Sparse modeling of chemical bonding in binary compounds. Issue 1 (31st December 2019)

• Record Type: Journal Article
• Authors: Kanda, Yosuke; Fujii, Hitoshi; Oguchi, Tamio
• Is Part Of: Science and technology of advanced materials. Volume 20:Issue 1(2019)
• Page Start: 1178
• Page End: 1188
• Publication Date: 2019-12-31
• Subjects: Sparse modeling -- machine learning -- chemical bonding -- binary compounds; 404 Materials informatics / Genomics; Materials -- Technological innovations -- Periodicals; 620.112
• DOI: 10.1080/14686996.2019.1697858
• Languages: English
• ISSNs: 1468-6996

Abstract

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. Graphical Abstract: uf0001