Emerging chalcohalide materials for energy applications

UV Ghorpade, MP Suryawanshi, MA Green… - Chemical …, 2022 - ACS Publications
Semiconductors with multiple anions currently provide a new materials platform from which
improved functionality emerges, posing new challenges and opportunities in material …

Machine learning in scanning transmission electron microscopy

SV Kalinin, C Ophus, PM Voyles, R Erni… - Nature Reviews …, 2022 - nature.com
Scanning transmission electron microscopy (STEM) has emerged as a uniquely powerful
tool for structural and functional imaging of materials on the atomic level. Driven by …

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 …

Structure prediction drives materials discovery

AR Oganov, CJ Pickard, Q Zhu, RJ Needs - Nature Reviews Materials, 2019 - nature.com
Progress in the discovery of new materials has been accelerated by the development of
reliable quantum-mechanical approaches to crystal structure prediction. The properties of a …

Expanding frontiers in materials chemistry and physics with multiple anions

H Kageyama, K Hayashi, K Maeda, JP Attfield… - Nature …, 2018 - nature.com
During the last century, inorganic oxide compounds laid foundations for materials synthesis,
characterization, and technology translation by adding new functions into devices previously …

Machine-learning phase prediction of high-entropy alloys

W Huang, P Martin, HL Zhuang - Acta Materialia, 2019 - Elsevier
High-entropy alloys (HEAs) have been receiving intensive attention due to their unusual
properties that largely depend on the selection among three phases: solid solution (SS) …

New frontiers for the materials genome initiative

JJ de Pablo, NE Jackson, MA Webb, LQ Chen… - npj Computational …, 2019 - nature.com
Abstract The Materials Genome Initiative (MGI) advanced a new paradigm for materials
discovery and design, namely that the pace of new materials deployment could be …

SISSO: A compressed-sensing method for identifying the best low-dimensional descriptor in an immensity of offered candidates

R Ouyang, S Curtarolo, E Ahmetcik, M Scheffler… - Physical Review …, 2018 - APS
The lack of reliable methods for identifying descriptors—the sets of parameters capturing the
underlying mechanisms of a material's property—is one of the key factors hindering efficient …

The Open Quantum Materials Database (OQMD): assessing the accuracy of DFT formation energies

S Kirklin, JE Saal, B Meredig, A Thompson… - npj Computational …, 2015 - nature.com
Abstract The Open Quantum Materials Database (OQMD) is a high-throughput database
currently consisting of nearly 300,000 density functional theory (DFT) total energy …

Computational predictions of energy materials using density functional theory

A Jain, Y Shin, KA Persson - Nature Reviews Materials, 2016 - nature.com
In the search for new functional materials, quantum mechanics is an exciting starting point.
The fundamental laws that govern the behaviour of electrons have the possibility, at the …