Learning from data to design functional materials without inversion symmetry

Autor: Prasanna V. Balachandran, Joshua Young, Turab Lookman, James M. Rondinelli
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: Nature Communications, Vol 8, Iss 1, Pp 1-13 (2017)
Druh dokumentu: article
ISSN: 2041-1723
DOI: 10.1038/ncomms14282
Popis: Computational design of functional materials with broken inversion symmetry is a complex task. Here, the authors demonstrate an approach that integrates symmetry analysis, data science methods, and density functional theory to accelerate the selection and identification process in complex oxides.
Databáze: Directory of Open Access Journals