found that the improved genetic algorithm method has good stability by studying the fitness function at each generation. In the homogeneous model, the activation energy with and without sodium carbonate was 54.89 and 95.56 kJ/mol, respectively. And. the activation energy with and without sodium carbonate in the shrinking core model was 49.83 and 92.18 kJ/mol, respectively. Therefore, it was concluded that the sodium carbonate has the catalytic action. In addition, results showed that the estimated conversions were agreed well with the experimental ones, which indicated that the calculated kinetic parameters were valid and the proposed method was successfully developed.展开更多
With the projected global surge in hydrogen demand, driven by increasing applications and the imperative for low-emission hydrogen, the integration of machine learning(ML) across the hydrogen energy value chain is a c...With the projected global surge in hydrogen demand, driven by increasing applications and the imperative for low-emission hydrogen, the integration of machine learning(ML) across the hydrogen energy value chain is a compelling avenue. This review uniquely focuses on harnessing the synergy between ML and computational modeling(CM) or optimization tools, as well as integrating multiple ML techniques with CM, for the synthesis of diverse hydrogen evolution reaction(HER) catalysts and various hydrogen production processes(HPPs). Furthermore, this review addresses a notable gap in the literature by offering insights, analyzing challenges, and identifying research prospects and opportunities for sustainable hydrogen production. While the literature reflects a promising landscape for ML applications in hydrogen energy domains, transitioning AI-based algorithms from controlled environments to real-world applications poses significant challenges. Hence, this comprehensive review delves into the technical,practical, and ethical considerations associated with the application of ML in HER catalyst development and HPP optimization. Overall, this review provides guidance for unlocking the transformative potential of ML in enhancing prediction efficiency and sustainability in the hydrogen production sector.展开更多
Heterogeneous catalysis is of tremendous importance to modern industries. Exposed atoms of heterogeneous catalysts are heavily involved in surface processes such as the adsorption, activation, diffusion and reaction o...Heterogeneous catalysis is of tremendous importance to modern industries. Exposed atoms of heterogeneous catalysts are heavily involved in surface processes such as the adsorption, activation, diffusion and reaction of substrate molecules. Surfaces of metal or metal oxide based catalysts are usually taken as hard templates that only undergo limited relaxation during catalytic reactions, especially in theoretical simulations. In this work, by using genetic algorithm (GA) aided density functional theory (DFT) calculations, we studied the surface processes involved in CO oxidation on the Au(100) surface. The use of GA greatly improves the capacity of DFT calculations in locating the potential energy surface (PES) of the surface reactions, and surprisingly, it has been found that the Au(100) surface can undergo drastic reconstruction under the influence of O adsorption and the adapted partially oxidized Au surface exhibits unique activities for subsequent adsorptions and reactions. This work depicts the kinetic nature of the Au (100) surface in its catalyzed reactions and also significantly expands our understanding of how surface atoms act in heterogeneous catalysis.展开更多
基金the National Natural Science Foundation of China(21476001)Key Project of Anhui Provincial Department of Education(KJ2017A045)are gratefully acknowledgedOpen Fund of Shaanxi Key Laboratory of Energy Chemical Process Intensification(No.SXECPI201601).
文摘The kinetics of coke solution loss reaction with and without sodium carbonate were investigated under the reaction atmosphere of carb on dioxide. The variables of gas flow rate and coke particle size were explored to eliminate the external and inteirial diffusion, respectively. Then, the improved method combining with the least square and the genetic algorithm was proposed to solve the homogeneous model and the shrinking core model. It was found that the improved genetic algorithm method has good stability by studying the fitness function at each generation. In the homogeneous model, the activation energy with and without sodium carbonate was 54.89 and 95.56 kJ/mol, respectively. And. the activation energy with and without sodium carbonate in the shrinking core model was 49.83 and 92.18 kJ/mol, respectively. Therefore, it was concluded that the sodium carbonate has the catalytic action. In addition, results showed that the estimated conversions were agreed well with the experimental ones, which indicated that the calculated kinetic parameters were valid and the proposed method was successfully developed.
基金express their gratitude to the Higher Institution Centre of Excellence (HICoE) fund under the project code (JPT.S(BPKI)2000/016/018/015JId.4(21)/2022002HICOE)Universiti Tenaga Nasional (UNITEN) for funding the research through the (J510050002–IC–6 BOLDREFRESH2025)Akaun Amanah Industri Bekalan Elektrik (AAIBE) Chair of Renewable Energy grant,and NEC Energy Transition Grant (202203003ETG)。
文摘With the projected global surge in hydrogen demand, driven by increasing applications and the imperative for low-emission hydrogen, the integration of machine learning(ML) across the hydrogen energy value chain is a compelling avenue. This review uniquely focuses on harnessing the synergy between ML and computational modeling(CM) or optimization tools, as well as integrating multiple ML techniques with CM, for the synthesis of diverse hydrogen evolution reaction(HER) catalysts and various hydrogen production processes(HPPs). Furthermore, this review addresses a notable gap in the literature by offering insights, analyzing challenges, and identifying research prospects and opportunities for sustainable hydrogen production. While the literature reflects a promising landscape for ML applications in hydrogen energy domains, transitioning AI-based algorithms from controlled environments to real-world applications poses significant challenges. Hence, this comprehensive review delves into the technical,practical, and ethical considerations associated with the application of ML in HER catalyst development and HPP optimization. Overall, this review provides guidance for unlocking the transformative potential of ML in enhancing prediction efficiency and sustainability in the hydrogen production sector.
基金supported by National Key R&D Program of China(No. 2018YFA0208602)National Natural Science Foundation of China(Nos. 21421004, 21825301, 21573067, 91545103)Program of Shanghai Academic Research Leader (No. 17XD1401400)
文摘Heterogeneous catalysis is of tremendous importance to modern industries. Exposed atoms of heterogeneous catalysts are heavily involved in surface processes such as the adsorption, activation, diffusion and reaction of substrate molecules. Surfaces of metal or metal oxide based catalysts are usually taken as hard templates that only undergo limited relaxation during catalytic reactions, especially in theoretical simulations. In this work, by using genetic algorithm (GA) aided density functional theory (DFT) calculations, we studied the surface processes involved in CO oxidation on the Au(100) surface. The use of GA greatly improves the capacity of DFT calculations in locating the potential energy surface (PES) of the surface reactions, and surprisingly, it has been found that the Au(100) surface can undergo drastic reconstruction under the influence of O adsorption and the adapted partially oxidized Au surface exhibits unique activities for subsequent adsorptions and reactions. This work depicts the kinetic nature of the Au (100) surface in its catalyzed reactions and also significantly expands our understanding of how surface atoms act in heterogeneous catalysis.
