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We have developed an efficient and reliable methodology for crystal structure prediction, merging ab initio total-energy calculations and a specifically devised evolutionary algorithm. This method allows one to predict the most stable…

Materials Science · Physics 2009-11-18 A. R. Oganov , C. W. Glass

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 recently developed evolutionary algorithm USPEX proved to be a tool that enables accurate and reliable prediction of structures for a given chemical composition. Here we extend this method to predict the crystal structure of polymers by…

Materials Science · Physics 2019-01-03 Qiang Zhu , Vinit Sharma , Artem R Oganov , Rampi Ramprasad

We have developed a method for prediction of the hardest crystal structures in a given chemical system. It is based on the evolutionary algorithm USPEX (Universal Structure Prediction: Evolutionary Xtallography) and electronegativity-based…

Materials Science · Physics 2011-10-25 Andriy O. Lyakhov , Artem R. Oganov

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

This paper introduces the HEX (High-pressure Elemental Xstals) database, a complete database of the ground-state crystal structures of the first 57 elements of the periodic table, from H to La, at 0, 100, 200 and 300 GPa. HEX aims to…

Materials Science · Physics 2024-03-15 Federico Giannessi , Simone Di Cataldo , Santanu Saha , Lilia Boeri

In this letter we propose a new methodology for crystal structure prediction, which is based on the evolutionary algorithm USPEX and the machine-learning interatomic potentials actively learning on-the-fly. Our methodology allows for an…

Materials Science · Physics 2019-03-06 Evgeny V. Podryabinkin , Evgeny V. Tikhonov , Alexander V. Shapeev , Artem R. Oganov

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 prediction of material structure from chemical composition has been a long-standing challenge in natural science. Although there have been various methodological developments and successes with computer simulations, the prediction of…

Materials Science · Physics 2018-05-23 Naoto Tsujimoto , Daiki Adachi , Ryosuke Akashi , Synge Todo , Shinji Tsuneyuki

Experimentally obtained X-ray diffraction (XRD) patterns can be difficult to solve, precluding the full characterization of materials, pharmaceuticals, and geological compounds. Herein, we propose a method based upon a multi-objective…

Materials Science · Physics 2024-07-09 Stefano Racioppi , Alberto Otero De la Roza , Samad Hajinazar , Eva Zurek

We have developed a software package CALYPSO (Crystal structure AnaLYsis by Particle Swarm Optimization) to predict the energetically stable/metastable crystal structures of materials at given chemical compositions and external conditions…

Materials Science · Physics 2015-06-05 Yanchao Wang , Jian Lv , Li Zhu , Yanming Ma

High-pressure crystal structure prediction (CSP) underpins advances in condensed matter physics, planetary science, and materials discovery. Yet, most large atomistic models are trained on near-ambient, equilibrium data, leading to degraded…

Materials Science · Physics 2025-09-15 Yinan Wang , Xiaoyang Wang , Zhenyu Wang , Jing Wu , Jian Lv , Han Wang

Experimental progress finally reached the metallic solid hydrogen phase, which was predicted by Wigner and Huntington over 80 years ago. However, the different structures in the phase diagram are still been debated due to the difficulty of…

Materials Science · Physics 2022-01-03 Tom Ichibha , Yunwei Zhang , Kenta Hongo , Ryo Maezono , Fernando A. Reboredo

Crystal Structure Prediction (CSP) is crucial in various scientific disciplines. While CSP can be addressed by employing currently-prevailing generative models (e.g. diffusion models), this task encounters unique challenges owing to the…

Materials Science · Physics 2024-03-08 Rui Jiao , Wenbing Huang , Peijia Lin , Jiaqi Han , Pin Chen , Yutong Lu , Yang Liu

Metastable materials are abundant in nature and technology, showcasing remarkable properties that inspire innovative materials design. However, traditional crystal structure prediction methods, which rely solely on energetic factors to…

Materials Science · Physics 2023-11-27 Busheng Wang , Katerina P. Hilleke , Samad Hajinazar , Gilles Frapper , Eva Zurek

Crystal structure prediction with theoretical methods is particularly challenging when unit cells with many atoms need to be considered. Here we employ a symmetry-driven structure search (SYDSS) method and combine it with density functional…

Materials Science · Physics 2018-12-05 Rustin Domingos , Kareemullah M. Shaik , Burkhard Militzer

The physicochemical behavior of elements and compounds is heavily altered by high pressure. The occurrence of pressure-induced reactions and phase transitions can be revealed by crystal structure prediction approaches. In this work, we…

Materials Science · Physics 2016-03-09 Gabriele Saleh , Artem R. Oganov

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

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

Reliable and robust methods of predicting the crystal structure of a compound, based only on its chemical composition, is crucial to the study of materials and their applications. Despite considerable ongoing research efforts, crystal…

Materials Science · Physics 2017-07-26 Qi-Jun Hong , Joseph Yasi , Axel van de Walle
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