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Crystal structures define how matter is organized at the atomic level. In the realm of crystalline inorganic materials, new structure types are rarely found, and most experimentally-realized structural motifs were established decades ago.…

In the electronic packaging and energy storage sectors, the study of Cu6Sn5 intermetallic compound (IMC) is getting more attention. At temperatures above 186 oC, this IMC exists in a hexagonal closed packed (HCP) crystalline structure.…

Materials Science · Physics 2023-05-31 Anil Kunwar , Haoran Ma , Johan Hektor

The application of generative models in crystal structure prediction (CSP) has gained significant attention. Conditional generation--particularly the generation of crystal structures with specified stability or other physical properties has…

Materials Science · Physics 2026-01-14 Takanori Ishii , Kaoru Hisama , Kohei Shinohara

Powder X-ray diffraction (PXRD) is a prevalent technique in materials characterization. While the analysis of PXRD often requires extensive human manual intervention, and most automated method only achieved at coarse-grained level. The more…

Chemical Physics · Physics 2025-02-11 Qingsi Lai , Fanjie Xu , Lin Yao , Zhifeng Gao , Siyuan Liu , Hongshuai Wang , Shuqi Lu , Di He , Liwei Wang , Cheng Wang , Guolin Ke

This paper introduces a new structural phase field crystal (PFC) type model that expands the PFC methodology to a wider class of structurally complex crystal structures than previously possible. Specifically, our new approach allows for…

Materials Science · Physics 2016-02-03 Matthew Seymour , Nikolas Provatas

We present a new numerical scheme to study systems of non-convex, irregular, and punctured particles in an efficient manner. We employ this method to analyze regular packings of odd-shaped bodies, not only from a nanoparticle but also both…

Soft Condensed Matter · Physics 2015-05-28 Joost de Graaf , René van Roij , Marjolein Dijkstra

Hafnium carbides are studied by a systematic search for possible stable stoichiometric compounds in the Hf-C system at ambient pressure using variable-composition ab initio evolutionary algorithm implemented in the USPEX code. In addition…

The exploration of solid-solid phase transition suffers from the uncertainty of how atoms in two crystal structures match. We devised a theoretical framework to describe and classify crystal-structure matches (CSM). Such description fully…

Materials Science · Physics 2024-02-22 Fang-Cheng Wang , Qi-Jun Ye , Yu-Cheng Zhu , Xin-Zheng Li

The discovery of novel carbon allotropes with tailored thermal and mechanical properties is critical for advanced thermal management. However, exploring the vast configurational space of carbon using \textit{ab initio} calculations remains…

Materials Science · Physics 2026-03-11 Yuzhou Hao , Yujie Liu , Xuejie Li , Turab Lookman , Xiangdong Ding , Jun Sun , Zhibin Gao

The discovery of new functional and stable materials is a big challenge due to its complexity. This work aims at the generation of new crystal structures with desired properties, such as chemical stability and specified chemical…

Computational Physics · Physics 2023-10-18 Arsen Sultanov , Jean-Claude Crivello , Tabea Rebafka , Nataliya Sokolovska

The behavior of identical particles interacting through the harmonic-repulsive pair potential has been studied in 3D using molecular dynamics simulations at a number of different densities. We found that at many densities, as the…

Soft Condensed Matter · Physics 2017-10-11 V. A. Levashov

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

Finding an optimal match between two different crystal structures underpins many important materials science problems, including describing solid-solid phase transitions, developing models for interface and grain boundary structures. In…

Materials Science · Physics 2020-02-21 Félix Therrien , Peter Graf , Vladan Stevanović

Crystallization processes at the mesoscopic scale, where faceted, dendritic growth, and multigrain formation can be observed, are of particular interest within materials science and metallurgy. These processes are highly nonlinear,…

Machine Learning · Computer Science 2024-05-28 Pol Timmer , Koen Minartz , Vlado Menkovski

Machine learning models have recently emerged to predict whether hypothetical solid-state materials can be synthesized. These models aim to circumvent direct first-principles modeling of solid-state phase transformations, instead learning…

Materials Science · Physics 2026-02-05 Jane Schlesinger , Simon Hjaltason , Nathan J. Szymanski , Christopher J. Bartel

We propose theoretical approach based on combination of graph theory and generalized Ising model (GIM), which enables systematic determination of extremal structures for crystalline solids without any information about interactions or…

Disordered Systems and Neural Networks · Physics 2017-01-13 Koretaka Yuge

Crystal structure design is important for the discovery of new highly functional materials because crystal structure strongly influences material properties. Crystal structures are composed of space-filling polyhedra, which affect material…

Materials Science · Physics 2024-02-06 Tomoyasu Yokoyama , Kazuhide Ichikawa , Hisashi Naito

Successful scientific applications of large-scale molecular dynamics often rely on automated methods for identifying the local crystalline structure of condensed phases. Many existing methods for structural identification, such as Common…

Materials Science · Physics 2016-05-24 Peter Mahler Larsen , Søren Schmidt , Jakob Schiøtz

The phase diagram of model anisotropic particles with four attractive patches in a tetrahedral arrangement has been computed at two different values for the range of the potential, with the aim of investigating the conditions under which a…

Materials Science · Physics 2013-06-26 Eva G. Noya , Carlos Vega , Jonathan P. K. Doye , Ard A. Louis

Materials property predictions have improved from advances in machine learning algorithms, delivering materials discoveries and novel insights through data-driven models of structure-property relationships. Nearly all available models rely…

Materials Science · Physics 2022-04-13 Yiqun Wang , Xiao-Jie Zhang , Fei Xia , Elsa A. Olivetti , Ram Seshadri , James M. Rondinelli