非晶态玻璃中用于盆地跳跃的高效扰动方法
Efficient perturbations for basin hopping in amorphous glasses
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中文总结 AI 辅助
本文以非晶态Al₂O₃为模型，提出弛豫辅助的非局域扰动方法，可减少非晶材料势能面采样的试探移动次数，提升结构搜索与反向蒙特卡洛的采样效率。
中文摘要 AI 辅助
对非晶态材料复杂势能面的高效探索是计算结构发现与优化的核心。传统蒙特卡洛、反向蒙特卡洛及相关方法通常通过小的局域试探移动采样构型空间，可能需要数百万至数千万次移动才能收敛。本文评估更大的非局域扰动结合局域几何弛豫作为替代采样策略，以非晶态Al₂O₃为模型系统开发并测试了四种扰动类型。其中，移动氧原子改变两个铝原子的配位数，相比传统蒙特卡洛轨迹，能以少得多的试探移动获得低能构型。这些结果表明，弛豫辅助的非局域移动可减少陷入局部极小值的情况，提升结构搜索与反向蒙特卡洛工作流中的采样效率。
英文摘要
Efficient exploration of the complex potential-energy landscapes of amorphous materials is central to computational structure discovery and refinement. Conventional Monte Carlo, reverse Monte Carlo, and related methods typically sample configuration space through small, local trial moves and may require millions to tens of millions of moves to converge. Here, we evaluate larger, nonlocal perturbations followed by local geometry relaxation as an alternative sampling strategy. We develop and test four perturbation types using amorphous Al$_2$O$_3$ as a model system. Among them, moving an oxygen atom to change the coordination numbers of two aluminum atoms, allows access to low-energy configurations with substantially fewer trial moves than a conventional Monte Carlo trajectory. These results suggest that relaxation-assisted nonlocal moves could reduce trapping in local minima and improve sampling in structure-search and reverse Monte Carlo workflows.
