Prediction and Classification of Formation Energies of Binary Compounds by Machine Learning: An Approach without Crystal Structure Information
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DOI: 10.1021/acsomega.1c01517
Abstract: It is well believed that machine learning models could help to predict the formation energies of materials if all elemental and crystal structural details are known. In this paper, it is shown that even without… read more here.
Keywords: crystal structure; machine learning; binary compounds; formation ... See more keywords