Smith William R, Qi Weikai
Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario N1G 2W1, Canada.
Department of Chemistry, University of Guelph, Guelph, Ontario N1G 2W1, Canada.
ACS Cent Sci. 2018 Sep 26;4(9):1185-1193. doi: 10.1021/acscentsci.8b00361. Epub 2018 Aug 23.
The molecular simulation of chemical reaction equilibrium (CRE) is a challenging and important problem of broad applicability in chemistry and chemical engineering. The primary molecular-based approach for solving this problem has been the reaction ensemble Monte Carlo (REMC) algorithm [Turner et al. Molec. Simulation2008, 34, (2), 119-146], based on classical force-field methodology. In spite of the vast improvements in computer hardware and software since its original development almost 25 years ago, its more widespread application is impeded by its computational inefficiency. A fundamental problem is that its MC basis inhibits the implementation of significant parallelization, and its successful implementation often requires system-specific tailoring and the incorporation of special MC approaches such as replica exchange, expanded ensemble, umbrella sampling, configurational bias, and continuous fractional component methodologies. We describe herein a novel CRE algorithm (reaction ensemble molecular dynamics, ReMD) that exploits modern computer hardware and software capabilities, and which can be straightforwardly implemented for systems of arbitrary size and complexity by exploiting the parallel computing methodology incorporated within many MD software packages (herein, we use GROMACS for illustrative purposes). The ReMD algorithm utilizes these features in the context of a macroscopically inspired and generally applicable free energy minimization approach based on the iterative approximation of the system Gibbs free energy function by a mathematically simple convex ideal solution model using the composition at each iteration as a reference state. Finally, we additionally describe a simple and computationally efficient method to estimate the equilibrium concentrations of species present in very small amounts relative to others in the primary calculation. To demonstrate the algorithm, we show its application to two classic example systems considered previously in the literature: the N-O-NO system and the ammonia synthesis system.
化学反应平衡(CRE)的分子模拟是化学和化学工程领域中一个具有挑战性且重要的问题,具有广泛的适用性。解决这个问题的主要基于分子的方法是反应系综蒙特卡罗(REMC)算法[特纳等人,《分子模拟》,2008年,34卷,(2)期,119 - 146页],该算法基于经典力场方法。尽管自近25年前首次开发以来,计算机硬件和软件有了巨大改进,但其计算效率低下阻碍了它更广泛的应用。一个根本问题是其蒙特卡罗基础抑制了显著并行化的实现,并且其成功实现通常需要针对特定系统进行定制,并纳入特殊的蒙特卡罗方法,如副本交换、扩展系综、伞形采样、构型偏倚和连续分数组分方法。我们在此描述一种新颖的CRE算法(反应系综分子动力学,ReMD),它利用了现代计算机硬件和软件的能力,并且通过利用许多分子动力学软件包中包含的并行计算方法,可以直接应用于任意大小和复杂度的系统(在此,我们以GROMACS为例进行说明)。ReMD算法在基于宏观启发且普遍适用的自由能最小化方法的背景下利用了这些特性,该方法基于通过使用每次迭代时的组成作为参考态,用数学上简单的凸理想溶液模型对系统吉布斯自由能函数进行迭代近似。最后,我们还描述了一种简单且计算高效的方法,用于估计在主要计算中相对于其他物质含量极少的物种的平衡浓度。为了演示该算法,我们展示了它在文献中先前考虑的两个经典示例系统中的应用:N - O - NO系统和氨合成系统。