Sparse modeling of chemical bonding in binary compounds

Abstract

A sparse model for quantifying energy difference between zinc-blende and rock-salt crystal structures in octet elemental and binary materials is constructed by using the linearly independent descriptor-generation method and exhaustive search, following the previous work by Ghiringhelli et al. [Phys Rev Lett. 2015;114:105503]. The obtained simplest model includes only atomic radius information of constituent atoms and its physical meaning is interpreted in relation to van Arkel-Ketelaar’s triangle for classifying chemical bonding in binary compounds.

Keywords

• sparse modeling
• machine learning
• chemical bonding
• binary compounds