Data-centric science for materials innovation

Isao Tanaka, Krishna Rajan, Christopher Wolverton

Research output: Contribution to journalArticle

9 Scopus citations

Abstract

With the development of high-speed computers, networks, and huge storage, researchers can utilize a large volume and wide variety of materials data generated by experimental facilities and computations. The emergence of these big data and advanced analytical techniques has opened unprecedented opportunities for materials research. The discovery of many kinds of materials, such as energy-harvesting materials, structural materials, catalysts, optoelectronic materials, and magnetic materials, have been greatly accelerated through high-throughput screening. The utility of data-centric science for materials research is likely to grow significantly in the future. Unraveling the complexities inherent in big data could lead to novel design rules as well as new materials and functionalities.

Original languageEnglish (US)
Pages (from-to)659-663
Number of pages5
JournalMRS Bulletin
Volume43
Issue number9
DOIs
StatePublished - Sep 1 2018

Keywords

  • DFT calculations
  • database
  • informatics
  • machine learning

ASJC Scopus subject areas

  • Materials Science(all)
  • Condensed Matter Physics
  • Physical and Theoretical Chemistry

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