Global optimization of parameters in the reactive force field ReaxFF for SiOH
Global optimization of parameters in the reactive force field ReaxFF for SiOH
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DOI：
10.1002/jcc.23382
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发表时间：
2013-09-30
影响因子：
3
通讯作者：
Hartke, Bernd
中科院分区：
文献类型：
--
作者：
Larsson, Henrik R.;van Duin, Adri C. T.;Hartke, Bernd
我们使用无偏全局优化来拟合一组给定的参考数据的反作用力场。具体地说，我们使用了遗传算法（GA）来使ReaxFF适应SiOH数据，使用内部的GA代码，该代码通过消息传递接口（MPI）在引用数据项之间并行化。结果表明，对于全局优化效率而言，遗传算法调整的细节远不如使用合适的参数变化范围重要。为了建立这些范围，既可以使用先验知识，也可以使用连续的GA优化阶段，每个阶段都建立在前一阶段找到的最佳参数向量和范围之上。我们最终得到了优化的力场，误差测量比以前发表的要小。因此，这种优化方法将有助于将力场拟合从专业任务转变为日常商品，即使对于更困难的反作用力场情况也是如此。(c) 2013 Wiley Periodicals, Inc.；
We have used unbiased global optimization to fit a reactive force field to a given set of reference data. Specifically, we have employed genetic algorithms (GA) to fit ReaxFF to SiOH data, using an in-house GA code that is parallelized across reference data items via the message-passing interface (MPI). Details of GA tuning turn-ed out to be far less important for global optimization efficiency than using suitable ranges within which the parameters are varied. To establish these ranges, either prior knowledge can be used or successive stages of GA optimizations, each building upon the best parameter vectors and ranges found in the previous stage. We have finally arrive-ed at optimized force fields with smaller error measures than those published previously. Hence, this optimization approach will contribute to converting force-field fitting from a specialist task to an everyday commodity, even for the more difficult case of reactive force fields. (c) 2013 Wiley Periodicals, Inc.