Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, USA.
J Chem Phys. 2013 Apr 28;138(16):164104. doi: 10.1063/1.4801869.
We present a local superbasin kinetic Monte Carlo (LSKMC) method that efficiently treats multiple-time-scale problems in kinetic Monte Carlo (KMC). The method is designed to solve the small-barrier problem created by groups of recurrent free-energy minima connected by low free-energy barriers and separated from the full phase space of the system by high barriers. We propose an algorithm to detect, on the fly, groups of recurrent free-energy minima connected by low free-energy barriers and to consolidate them into "superbasins," which we treat with rate equations and/or absorbing Markov chains. We discuss various issues involved with implementing LSKMC simulations that contain local superbasins and non-superbasin events concurrently. These issues include the time distribution of superbasin escapes and interactions between superbasin and non-superbasin states. The LSKMC method is exact, as it introduces no new approximations into conventional KMC simulations. We demonstrate various aspects of LSKMC in several examples, which indicate that significant increases in computational efficiency can be achieved using this method.
我们提出了一种局部超区动力学蒙特卡罗（LSKMC）方法，该方法能够有效地处理动力学蒙特卡罗（KMC）中的多时间尺度问题。该方法旨在解决由通过低自由能势垒连接且被系统的高势垒与完整相空间隔开的周期性自由能极小值组产生的小势垒问题。我们提出了一种在飞行中检测由低自由能势垒连接的周期性自由能极小值组并将它们合并为“超区”的算法，我们用速率方程和/或吸收马尔可夫链来处理超区。我们讨论了在同时包含局部超区和非超区事件的 LSKMC 模拟中涉及的各种问题。这些问题包括超区逃逸的时间分布和超区与非超区状态之间的相互作用。LSKMC 方法是精确的，因为它不会向传统的 KMC 模拟中引入新的近似。我们在几个示例中展示了 LSKMC 的各个方面，这表明使用该方法可以显著提高计算效率。
