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This study proposes algorithms for building tilt grain boundary (GB) models with a boundary plane-oriented approach that does not rely on existence of a coincidence site lattice (CSL). As conventional GB model generation uses the CSL of…

Materials Science · Physics 2023-05-02 Yoyo Hinuma , Masanori Kohyama , Shingo Tanaka

Crystalline interfaces are of highly importance in many practical applications. To conduct effective simulation and analysis for coincident site lattice (CSL) interfaces, effective programmes are of high demand in building their CSL…

Materials Science · Physics 2022-11-29 Yaoshu Xie , Kiyou Shibata , Teruyasu Mizoguchi

When modeling microstructures, the computational resource requirements increase rapidly as the simulation domain becomes larger. As a result, simulating a small representative fraction under periodic boundary conditions is often a necessary…

In this work, we present a theoretical method to predict all coincidence site lattice (CSL) tilt grain boundaries (GBs) in A15, especially high-$\Sigma$ CSL GBs. This method includes a modified Farey diagram (MFD) and a computational…

Materials Science · Physics 2025-06-30 Wenwen Zou , Zihan Su , Juan Zhang , Kai Jiang

A computer algorithm to search symmetries of crystal structures as implemented in the \texttt{spglib} code is described. An iterative algorithm is employed to robustly identify space group types tolerating a certain amount of distortion in…

Materials Science · Physics 2024-03-14 Atsushi Togo , Kohei Shinohara , Isao Tanaka

The structure and energy of grain boundaries (GBs) are essential for predicting the properties of polycrystalline materials. In this work, we use high-throughput density functional theory calculations workflow to construct the Grain…

We describe the \texttt{Imeall} package for the calculation and indexing of atomistic properties of grain boundaries in materials. The package provides a structured database for the storage of atomistic structures and their associated…

Materials Science · Physics 2018-08-15 Henry Lambert , Adam Fekete , James R Kermode , A. De Vita

We propose a systematic method to construct crystal-based molecular structures often needed as input for computational chemistry studies. These structures include crystal ``slabs" with periodic boundary conditions (PBCs) and non-periodic…

Grain Boundaries govern many properties of polycrystalline materials, including the vast majority of engineering materials. Evolutionary algorithm can be applied to predict the grain boundary structures in different systems. However, the…

Materials Science · Physics 2017-10-04 Bingxi Li

The study of grain boundary phase transitions is an emerging field until recently dominated by experiments. The major bottleneck in exploration of this phenomenon with atomistic modeling has been the lack of a robust computational tool that…

Materials Science · Physics 2018-02-21 Qiang Zhu , Amit Samanta , Bingxi Li , Robert E. Rudd , Timofey Frolov

We present a systematic methodology, built within the Open Knowledgebase of Interatomic Models (OpenKIM) framework (https://openkim.org), for quantifying properties of grain boundaries (GBs) for arbitrary interatomic potentials (IPs), GB…

The yaglm package aims to make the broader ecosystem of modern generalized linear models accessible to data analysts and researchers. This ecosystem encompasses a range of loss functions (e.g. linear, logistic, quantile regression),…

Computation · Statistics 2021-10-13 Iain Carmichael , Thomas Keefe , Naomi Giertych , Jonathan P Williams

Simulation-driven development of intelligent machines benefits from artificial terrains with controllable, well-defined characteristics. However, most existing tools for terrain generation focus on artist-driven workflows and visual…

Computational Engineering, Finance, and Science · Computer Science 2025-06-25 Erik Wallin

Temporally indexed data are essential in a wide range of fields and of interest to machine learning researchers. Time series data, however, are often scarce or highly sensitive, which precludes the sharing of data between researchers and…

Machine Learning · Computer Science 2024-07-10 Alexander Nikitin , Letizia Iannucci , Samuel Kaski

The topological transitions that occur to the grain boundary network during grain growth in a material with uniform grain boundary energies are believed to be known. The same is not true for more realistic materials, since more general…

Materials Science · Physics 2021-10-29 Erdem Eren , Jeremy K. Mason

Graph neural networks are widely used in machine learning applied to chemistry, and in particular for material science discovery. For crystalline materials, however, generating graph-based representation from geometrical information for…

Materials Science · Physics 2023-07-12 Astrid Klipfel , Yaël Frégier , Adlane Sayede , Zied Bouraoui

We introduce pyGSL, a Python library that provides efficient implementations of state-of-the-art graph structure learning models along with diverse datasets to evaluate them on. The implementations are written in GPU-friendly ways, allowing…

Machine Learning · Computer Science 2022-11-08 Max Wasserman , Gonzalo Mateos

Coincidence Site Lattices (CSLs) are a well established tool in the theory of grain boundaries. For several lattices up to dimension $d=4$, the CSLs are known explicitly as well as their indices and multiplicity functions. Many of them…

Metric Geometry · Mathematics 2012-12-20 Peter Zeiner

With the increasing availability of experimental and computational data concerning the properties and distribution of grain boundaries in polycrystalline materials, there is a corresponding need to efficiently and systematically express…

Materials Science · Physics 2019-09-27 Jeremy K. Mason , Srikanth Patala

The complex arrangements of atoms near grain boundaries are difficult to understand theoretically. We propose a phenomenological (Ginzburg-Landau-like) description of crystalline phases based on symmetries and fairly general stability…

Materials Science · Physics 2015-06-25 Denis Boyer , David Romeu
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