Vijay Sudarshan, H Heenen Hendrik, Singh Aayush R, Chan Karen, Voss Johannes
CatTheory, Department of Physics, Technical University of Denmark, Kgs. Lyngby, Denmark.
Fritz-Haber-Institut der Max-Planck-Gesellschaft, Berlin, Germany.
J Comput Chem. 2024 Apr 5;45(9):546-551. doi: 10.1002/jcc.27263. Epub 2023 Nov 27.
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.
通过从头算计算参数化的动力学模型,在理解多相催化中的化学反应方面取得了显著进展。这些研究得益于确定稳态覆盖率和平均场微动力学模型速率的实现方法。在开源动力学建模程序CatMAP中实现时,传统的求解策略是使用根查找算法,通过稳态表达式确定所有中间体的覆盖率,将所有覆盖率约束为非负且总和恰为1。尽管直观,但由于这些强加的约束,这种根查找策略在收敛到解时会产生问题。在这项工作中,我们避免明确施加这些约束,在位点数量空间中求解平均场稳态微动力学模型,而不是在覆盖率空间中求解。我们将受约束的根查找问题转化为无约束的最小二乘最小化问题,从而在求解微动力学模型时显著提高了收敛性,进而能够高效地研究更复杂的催化反应。