We present an artificial intelligence (AI) method for automatically computing the melting point based on coexistence simulations in the NPT ensemble. Given the interatomic interaction model, the method makes decisions regarding the number of atoms and temperature at which to conduct simulations, and based on the collected data predicts the melting point along with the uncertainty, which can be systematically improved with more data. We demonstrate how incorporating physical models of the solid-liquid coexistence evolution enhances the AI method's accuracy and enables optimal decision-making to effectively reduce predictive uncertainty. To validate our approach, we compare our results with approximately 20 melting point calculations from the literature. Remarkably, we observe significant deviations in about one-third of the cases, underscoring the need for accurate and reliable AI-based algorithms for materials property calculations.

翻译：我们提出了一种人工智能（AI）方法，可在NPT系综中基于共存模拟自动计算熔点。给定原子间相互作用模型后，该方法自主决定模拟所需的原子数目与温度条件，并根据收集的数据预测熔点及其不确定性——该不确定性可通过增加数据量实现系统性改进。我们展示了将固液共存演化的物理模型融入AI方法如何提升其精度，并实现最优决策以有效降低预测不确定性。为验证该方法的有效性，我们将计算结果与文献中约20例熔点计算值进行对比。值得注意的是，约三分之一的案例中出现了显著偏差，这充分凸显了开发基于AI的精确可靠算法对于材料性质计算的必要性。