Prediction and Classification of Formation Energies of Binary Compounds by Machine Learning: An Approach without Crystal Structure Information

Abstract

= 0) are predicted using this model, and both show reasonable agreements with experimental and Materials Project's calculated values. The descriptor set is capable of reflecting the formation energies of binary compounds and is also consistent with the common understanding that the formation energy is mainly determined by electronegativity, electron affinity, bond energy, and other atomic properties. As crystal structure parameters are not necessary prerequisites, it can be widely applied to the formation energy prediction and classification of binary compounds in large quantities.

Topics & Concepts