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Multipole symmetries are of interest in multiple contexts, from the study of fracton phases, to nonergodic quantum dynamics, to the exploration of new hydrodynamic universality classes. However, prior explorations have focused on continuum…

Strongly Correlated Electrons · Physics 2023-12-13 Daniel Bulmash , Oliver Hart , Rahul Nandkishore

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

Generative models for materials, especially inorganic crystals, hold potential to transform the theoretical prediction of novel compounds and structures. Advancement in this field depends on robust benchmarks and minimal, information-rich…

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…

The Voronoi cell of any atom in a lattice is identical. If atoms are perturbed from their lattice coordinates, then the topologies of the Voronoi cells of the atoms will change. We consider the distribution of Voronoi cell topologies in…

Statistical Mechanics · Physics 2016-06-10 Hannes Leipold , Emanuel A. Lazar , Kenneth A. Brakke , David J. Srolovitz

Mathematical crystal chemistry views crystal structures as the optimal solutions of mathematical optimization problem formalizing inorganic structural chemistry. This paper introduces the minimum and maximum atomic radii depending on the…

Materials Science · Physics 2025-04-01 Ryotaro Koshoji

New crystal structures are frequently derived by performing ionic substitutions on known crystal structures. These derived structures are then used in further experimental analysis, or as the initial guess for structural optimization in…

Materials Science · Physics 2018-02-23 Iek-Heng Chu , Sayan Roychowdhury , Daehui Han , Anubhav Jain , Shyue Ping Ong

An algorithm for determining crystal structures from diffraction data is described which does not rely on the usual Fourier-space formulations of atomicity. The new algorithm implements atomicity constraints in real-space, as well as…

Condensed Matter · Physics 2007-05-23 Veit Elser

The statistical shape analysis called Procrustes analysis minimizes the distance between matrices by similarity transformations. The method returns a set of optimal orthogonal matrices, which project each matrix into a common space. This…

Applications · Statistics 2023-01-18 Angela Andreella , Riccardo De Santis , Anna Vesely , Livio Finos

The pair correlation function (PCF) has proven an effective tool for analyzing many physical systems due to its simplicity and its applicability to simulated and experimental data. However, as an averaged quantity, the PCF can fail to…

Disordered Systems and Neural Networks · Physics 2023-12-14 Vasco M. Worlitzer , Gil Ariel , Emanuel A. Lazar

Two-dimensional lead halide perovskites are promising materials for optoelectronics due to the tunability of their properties with the number of lead halide layers and the choice of an organic spacer. Physical understanding for the rational…

Voronoi Tessellations form an attractive and versatile geometrical asymptotic model for the foamlike cosmic distribution of matter and galaxies. In the Voronoi model the vertices are identified with clusters of galaxies. For a substantial…

Astrophysics · Physics 2007-05-23 Rien van de Weygaert

We introduce a computational method to discover polymorphs in molecular crystals at finite temperature. The method is based on reproducing the crystallization process starting from the liquid and letting the system discover the relevant…

Chemical Physics · Physics 2020-04-10 Pablo M. Piaggi , Michele Parrinello

This paper introduces a new approach toward characterizing local structural features of two-dimensional particle systems. The approach can accurately identify and characterize defects in high-temperature crystals, distinguish a wide range…

Materials Science · Physics 2024-11-14 Emanuel A. Lazar , Jiayin Lu , Chris H. Rycroft , Deborah Schwarcz

Crystal structure prediction (CSP) for inorganic materials is one of the central and most challenging problems in materials science and computational chemistry. This problem can be formulated as a global optimization problem in which global…

Materials Science · Physics 2021-01-27 Jianjun Hu , Wenhui Yang , Edirisuriya M. Dilanga Siriwardane

Crystal structure predictions based on the combination of first-principles calculations and machine learning have achieved significant success in materials science. However, most of these approaches are limited to predicting specific…

Materials Science · Physics 2025-01-28 Zongguo Wang , Ziyi Chen , Yang Yuan , Yangang Wang

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…

In complex crystals close to melting or at finite temperatures, different types of defects are ubiquitous and their role becomes relevant in the mechanical response of these solids. Conventional elasticity theory fails to provide a…

Despite an artificial intelligence-assisted modeling of disordered crystals is a widely used and well-tried method of new materials design, the issues of its robustness, reliability, and stability are still not resolved and even not…

Computational Physics · Physics 2024-11-08 Fedor S. Avilov , Roman A. Eremin , Semen A. Budennyy , Innokentiy S. Humonen

The ionic bonding across the lattice and ordered microscopic structures endow crystals with unique symmetry and determine their macroscopic properties. Unconventional crystals, in particular, exhibit non-traditional lattice structures or…

Materials Science · Physics 2024-11-04 Hongyi Wang , Ji Sun , Jinzhe Liang , Li Zhai , Zitian Tang , Zijian Li , Wei Zhai , Xusheng Wang , Weihao Gao , Sheng Gong