Big–deep–smart data in imaging for guiding materials design [electronic resource].
- Washington, D.C. : United States. Dept. of Energy, 2015.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy
- Physical Description:
- pages 973-980 : digital, PDF file
- Additional Creators:
- Oak Ridge National Laboratory, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
- Restrictions on Access:
- Free-to-read Unrestricted online access
- Harnessing big data, deep data, and smart data from state-of-the-art imaging might accelerate the design and realization of advanced functional materials. Here we discuss new opportunities in materials design enabled by the availability of big data in imaging and data analytics approaches, including their limitations, in material systems of practical interest. We specifically focus on how these tools might help realize new discoveries in a timely manner. Such methodologies are particularly appropriate to explore in light of continued improvements in atomistic imaging, modelling and data analytics methods.
- Report Numbers:
- E 1.99:1393877
- Published through SciTech Connect.
Nature Materials 14 10 ISSN 1476-1122 AM
Sergei V. Kalinin; Bobby G. Sumpter; Richard K. Archibald.
- Funding Information:
View MARC record | catkey: 24061040