The 2021 room-temperature superconductivity roadmap

B Lilia, R Hennig, P Hirschfeld, G Profeta… - Journal of Physics …, 2022 - iopscience.iop.org
Designing materials with advanced functionalities is the main focus of contemporary solid-
state physics and chemistry. Research efforts worldwide are funneled into a few high-end …

MAGUS: machine learning and graph theory assisted universal structure searcher

J Wang, H Gao, Y Han, C Ding, S Pan… - National Science …, 2023 - academic.oup.com
Crystal structure predictions based on first-principles calculations have gained great
success in materials science and solid state physics. However, the remaining challenges …

Accelerating crystal structure prediction by machine-learning interatomic potentials with active learning

EV Podryabinkin, EV Tikhonov, AV Shapeev… - Physical Review B, 2019 - APS
We propose a methodology for crystal structure prediction that is based on the evolutionary
algorithm USPEX and the machine-learning interatomic potentials actively learning on-the …

[HTML][HTML] High-temperature superconductivity in alkaline and rare earth polyhydrides at high pressure: A theoretical perspective

E Zurek, T Bi - The Journal of chemical physics, 2019 - pubs.aip.org
The theoretical exploration of the phase diagrams of binary hydrides under pressure using
ab initio crystal structure prediction techniques coupled with first principles calculations has …

Machine learning and energy minimization approaches for crystal structure predictions: a review and new horizons

J Graser, SK Kauwe, TD Sparks - Chemistry of Materials, 2018 - ACS Publications
Predicting crystal structure has always been a challenging problem for physical sciences.
Recently, computational methods have been built to predict crystal structure with success …

The XtalOpt evolutionary algorithm for crystal structure prediction

Z Falls, P Avery, X Wang, KP Hilleke… - The Journal of Physical …, 2020 - ACS Publications
Significant progress has been made in the field of a priori crystal structure prediction, with a
number of recent remarkable success stories. Herein, we briefly outline the methods that …

Metallic VS2 Monolayer Polytypes as Potential Sodium-Ion Battery Anode via ab Initio Random Structure Searching

DB Putungan, SH Lin, JL Kuo - ACS applied materials & interfaces, 2016 - ACS Publications
We systematically investigated the potential of single-layer VS2 polytypes as Na-battery
anode materials via density functional theory calculations. We found that sodiation tends to …

A novel superhard tungsten nitride predicted by machine-learning accelerated crystal structure search

K Xia, H Gao, C Liu, J Yuan, J Sun, HT Wang, D Xing - Science bulletin, 2018 - Elsevier
Transition metal nitrides have been suggested to have both high hardness and good
thermal stability with large potential application value, but so far stable superhard transition …

A systematic literature review of adaptive parameter control methods for evolutionary algorithms

A Aleti, I Moser - ACM Computing Surveys (CSUR), 2016 - dl.acm.org
Evolutionary algorithms (EAs) are robust stochastic optimisers that perform well over a wide
range of problems. Their robustness, however, may be affected by several adjustable …

[HTML][HTML] Tuning chemical precompression: Theoretical design and crystal chemistry of novel hydrides in the quest for warm and light superconductivity at ambient …

KP Hilleke, E Zurek - Journal of Applied Physics, 2022 - pubs.aip.org
Over the past decade, a combination of crystal structure prediction techniques and
experimental synthetic work has thoroughly explored the phase diagrams of binary hydrides …