Published February 12, 2021 | Version v1
Journal article Open

Reducing Time to Discovery: Materials and Molecular Modeling, Imaging, Informatics, and Integration

Description

Multiscale and multimodal imaging of material structures and properties provides solid ground on which materials theory and design can flourish. Recently, KAIST announced 10 flagship research fields, which include KAIST Materials Revolution: Materials and Molecular Modeling, Imaging, Informatics and Integration (M3I3). The M3I3 initiative aims to reduce the time for the discovery, design and development of materials based on elucidating multiscale processing–structure–property relationship and materials hierarchy, which are to be quantified and understood through a combination of machine learning and scientific insights. In this review, we begin by introducing recent progress on related initiatives around the globe, such as the Materials Genome Initiative (U.S.), Materials Informatics (U.S.), the Materials Project (U.S.), the Open Quantum Materials Database (U.S.), Materials Research by Information Integration Initiative (Japan), Novel Materials Discovery (E.U.), the NOMAD repository (E.U.), Materials Scientific Data Sharing Network (China), Vom Materials Zur Innovation (Germany), and Creative Materials Discovery (Korea), and discuss the role of multiscale materials and molecular imaging combined with machine learning in realizing the vision of M3I3. Specifically, microscopies using photons, electrons, and physical probes will be revisited with a focus on the multiscale structural hierarchy, as well as structure–property relationships. Additionally, data mining from the literature combined with machine learning will be shown to be more efficient in finding the future direction of materials structures with improved properties than the classical approach. Examples of materials for applications in energy and information will be reviewed and discussed. A case study on the development of a Ni–Co–Mn cathode materials illustrates M3I3's approach to creating libraries of multiscale structure–property–processing relationships. We end with a future outlook toward recent developments in the field of M3I3.

Notes

Due to the large number of authors, only the first 20 and the University of Chicago authors are included on the above author list. Please download the article for the complete list of authors.

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Additional details

Identifiers

DOI
10.1021/acsnano.1c00211
Other
oai:uchicago.tind.io:13347

Funding

National Science Foundation
TRIPODS + X:RES-1839234
Korean Advanced Institute of Science and Engineering
Nano/Human Interfaces Presidential Initiative
U.S. Department of Energy

UChicago Information

Division(s)
Physical Sciences Division
Center(s) or Institute(s)
James Franck Institute