Human-and machine-centred designs of molecules and materials for sustainability and decarbonization

J Peng, D Schwalbe-Koda, K Akkiraju, T **e… - Nature Reviews …, 2022 - nature.com
Breakthroughs in molecular and materials discovery require meaningful outliers to be
identified in existing trends. As knowledge accumulates, the inherent bias of human intuition …

Emerging materials intelligence ecosystems propelled by machine learning

R Batra, L Song, R Ramprasad - Nature Reviews Materials, 2021 - nature.com
The age of cognitive computing and artificial intelligence (AI) is just dawning. Inspired by its
successes and promises, several AI ecosystems are blossoming, many of them within the …

Scaling deep learning for materials discovery

A Merchant, S Batzner, SS Schoenholz, M Aykol… - Nature, 2023 - nature.com
Novel functional materials enable fundamental breakthroughs across technological
applications from clean energy to information processing,,,,,,,,,–. From microchips to batteries …

Autonomous experimentation systems for materials development: A community perspective

E Stach, B DeCost, AG Kusne, J Hattrick-Simpers… - Matter, 2021 - cell.com
Solutions to many of the world's problems depend upon materials research and
development. However, advanced materials can take decades to discover and decades …

Deep learning model to predict complex stress and strain fields in hierarchical composites

Z Yang, CH Yu, MJ Buehler - Science Advances, 2021 - science.org
Materials-by-design is a paradigm to develop previously unknown high-performance
materials. However, finding materials with superior properties is often computationally or …

Machine learning for catalysis informatics: recent applications and prospects

T Toyao, Z Maeno, S Takakusagi, T Kamachi… - Acs …, 2019 - ACS Publications
The discovery and development of catalysts and catalytic processes are essential
components to maintaining an ecological balance in the future. Recent revolutions made in …

Electronic-structure methods for materials design

N Marzari, A Ferretti, C Wolverton - Nature materials, 2021 - nature.com
The accuracy and efficiency of electronic-structure methods to understand, predict and
design the properties of materials has driven a new paradigm in research. Simulations can …

A review of the recent progress in battery informatics

C Ling - npj Computational Materials, 2022 - nature.com
Batteries are of paramount importance for the energy storage, consumption, and
transportation in the current and future society. Recently machine learning (ML) has …

Material evolution with nanotechnology, nanoarchitectonics, and materials informatics: what will be the next paradigm shift in nanoporous materials?

W Chaikittisilp, Y Yamauchi, K Ariga - Advanced Materials, 2022 - Wiley Online Library
Materials science and chemistry have played a central and significant role in advancing
society. With the shift toward sustainable living, it is anticipated that the development of …

In pursuit of the exceptional: Research directions for machine learning in chemical and materials science

J Schrier, AJ Norquist, T Buonassisi… - Journal of the American …, 2023 - ACS Publications
Exceptional molecules and materials with one or more extraordinary properties are both
technologically valuable and fundamentally interesting, because they often involve new …