Big–deep–smart data in imaging for guiding materials design
- 23 September 2015
- journal article
- Published by Springer Science and Business Media LLC in Nature Materials
- Vol. 14 (10), 973-980
- https://doi.org/10.1038/nmat4395
Abstract
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.Keywords
This publication has 77 references indexed in Scilit:
- A single-atom transistorNature Nanotechnology, 2012
- Predicting crystal structure by merging data mining with quantum mechanicsNature Materials, 2006
- Polarization dynamics and formation of polar nanoregions in relaxor ferroelectricsPhysical Review B, 2006
- Review of crystal and domain structures in thesolid solutionPhysical Review B, 2005
- The Renaissance of Magnetoelectric MultiferroicsScience, 2005
- Complexity in Strongly Correlated Electronic SystemsScience, 2005
- Revival of the magnetoelectric effectJournal of Physics D: Applied Physics, 2005
- Factors Governing Oxygen Reduction in Solid Oxide Fuel Cell CathodesChemical Reviews, 2004
- Colossal magnetoresistant materials: the key role of phase separationPhysics Reports, 2001
- Spin glasses: Experimental facts, theoretical concepts, and open questionsReviews of Modern Physics, 1986