Machine-enabled inverse design of inorganic solid materials: promises and challenges
Author:
Affiliation:
1. Department of Chemical and Biomolecular Engineering
2. Korea Advanced Institute of Science and Technology (KAIST)
3. Daejeon 34141
4. Republic of Korea
Abstract
The grand challenge of materials science, discovery of novel materials with target properties, can be greatly accelerated by machine-learned inverse design strategies.
Funder
National Research Foundation of Korea
Publisher
Royal Society of Chemistry (RSC)
Subject
General Chemistry
Link
http://pubs.rsc.org/en/content/articlepdf/2020/SC/D0SC00594K
Reference98 articles.
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