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Rapid screening of high-throughput ground state predictions
Calphad ( IF 1.9 ) Pub Date : 2021-07-17 , DOI: 10.1016/j.calphad.2021.102306
Sayan Samanta 1 , Axel van de Walle 1
Affiliation  

High-throughput computational thermodynamic approaches are becoming an increasingly popular tool to uncover novel compounds. However, traditional methods tend to be limited to stability predictions of stoichiometric phases at absolute zero. Such methods thus carry the risk of identifying an excess of possible phases that do not survive to temperatures of practical relevance. We demonstrate how the Calphad formalism, informed by simple first-principles input can be simply used to overcome this problem at a low computational cost and deliver quantitatively useful phase diagram predictions at all temperatures. We illustrate the method by re-assessing prior compound formation predictions and reconcile these findings with long-standing experimental evidence to the contrary.



中文翻译:

高通量基态预测的快速筛选

高通量计算热力学方法正成为发现新化合物的越来越流行的工具。然而,传统方法往往仅限于在绝对零时化学计量相的稳定性预测。因此,这样的方法存在识别过量的在实际相关温度下无法存活的可能相的风险。我们展示了 Calphad 形式主义如何以简单的第一性原理输入为基础,以较低的计算成本简单地用于克服这个问题,并在所有温度下提供定量有用的相图预测。我们通过重新评估先前的化合物形成预测来说明该方法,并将这些发现与相反的长期实验证据相协调。

更新日期:2021-07-18
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