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Oxidation states are the charges of atoms after their ionic approximation of their bonds, which have been widely used in charge-neutrality verification, crystal structure determination, and reaction estimation. Currently only heuristic…

Materials Science · Physics 2022-11-30 Nihang Fu , Jeffrey Hu , Ying Feng , Gregory Morrison , Hans-Conrad zur Loye , Jianjun Hu

High-throughput calculations are a very promising tool for screening a large number of compounds in order to discover new useful materials. Ternary intermetallic are thus investigated in the present work to find new compounds potentially…

Materials Science · Physics 2020-10-22 Celine Barreteau , Jean-Claude Crivello , Jean-Marc Joubert , Eric Alleno

Identifying novel functional materials with desired key properties is an important part of bridging the gap between fundamental research and technological advancement. In this context, high-throughput calculations combined with data-mining…

Even though thermodynamic energy-based crystal structure prediction (CSP) has revolutionized materials discovery, the energy-driven CSP approaches often struggle to identify experimentally realizable metastable materials synthesized through…

Materials Science · Physics 2025-05-15 Yu Xin , Peng Liu , Zhuohang Xie , Wenhui Mi , Pengyue Gao , Hong Jian Zhao , Jian Lv , Yanchao Wang , Yanming Ma

We use ab initio global structural prediction, and specifically the minima hopping method, to explore the periodic table in search of novel oxide phases. In total, we study 183 different compositions of the form MXO2, where M=(Cu, Ag, Au)…

We present an ensemble machine-learning approach for composition-based, structure-agnostic screening of candidate superconductors among ternary hydrides under high pressure. Hydrogen-rich hydrides are known to exhibit high superconducting…

Superconductivity · Physics 2026-05-18 Kazuaki Tokuyama , Souta Miyamoto , Taichi Masuda , Katsuaki Tanabe

We present a scale-bridging approach based on a multi-fidelity (MF) machine-learning (ML) framework leveraging Gaussian processes (GP) to fuse atomistic computational model predictions across multiple levels of fidelity. Through the…

Computational Physics · Physics 2020-08-06 Anh Tran , Julien Tranchida , Tim Wildey , Aidan P. Thompson

Materials properties depend strongly on chemical composition, i.e., the relative amounts of each chemical element. Changes in composition lead to entirely different chemical arrangements, which vary in complexity from perfectly ordered…

Materials Science · Physics 2025-06-24 Killian Sheriff , Daniel Xiao , Yifan Cao , Lewis R. Owen , Rodrigo Freitas

Computational materials discovery relies on the generation of plausible crystal structures. The plausibility is typically judged through density functional theory methods which, while typically accurate at zero Kelvin, often favor…

Computational Engineering, Finance, and Science · Computer Science 2025-11-04 Thorben Prein , Willis O'Leary , Aikaterini Flessa Savvidou , Elchaïma Bourneix , Joonatan E. M. Laulainen

We report the computational investigation of a series of ternary X$_4$Y$_2$Z and X$_5$Y$_2$Z$_2$ compounds with X={Mg, Ca, Sr, Ba}, Y={P, As, Sb, Bi}, and Z={S, Se, Te}. The compositions for these materials were predicted through a search…

Materials Science · Physics 2019-04-03 Maximilian Amsler , Logan Ward , Vinay I. Hegde , Maarten G. Goesten , Xia Yi , Chris Wolverton

Computational searches for new materials are naturally turning from binary systems, to ternary and other multicomponent systems, and beyond. Here, we select the industrially-relevant metals titanium and aluminium and report the results of…

Materials Science · Physics 2021-12-16 Joseph R. Nelson , Richard J. Needs , Chris J. Pickard

A high-throughput screening using density functional calculations is performed to search for stable boride superconductors from the existing materials database. The workflow employs the fast frozen phonon method as the descriptor to…

Materials Science · Physics 2024-04-30 Shiya Chen , Zepeng Wu , Zhen Zhang , Shunqing Wu , Kai-Ming Ho , Vladimir Antropov , Yang Sun

We propose an efficient computational methodology for predicting the synthesizability of high entropy oxides (HEOs) in a large space of possible candidate compounds. HEOs are a growing field with an enormous potential chemical composition…

Materials Science · Physics 2026-03-03 Oliver A. Dicks , Solveig S. Aamlid , Alannah M. Hallas , Joerg Rottler

The prediction of energetically stable crystal structures formed by a given chemical composition is a central problem in solid-state physics. In principle, the crystalline state of assembled atoms can be determined by optimizing the energy…

Materials Science · Physics 2022-06-01 Minoru Kusaba , Chang Liu , Ryo Yoshida

The optimized effective potential (OEP) method is a promising technique for calculating the ground state properties of a system within the density functional theory. However, it is not widely used as its computational cost is rather high…

Materials Science · Physics 2016-12-15 Taro Fukazawa , Hisazumi Akai

The oxidation state (OS) is an essential chemical concept that embodies chemical intuition but cannot be computed with well-defined physical laws. We establish a data-driven paradigm, with its implementation as Tsinghua Oxidation States in…

Chemical Physics · Physics 2025-07-30 Yue Yin , Hai Xiao

Identifying optimal synthesis conditions for metal-organic frameworks (MOFs) is a major challenge that can serve as a bottleneck for new materials discovery and development. Trial-and-error approach that relies on a chemist's intuition and…

Materials Science · Physics 2021-09-01 Hyunsoo Park , Yeonghun Kang , Wonyoung Choe , Jihan Kim

We have developed an efficient crystal structure prediction (CSP) method for desired chemical compositions, specifically suited for compounds featuring recurring molecules or rigid bodies. We applied this method to two metal chalcogenides:…

Materials Science · Physics 2024-08-01 Qi Zhang , Amitava Choudhury , Aleksandr Chernatynskiy

The development of new high dielectric materials is essential for advancement in modern electronics. Oxides are generally regarded as the most promising class of high dielectric materials for industrial applications as they possess both…

Materials Science · Physics 2019-09-11 Jingyu Qu , David Zageceta , Weiwei Zhang , Qiang Zhu

Ternary C_{x}N_{y}O_{z} compounds are actively researched as novel high energy density and ultrahard materials. Although some synthesis work has been performed at ambient conditions, very little is known about the high pressure chemistry of…

Materials Science · Physics 2017-10-11 Brad A. Steele , Ivan I. Oleynik
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