Nudged Elastic Band Method for Molecular Reactions Using Energy-Weighted Springs Combined with Eigenvector Following
Nudged Elastic Band Method for Molecular Reactions Using Energy-Weighted Springs Combined with Eigenvector Following
复制标题
DOI：
10.1021/acs.jctc.1c00462
复制
发表时间：
2021-07-18
影响因子：
5.5
通讯作者：
Jonsson, Hannes
中科院分区：
文献类型：
--
作者：
Asgeirsson, Vilhjalmur;Birgisson, Benedikt Orri;Jonsson, Hannes
采用爬升图像轻推弹性带法（CI-NEB）识别反应坐标，寻找代表反应过渡态的鞍点。它可以有效地利用并行计算，因为可以同时进行离散点（即所谓的图像）的计算。在典型的实现中，通过用相同刚性的弹簧连接相邻图像，使图像沿路径均匀分布。然而，对于具有高度灵活性的系统，这可能导致鞍点附近的分辨率较差。通过使弹簧常数随能量的增大而增大，提高了鞍点附近的分辨率。为了评估这种能量加权CI-NEB方法的性能，对121个分子反应的基准集进行了计算。根据输入参数分析了该方法的性能。研究发现，能量加权弹簧极大地提高了性能，并且使用所有反应的相同参数值，平均在不到1000次的能量和力评估（每张图像约100次）中成功定位了鞍点。在完全收敛前停止计算，从爬升图像的位置出发，采用特征向量跟随方法完成鞍点搜索，可以获得更好的性能。这种被称为NEB-TS的方法组合被证明是稳健和高效的，因为它将能量和力评估的平均次数减少到三分之一，即305次。这些方法在ORCA软件中得到了有效而灵活的实现。
The climbing image nudged elastic band method (CI-NEB) is used to identify reaction coordinates and to find saddle points representing transition states of reactions. It can make efficient use of parallel computing as the calculations of the discretization points, the so-called images, can be carried out simultaneously. In typical implementations, the images are distributed evenly along the path by connecting adjacent images with equally stiff springs. However, for systems with a high degree of flexibility, this can lead to poor resolution near the saddle point. By making the spring constants increase with energy, the resolution near the saddle point is improved. To assess the performance of this energy-weighted CI-NEB method, calculations are carried out for a benchmark set of 121 molecular reactions. The performance of the method is analyzed with respect to the input parameters. Energy-weighted springs are found to greatly improve performance and result in successful location of the saddle points in less than a thousand energy and force evaluations on average (about a hundred per image) using the same set of parameter values for all of the reactions. Even better performance is obtained by stopping the calculation before full convergence and complete the saddle point search using an eigenvector following method starting from the location of the climbing image. This combination of methods, referred to as NEB-TS, turns out to be robust and highly efficient as it reduces the average number of energy and force evaluations down to a third, to 305. An efficient and flexible implementation of these methods has been made available in the ORCA software.