Using a recently developed approach to represent ab initio based force fields by a neural network potential, we perform molecular dynamics simulations of lead telluride and cadmium telluride crystals. In particular, we study the diffusion of a single cation interstitial in these two systems. Our simulations indicate that the interstitials migrate via two distinct mechanisms: through hops between interstitial sites and through exchanges with lattice atoms. We extract activation energies for both of these mechanisms and show how the temperature dependence of the total diffusion coefficient deviates from Arrhenius behaviour. The accuracy of the neural network approach is estimated by comparing the results for three different independently trained potentials.

中文翻译：

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基于神经网络势的分子动力学模拟研究碲化铅和碲化镉中的阳离子间隙扩散

使用最近开发的方法通过神经网络势表示基于从头算的力场，我们对碲化铅和碲化镉晶体进行分子动力学模拟。特别是，我们研究了这两个系统中单个阳离子间隙的扩散。我们的模拟表明间隙通过两种不同的机制迁移：通过间隙位点之间的跳跃和通过与晶格原子的交换。我们提取了这两种机制的活化能，并展示了总扩散系数的温度依赖性如何偏离 Arrhenius 行为。通过比较三个不同的独立训练电位的结果来估计神经网络方法的准确性。