解算器
动能
稳态(化学)
趋同(经济学)
参数化复杂度
应用数学
领域(数学)
状态空间
从头算
计算机科学
数学
数学优化
化学
物理
算法
物理化学
经典力学
量子力学
统计
纯数学
经济
经济增长
作者
Sudarshan Vijay,Hendrik H. Heenen,Aayush R. Singh,Karen Chan,Johannes Voss
摘要
Abstract Kinetic models parameterized by ab‐initio calculations have led to significant improvements in understanding chemical reactions in heterogeneous catalysis. These studies have been facilitated by implementations which determine steady‐state coverages and rates of mean‐field micro‐kinetic models. As implemented in the open‐source kinetic modeling program, CatMAP, the conventional solution strategy is to use a root‐finding algorithm to determine the coverage of all intermediates through the steady‐state expressions, constraining all coverages to be non‐negative and to properly sum to unity. Though intuitive, this root‐finding strategy causes issues with convergence to solution due to these imposed constraints. In this work, we avoid explicitly imposing these constraints, solving the mean‐field steady‐state micro‐kinetic model in the space of number of sites instead of solving it in the space of coverages . We transform the constrained root‐finding problem to an unconstrained least‐squares minimization problem, leading to significantly improved convergence in solving micro‐kinetic models and thus enabling the efficient study of more complex catalytic reactions.
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