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Machine learning potentials (MLPs) have become indispensable for performing accurate large-scale atomistic simulations and predicting crystal structures. This study introduces the development of a polynomial MLP specifically for the ternary…

Materials Science · Physics 2024-07-31 Atsuto Seko

High entropy alloys (HEA) show promise as a new type of high-performance structural material. Their vast degrees of freedom provide for extensive opportunities to design alloys with tailored properties. However, the compositional…

Disordered Systems and Neural Networks · Physics 2019-04-19 Qi Jie , Andrew Cheung , S. Joseph Poon

Cerium-based intermetallics have garnered significant research attention as potential new permanent magnets. In this study, we explore the compositional and structural landscape of Ce-Co-Cu ternary compounds using a machine learning…

Materials Science · Physics 2025-02-07 Weiyi Xia , Wei-Shen Tee , Paul Canfield , Rebecca Flint , Cai-Zhuang Wang

Evolutionary crystal structure prediction searches have been employed to explore the ternary Li-F-H system at 300 GPa. Metastable phases were uncovered within the static lattice approximation, with LiF$_3$H$_2$, LiF$_2$H, Li$_3$F$_4$H,…

Materials Science · Physics 2021-04-07 Tiange Bi , Andrew Shamp , Tyson Terpstra , Russell J. Hemley , Eva Zurek

The fundamental principles underlying the arrangement of elements into solid compounds with an enormous variety of crystal structures are still largely unknown. This study presents a general overview of the structure types appearing in an…

Materials Science · Physics 2017-12-11 Alon Hever , Corey Oses , Stefano Curtarolo , Ohad Levy , Amir Natan

A combination of theoretical calculation and the experimental synthesis to explore the new ternary compound is demonstrated in the Sr-Pt-Bi system. Since Pt-Bi is considered as a new critical charge-transfer pair for superconductivity, it…

Materials Science · Physics 2017-12-25 Xin Gui , Xin Zhao , Zuzanna Sobczak , Cai-Zhuang Wang , Tomasz Klimczuk , Kai-Ming Ho , Weiwei Xie

Predicting the glass-forming ability (GFA) of chemical compositions remains a fundamental challenge in materials science, especially for oxide glasses with broad compositional diversity. Traditional empirical and thermodynamic approaches…

Materials Science · Physics 2025-12-10 Fatemeh Mahmoudi

A novel method for crystal structure prediction, based on metadynamics and evolutionary algorithms, is presented here. This technique can be used to produce efficiently both the ground state and metastable states easily reachable from a…

Materials Science · Physics 2012-06-08 Qiang Zhu , Artem R. Oganov , Andriy O. Lyakhov

Predicting the ground state of alloy systems is challenging due to the large number of possible configurations. We identify an easily computed descriptor for the stability of binary surface alloys, the effective coordination number…

Materials Science · Physics 2017-02-17 Sananda Biswas , Shobhana Narasimhan

We present a genetic algorithm (GA) for structural search that combines the speed of structure exploration by classical potentials with the accuracy of density functional theory (DFT) calculations in an adaptive and iterative way. This…

Materials Science · Physics 2015-11-06 S. Q. Wu , M. Ji , C. Z. Wang , M. C. Nguyen , X. Zhao , K. Umemoto , R. M. Wentzcovitch , K. M. Ho

The discovery of intrinsic magnetic topological order in $\rm MnBi_2Te_4$ has invigorated the search for materials with coexisting magnetic and topological phases. These multi-order quantum materials are expected to exhibit new topological…

Only several compounds bearing Ag(II) cation and other transition metal cation have been known. Herein, we predict stability and crystal structures of hypothetical ternary silver(II) fluorides with copper, nickel and cobalt in 1:1…

Materials Science · Physics 2021-07-29 Mateusz A. Domański , Mariana Derzsi , Wojciech Grochala

Exploratory synthesis in novel chemical spaces is the essence of solid-state chemistry. However, uncharted chemical spaces can be difficult to navigate, especially when materials synthesis is challenging. Nitrides represent one such space,…

Since the discovery of copper oxide superconductor in 1986 [1], extensive efforts have been devoted to the search of new high-Tc superconducting materials, especially high-Tc systems other than cuprates. The recently discovered quaternary…

Superconductivity · Physics 2008-09-19 Zhi-An Ren , Jie Yang , Wei Lu , Wei Yi , Guang-Can Che , Xiao-Li Dong , Li-Ling Sun , Zhong-Xian Zhao

It has been shown that oxide ceramics containing multiple transition and/or rare-earth elements in equimolar ratios have a strong tendency to crystallize in simple single phase structures, stabilized by the high configurational entropy. In…

Materials Science · Physics 2019-03-27 Ralf Witte , Abhishek Sarkar , Robert Kruk , Benedikt Eggert , Richard A. Brand , Heiko Wende , Horst Hahn

Transparent conducting oxides (TCOs) play an essential role in modern optoelectronic devices through their combination of electrical conductivity and optical transparency. We review recent progress in our understanding of multi-component…

Materials Science · Physics 2013-09-18 Aron Walsh , Juarez L. F. Da Silva , Su-Huai Wei

Novel wide-band-gap semiconductors are needed for next-generation power electronic but there is a gap between a promising material and a functional device. Finding stable contacts is one of the major challenges, which is currently dealt…

Materials Science · Physics 2023-12-20 Cheng-Wei Lee , Andriy Zakutayev , Vladan Stevanović

The discovery of novel quantum materials within ternary phase spaces containing antagonistic pair such as Fe with Bi, Pb, In, and Ag, presents significant challenges yet holds great potential. In this work, we investigate the stabilization…

MAB phases (MABs) are atomically-thin laminates of ceramic/metallic-like layers, having made a breakthrough in the development of 2D materials. Though theoretically offering a vast chemical and phase space, relatively few MABs have yet been…

Materials Science · Physics 2024-06-21 Nikola Koutná , Lars Hultman , Paul H. Mayrhofer , Davide G. Sangiovanni

The discovery of novel high-temperature superconductor materials holds transformative potential for a wide array of technological applications. However, the combinatorially vast chemical and configurational search space poses a significant…

Superconductivity · Physics 2025-02-25 Xiaoyang Wang , Chengqian Zhang , Zhenyu Wang , Hanyu Liu , Jian Lv , Han Wang , Weinan E , Yanming Ma