Data mining and accelerated electronic structure theory as a tool in the search for new functional materials

TL;DR

This study combines data mining with accelerated electronic structure calculations to predict new functional inorganic materials, identifying 136 promising candidates for radiation detection applications.

Contribution

It introduces an automated ab-initio methodology integrating structural data mining with electronic structure calculations to efficiently discover new functional materials.

Findings

Identified 136 novel materials for ionizing radiation detection.

Accelerated electronic structure calculations enabled rapid screening of 22,000 compounds.

Developed an accessible database for further research and validation.

Abstract

Data mining is a recognized predictive tool in a variety of areas ranging from bioinformatics and drug design to crystal structure prediction. In the present study, an electronic structure implementation has been combined with structural data from the Inorganic Crystal Structure Database to generate results for highly accelerated electronic structure calculations of about 22,000 inorganic compounds. It is shown how data mining algorithms employed on the database can identify new functional materials with desired materials properties, resulting in a prediction of 136 novel materials with potential for use as detector materials for ionizing radiation. The methodology behind the automatized ab-initio approach is presented, results are tabulated and a version of the complete database is made available at the internet web site http://gurka.fysik.uu.se/ESP/ (Ref.1).