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Fast and accurate crystal structure prediction (CSP) algorithms and web servers are highly desirable for exploring and discovering new materials out of the infinite design space. However, currently, the computationally expensive first…

Evolutionary crystal structure prediction proved to be a powerful approach for studying a wide range of materials. Here, we present a specifically designed algorithm for the prediction of the structure of complex crystals consisting of…

Materials Science · Physics 2012-05-21 Qiang Zhu , Artem R. Oganov , Colin W. Glass , Harold T. Stokes

At high pressure, the typical behavior of elements dictated by the periodic table - including oxidation numbers, stoichiometries in compounds, and reactivity, to name but a few - is altered dramatically. As pressure is applied, the…

Materials Science · Physics 2022-05-11 Katerina P. Hilleke , Tiange Bi , Eva Zurek

Crystal structure prediction remains a major challenge in materials science, directly impacting the discovery and development of next-generation materials. We introduce TCSP 2.0, a substantial evolution of our template-based crystal…

Materials Science · Physics 2025-04-01 Lai Wei , Rongzhi Dong , Nihang Fu , Sadman Sadeed Omee , Jianjun Hu

Hex-dominant mesh generation has received significant attention in recent research due to its superior robustness compared to pure hex-mesh generation techniques. In this work, we introduce the first structure for analyzing hex-dominant…

Graphics · Computer Science 2024-03-04 Lei Si , Haowei Cao , Guoning Chen

High-entropy materials have attracted considerable interest due to the combination of useful properties and promising applications. Predicting their formation remains the major hindrance to the discovery of new systems. Here we propose a…

High-entropy alloys (HEAs) have attracted growing attention for their exceptional mechanical and thermal properties arising from complex atomic configurations. In this paper, we propose crystal fractional graph neural network for predicting…

Computational Physics · Physics 2026-05-12 Takanori Kotama , Yang Huang

Lithium (Li) is a prototypical simple metal at ambient conditions, but exhibits remarkable changes in structural and electronic properties under compression. There has been intense debate about the structure of dense Li, and recent…

Materials Science · Physics 2023-06-21 Xiaoyang Wang , Zhenyu Wang , Pengyue Gao , Chengqian Zhang , Jian Lv , Han Wang , Haifeng Liu , Yanchao Wang , Yanming Ma

Diffraction is the most common method to solve for unknown or partially known crystal structures. However, it remains a challenge to determine the crystal structure of a new material that may have nanoscale size or heterogeneities. Here we…

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

The practically unlimited high-dimensional composition space of high-entropy materials (HEMs) has emerged as an exciting platform for functional materials design and discovery. However, the identification of stable and synthesizable HEMs…

Materials Science · Physics 2024-03-01 Dibyendu Dey , Liangbo Liang , Liping Yu

Galactic globular clusters (GCs) were born shortly after the Big Bang. For such old stellar systems the initial mass function (IMF) at the high mass regime can never be observed directly, because stars more massive than about 1 Mo have…

Solar and Stellar Astrophysics · Physics 2026-03-25 Eugenio Carretta

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

High energy density is always a key goal for developments of energy storage or energetic materials (EMs). Except exploring novel EMs with high chemical energy, it is also desirable if the traditional EMs could be assembled at a higher…

High entropy oxides (HEOs) are a rapidly emerging class of functional materials consisting of multiple principal cations. The original paradigm of HEOs assumes cationic occupations with the highest possible configurational entropy allowed…

Evolutionary algorithms and the particle swarm optimization method have been used to predict stable and metastable high hydrides of iron between 150-300 GPa that have not been discussed in previous studies. Cmca FeH5, Pmma FeH6 and P2/c…

Superconductivity · Physics 2018-10-31 Niloofar Zarifi , Tiange Bi , Hanyu Liu , Eva Zurek

Geometric information such as the space groups and crystal systems plays an important role in the properties of crystal materials. Prediction of crystal system and space group thus has wide applications in crystal material property…

Materials Science · Physics 2021-05-18 Yuxin Li , Rongzhi Dong , Wenhui Yang , Jianjun Hu

Solid-state electrolyte batteries are expected to replace liquid electrolyte lithium-ion batteries in the near future thanks to their higher theoretical energy density and improved safety. However, their adoption is currently hindered by…

Crystal Structure Prediction (CSP) remains a fundamental challenge with significant implications for the development of new materials and the advancement of various scientific disciplines. Recent developments have shown that generative…

Computational Engineering, Finance, and Science · Computer Science 2025-09-01 Yang Liu , Chuan Zhou , Shuai Zhang , Peng Zhang , Xixun Lin , Shirui Pan

A novel stable crystallographic structure is discovered in a variety of ABO3, ABF3 and A2O3 compounds (including materials of geological relevance, prototypes of multiferroics, exhibiting strong spin-orbit effects, etc...), via the use of…

Materials Science · Physics 2015-01-20 Changsong Xu , Bin Xu , Yurong Yang , Huafeng Dong , A. R. Oganov , Shanying Wang , Wenhui Duan , Binglin Gu , L. Bellaiche