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 …

[HTML][HTML] A perspective on conventional high-temperature superconductors at high pressure: Methods and materials

JA Flores-Livas, L Boeri, A Sanna, G Profeta, R Arita… - Physics Reports, 2020 - Elsevier
Two hydrogen-rich materials, H 3 S and LaH 10, synthesized at megabar pressures, have
revolutionized the field of condensed matter physics providing the first glimpse to the …

Penta-graphene: A new carbon allotrope

S Zhang, J Zhou, Q Wang, X Chen, Y Kawazoe… - Proceedings of the …, 2015 - pnas.org
A 2D metastable carbon allotrope, penta-graphene, composed entirely of carbon pentagons
and resembling the Cairo pentagonal tiling, is proposed. State-of-the-art theoretical …

Machine-learning atomic simulation for heterogeneous catalysis

D Chen, C Shang, ZP Liu - npj Computational Materials, 2023 - nature.com
Heterogeneous catalysis is at the heart of chemistry. New theoretical methods based on
machine learning (ML) techniques that emerged in recent years provide a new avenue to …

Interface structure prediction via CALYPSO method

B Gao, P Gao, S Lu, J Lv, Y Wang, Y Ma - Science Bulletin, 2019 - Elsevier
The atomistic structures of solid–solid interfaces are of fundamental interests for
understanding physical properties of interfacial materials. However, determination of …

Two‐dimensional boron monolayers mediated by metal substrates

Z Zhang, Y Yang, G Gao, BI Yakobson - Angewandte Chemie, 2015 - Wiley Online Library
Abstract Two‐dimensional (2D) materials, such as graphene and boron nitride, have specific
lattice structures independent of external conditions. In contrast, the structure of 2D boron …

Catalysis in the digital age: Unlocking the power of data with machine learning

BM Abraham, MV Jyothirmai, P Sinha… - Wiley …, 2024 - Wiley Online Library
The design and discovery of new and improved catalysts are driving forces for accelerating
scientific and technological innovations in the fields of energy conversion, environmental …

CALYPSO structure prediction method and its wide application

H Wang, Y Wang, J Lv, Q Li, L Zhang, Y Ma - Computational Materials …, 2016 - Elsevier
Atomistic structure prediction from “scratch” is one of the central issues in physical, chemical,
materials and planetary science, and it will inevitably play a critical role in accelerating …

Recent advances in La2NiMnO6 double perovskites for various applications; challenges and opportunities

SC Baral, P Maneesha, EG Rini, S Sen - Progress in Solid State Chemistry, 2023 - Elsevier
Abstract Double perovskites R 2 NiMnO 6 (R= Rare earth element)(RNMO) are a significant
class of materials owing to their Multifunctional properties with the structural modifications. In …

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 …