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Despite being forbidden in equilibrium, spontaneous breaking of time translation symmetry can occur in periodically driven, Floquet systems with discrete time-translation symmetry. The period of the resulting discrete time crystal is…

Disordered Systems and Neural Networks · Physics 2017-06-21 Norman Y. Yao , Andrew C. Potter , Ionut-Dragos Potirniche , Ashvin Vishwanath

A fundamental challenge in materials design is linking building block attributes to crystal structure. Addressing this challenge is particularly difficult for systems that exhibit emergent order, such as entropy-stabilized colloidal…

Materials Science · Physics 2018-01-22 Yina Geng , Greg van Anders , Sharon C. Glotzer

The atomic displacements associated with the freezing of metals and salts are calculated by treating crystal growth as an assignment problem through the use of an optimal transport algorithm. Converting these displacements into time scales…

Materials Science · Physics 2022-06-08 Gang Sun , Alexander Hawken , Peter Harrowell

We extend the phase field crystal method for nonequilibrium patterning to stochastic systems with external source where transient dynamics is essential. It was shown that at short time scales the system manifests pattern selection…

Statistical Mechanics · Physics 2011-01-18 D. Kharchenko , V. Kharchenko , I. Lysenko

Time crystals, a phase showing spontaneous breaking of time-translation symmetry, has been an intriguing subject for systems far away from equilibrium. Recent experiments found such a phase both in the presence and absence of localization,…

Quantum Gases · Physics 2018-03-21 Biao Huang , Ying-Hai Wu , W. Vincent Liu

Crystal structure prediction has been a subject of topical interest, but remains a substantial challenge, especially for complex structures as it deals with the global minimization of the extremely rugged high-dimensional potential energy…

Materials Science · Physics 2022-01-26 Xuecheng Shao , Jian Lv , Peng Liu , Sen Shao , Pengyue Gao , Hanyu Liu , Yanchao Wang , Yanming Ma

Crystal structure prediction (CSP), which aims to predict the three-dimensional atomic arrangement of a crystal from its composition, is central to materials discovery and mechanistic understanding. However, given the composition in a unit…

Materials Science · Physics 2026-03-10 Shi Yin , Jinming Mu , Xudong Zhu , Linxin He

Recently, it was shown that a theoretical description of nucleation based on fluctuating hydrodynamics and classical density functional theory can be used to determine non-classical nucleation pathways for crystallization (Lutsko, Sci. Adv.…

Chemical Physics · Physics 2024-06-26 James F. Lutsko , Cédric Schoonen

The ability to control forces between sub-micron-scale building blocks offers considerable potential for designing new materials through self-assembly. A typical paradigm is to first identify a particular (crystal) structure that has some…

Soft Condensed Matter · Physics 2024-04-24 Mengjie Zu , Carl Goodrich

We introduce CrystalFormer, a transformer-based autoregressive model specifically designed for space group-controlled generation of crystalline materials. By explicitly incorporating space group symmetry, CrystalFormer greatly reduces the…

Materials Science · Physics 2025-09-29 Zhendong Cao , Xiaoshan Luo , Jian Lv , Lei Wang

Diffraction methods are at the heart of structure determination of solids. While Bragg-like scattering (pure point diffraction) is a characteristic feature of crystals and quasicrystals, it is not straightforward to interpret continuous…

Mathematical Physics · Physics 2009-06-26 Michael Baake , Uwe Grimm

The crystalline solids with lack of orientational ordering of anisotropic particles serve the purpose of studying the disordered systems with many fundamental applications in contemporary research. Despite the orientational disorder,…

Soft Condensed Matter · Physics 2024-11-01 Sumitava Kundu , Kaustav Chakraborty , Avisek Das

We consider several patchy particle models that have been proposed in literature and we investigate their candidate crystal structures in a systematic way. We compare two different algorithms for predicting crystal structures: (i) an…

Computational Physics · Physics 2015-06-05 Emanuela Bianchi , Guenther Doppelbauer , Laura Filion , Marjolein Dijkstra , Gerhard Kahl

We propose an efficient algorithm to analyze $3D$ atomic resolution crystal images based on a fast $3D$ synchrosqueezed wave packet transform. The proposed algorithm can automatically extract microscopic information from $3D$ atomic…

Numerical Analysis · Mathematics 2018-11-14 Tao Zhang , Ling Li , Haizhao Yang

Crystal structures are characterised by repeating atomic patterns within unit cells across three-dimensional space, posing unique challenges for graph-based representation learning. Current methods often overlook essential periodic boundary…

The local structure study reveals important aspects of the physical properties, because it is closely related to the electronic structure. Standard crystallographic analysis based on a space group fails to observe disorder in the crystal…

Materials Science · Physics 2019-06-26 Shin-ichi Shamoto

Multi-technique high resolution X-ray mapping enhanced by the recent advent of 4th generation synchrotron facilities can produce colossal datasets, challenging traditional analysis methods. Such difficulty is clearly materialized when…

Time crystals are genuinely non-equilibrium quantum phases of matter that break time-translational symmetry. While in non-equilibrium closed systems time crystals have been experimentally realized, it remains an open question whether or not…

Quantum Physics · Physics 2020-05-27 Andreu Riera-Campeny , Maria Moreno-Cardoner , Anna Sanpera

Inorganic crystals are periodic, highly-symmetric arrangements of atoms in three-dimensional space. Their structures are constrained by the symmetry operations of a crystallographic \emph{space group} and restricted to lie in specific…

Machine Learning · Computer Science 2025-09-30 Omri Puny , Yaron Lipman , Benjamin Kurt Miller

Inspired by the recent success of machine-learned interatomic potentials for crystal structure prediction of the inorganic crystals, we present a methodology that exploits Moment Tensor Potentials and active learning (based on maxvol…

Materials Science · Physics 2024-10-07 Nikita Rybin , Ivan S. Novikov , Alexander Shapeev
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