缺陷输运张量的自动计算与收敛
Automated calculation and convergence of defect transport tensors
摘要：
缺陷输运是材料科学和催化中的关键过程，但由于迁移机制通常过于复杂而无法先验地枚举，因此输运张量的计算通常没有收敛的度量并且需要显著的最终用户干预。这两个瓶颈阻碍了高吞吐量的实现，这对于将模型形式的不确定性从原子间相互作用传播到预测模拟至关重要。为了解决这些问题，我们扩展了一个大规模并行加速采样方案，自主控制的贝叶斯估计的状态采样完整性，建立原子动力学蒙特卡罗模型的状态空间不可约下交换和空间群对称性。专注于孤立的缺陷，我们推导出缺陷输运张量的解析表达式，并通过计算与采样不确定性一致的扩散过程的合奏的Kullback-Leiber发散提供了一个收敛度量。该方法的自主性和有效性被证明在表面三聚体在钨和六元在氧化镁，这两者都表现出复杂的，相关的迁移机制。
英文摘要：
Defect transport is a key process in materials science and catalysis, but as migration mechanisms are often too complex to enumerate a priori, calculation of transport tensors typically have no measure of convergence and require significant end user intervention. These two bottlenecks prevent high-throughput implementations essential to propagate model-form uncertainty from interatomic interactions to predictive simulations. In order to address these issues, we extend a massively parallel accelerated sampling scheme, autonomously controlled by Bayesian estimators of statewise sampling completeness, to build atomistic kinetic Monte Carlo models on a state space irreducible under exchange and space group symmetries. Focusing on isolated defects, we derive analytic expressions for defect transport tensors and provide a convergence metric by calculating the Kullback-Leiber divergence across the ensemble of diffusion processes consistent with the sampling uncertainty. The autonomy and efficacy of the method is demonstrated on surface trimers in tungsten and hexa-interstitials in magnesium oxide, both of which exhibit complex, correlated migration mechanisms.
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