OpenMKM: An Open-Source C++ Multiscale Modeling Simulator for Homogeneous and Heterogeneous Catalytic Reactions

计算机科学 计算科学 工作流程 Python(编程语言) 软件 MATLAB语言 常微分方程 微分方程 物理 程序设计语言 数据库 量子力学
作者
Bharat Medasani,Sashank Kasiraju,Dionisios G. Vlachos
出处
期刊:Journal of Chemical Information and Modeling [American Chemical Society]
卷期号:63 (11): 3377-3391 被引量:10
标识
DOI:10.1021/acs.jcim.3c00088
摘要

Microkinetic modeling is invaluable for coupling "microscale" atomistic data with "macroscale" reactor observables. We introduce an Open-source Microkinetic Modeling (OpenMKM) multiscale mean-field microkinetics modeling toolkit targeting mainly heterogeneous catalytic reactions but applies equally to homogeneous reactions. OpenMKM is a modular, object-oriented, C++ software, built on top of the robust open-source Cantera built mainly for homogeneous reactions. Reaction mechanisms can be input from human-readable files or automatic reaction generators, avoiding tedious work and errors. The governing equations are also built automatically, unlike Matlab and Python manual implementations, providing speed and error-free models. OpenMKM has built-in interfaces with numerical software, SUNDIALS, for solving ordinary differential equations and differential-algebraic equations. Users can choose various ideal reactors and energy balance options, such as isothermal, adiabatic, temperature ramp, and an experimentally measured temperature profile. OpenMKM is tightly integrated with pMuTT for thermochemistry input file generation from density functional theory (DFT), streamlining the workflow from DFT to MKM and eliminating tedious work and human errors. It is also seamlessly integrated with the RenView software for visualizing the reaction pathways and performing the reaction path or flux analysis (RPA). OpenMKM includes local sensitivity analysis (LSA) by solving the augmented system of equations or using the one-at-a-time finite difference (first or second order) method. LSA can identify not only kinetically influential reactions but also species. The software provides two techniques for large reaction mechanisms for which LSA is too expensive to run. One is the Fischer Information Matrix, which is approximate but comes at nearly zero cost. The other is a new method that we term RPA-guided LSA, which is a finite difference-based method but uses RPA to select kinetically relevant reactions instead of exploiting the entire reaction network. Users can quickly set up and conduct microkinetic simulations without writing code. The user inputs are conveniently divided into reactor setup files and thermodynamic and kinetic definition files to set up different reactors. The source code and documentation are openly available at https://github.com/VlachosGroup/openmkm.
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