MAGUS: machine learning and graph theory assisted universal structure searcher
Crystal structure predictions based on first-principles calculations have gained great
success in materials science and solid state physics. However, the remaining challenges …
success in materials science and solid state physics. However, the remaining challenges …
Computational design of energy‐related materials: From first‐principles calculations to machine learning
Energy‐related materials are crucial for advancing energy technologies, improving
efficiency, reducing environmental impacts, and supporting sustainable development …
efficiency, reducing environmental impacts, and supporting sustainable development …
Coexistence of superconductivity and electride states in Ca 2 H with an antifluorite-type motif under compression
Hydrogen-abundant compounds, as highly potential candidates of near-or room-
temperature superconductors, have recently attracted substantial attention. It is noted that …
temperature superconductors, have recently attracted substantial attention. It is noted that …
Superconductivity in electride
Located at crystal voids, interstitial anion electrons (IAEs) have diverse topologies, which
may be tuned to achieve different properties. Elucidating the role of IAEs in electron-phonon …
may be tuned to achieve different properties. Elucidating the role of IAEs in electron-phonon …
Interstitial anionic electrons favoring superconductivity in Li-As electrides
Interstitial anionic electrons (IAEs) at lattice cavities of electrides, which have diverse
morphologies and concentrations, can induce interesting physical and chemical properties …
morphologies and concentrations, can induce interesting physical and chemical properties …
[HTML][HTML] Pressure-induced evolution of stoichiometries and electronic structures of host–guest Na–B compounds
Z Guo, X Li, A Bergara, S Ding, X Zhang… - Matter and Radiation at …, 2023 - pubs.aip.org
Superionic and electride behaviors in materials, which induce a variety of exotic physical
properties of ions and electrons, are of great importance both in fundamental research and …
properties of ions and electrons, are of great importance both in fundamental research and …
A comprehensive investigation on the accuracy and efficiency of methods for melting temperature calculation using molecular dynamics simulations
X Wang, M Yang, X Gai, Y Sun, B Cao, J Chen… - Journal of Molecular …, 2024 - Elsevier
Abstract Machine learning approaches have been extensively applied to improve the
accuracy and reliability of potentials, addressing inherent limitations in molecular dynamics …
accuracy and reliability of potentials, addressing inherent limitations in molecular dynamics …
[HTML][HTML] Development of a neuroevolution machine learning potential of Pd-Cu-Ni-P alloys
R Zhao, S Wang, Z Kong, Y Xu, K Fu, P Peng, C Wu - Materials & Design, 2023 - Elsevier
Abstract Pd-Cu-Ni-P alloy is an ideal model system of metallic glass known for its
exceptional glass-forming ability. However, few correlation of structures with properties was …
exceptional glass-forming ability. However, few correlation of structures with properties was …
Exploring the Coexistence Conditions and Intrinsic Relationships between Electrides, Superconductivity, Kagome Lattice, and Superionic Behaviors in Li–Ge …
X Wang, W Tang, XW Sun, ZJ Liu, B Cao… - ACS Materials …, 2024 - ACS Publications
A systematic prediction of crystal structures of the Li x Ge (x= 1–8) system is performed using
a combination of structure prediction and ab initio calculations coupled with deep learning …
a combination of structure prediction and ab initio calculations coupled with deep learning …
Vacancy defects impede the transition from peapods to diamond: a neuroevolution machine learning study
Exploration of novel carbon allotropes has been a central subject in materials science, in
which carbon peapods hold great potential as a precursor for the development of new …
which carbon peapods hold great potential as a precursor for the development of new …