XPK: Toward Accurate and Efficient Microkinetic Modeling in Heterogeneous Catalysis

被引:10
作者
Chen, Zheng [1 ]
Liu, Zhangyun [1 ]
Xu, Xin [1 ,2 ]
机构
[1] Fudan Univ, Collaborat Innovat Ctr Chem Energy Mat, Dept Chem, Key Lab Mol Catalysis & Innovat Mat,MOE Key Lab Co, Shanghai 200433, Peoples R China
[2] Hefei Natl Lab, Hefei 230088, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
microkinetics; kinetic Monte Carlo; extendedphenomenological kinetics; lateral interactions; time scale separation; free energy landscape; AMMONIA-SYNTHESIS; SCIENCE; SURFACE; METHANATION; SELECTIVITY; ADSORPTION; SIMULATION; COMPLEXITY; REDUCTION; EQUATION;
D O I
10.1021/acscatal.3c04298
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
The traditional trial-and-error approach can no longer meet the surging demand for developing catalysts to address the grand challenges of energy and environment, while rational catalyst design, especially first-principles based rational catalyst design, has evolved from concept to reality and is playing an increasingly important role. To this end, microkinetic modeling is needed to effectively correlate microscopic properties from first-principles calculations to the catalyst's macroscopic performance, identify the rate-controlling steps, and guide the rational catalyst design. However, the accuracy and efficiency of current microkinetic modeling methods need to be improved so as to accurately describe the inherent nonuniformity in catalyst surfaces as well as the spatial correlations of surface species caused by lateral interactions. Recently, we have developed a microkinetic method, namely XPK, which extended the phenomenological kinetics approach to capture critical spatial correlations and multiple time scales among surface diffusion, fast reaction equilibriums, and slow reaction steps, reaching a good balance between accuracy and efficiency in simulating complexed heterogeneous catalytic processes under in situ/operando conditions. On top of the XPK results, we have proposed a formulation of free energy landscape (FEL), which provides a powerful way to understand how local surface coverages can affect the values of the macroscopic measurables. It is anticipated that the continuous development of theoretical methods and the synergy between experiment and theory will enable increasingly quantitative and predictive computational modeling of catalysis in the future.
引用
收藏
页码:15219 / 15229
页数:11
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