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 language | English (US) |
|---|---|
| Pages (from-to) | 659-663 |
| Number of pages | 5 |
| Journal | MRS Bulletin |
| Volume | 43 |
| Issue number | 9 |
| DOIs | |
| State | Published - Sep 1 2018 |
Funding
I.T. acknowledges the Japan Society for the Promotion of Science (JSPS) for a Grant-in-Aid for Scientific Research on Innovative Areas "Nano-Informatics" (18H05195) and a Grant-in-Aid for Scientific Research (A) (18H03843); Japan Science and Technology Agency (JST) through Materials Research by Information Integration Initiative (MI2I). K.R. acknowledges support from the National Science Foundation (NSF) DIBBs Project, Award No. ACI-16-40867. C.W. acknowledges support from the Center for Hierarchical Materials Design and from the US Department of Commerce, National Institute of Standards and Technology under Award No. 70NANB14H012.
Keywords
- DFT calculations
- database
- informatics
- machine learning
ASJC Scopus subject areas
- General Materials Science
- Condensed Matter Physics
- Physical and Theoretical Chemistry