Global potential energy surface (PES) exploration provides a unique route to predict the thermodynamic and kinetic properties of unknown materials, but the task is highly challenging for systems with tight covalent bonds. Here, we develop the local-softening stochastic surface walking (LS-SSW) method for scanning corrugated PESs. LS-SSW transforms the vibrational mode space of a system by adding pairwise penalty potentials with a self-adaption mechanism, which helps to delocalize and soften the strong local modes. This allows the stochastic surface walking (SSW) method to capture more efficiently the correct local atomic movement toward nearby minima and simultaneously reduce the barrier height of reactions. As a result, the local trapping time in searching for the corrugated PES is greatly reduced. LS-SSW can be applied generally to the reaction pathway sampling and the global PES exploration of both clusters and crystals, the high efficiency of which is demonstrated in searching the reaction pathways between C4H6 isomers, finding the global minimum of carbon clusters up to 360 atoms, and constructing the global PES of Fe7C3 material.

中文翻译：

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局部软化随机表面行走，用于快速探索波纹势能表面。


全球势能表面 （PES） 探索为预测未知材料的热力学和动力学特性提供了一种独特的途径，但对于具有紧密共价键的系统来说，这项任务极具挑战性。在这里，我们开发了用于扫描波纹 PES 的局部软化随机表面步走 （LS-SSW） 方法。LS-SSW 通过添加具有自适应机制的成对罚势来转换系统的振动模态空间，这有助于去域化和软化强局部模态。这使得随机表面行走 （SSW） 方法能够更有效地捕获正确的局部原子向附近最小值的运动，同时降低反应的势垒高度。因此，搜索波纹 PES 的局部陷印时间大大减少。LS-SSW 通常可应用于反应途径采样和团簇和晶体的整体 PES 探索，其高效性体现在搜索 C4H6 异构体之间的反应途径，找到高达 360 个原子的碳团簇的全局最小值，以及构建 Fe7C3 材料的全局 PES。