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Two finite element level-set (FE-LS) formulations are compared for the modeling of grain growth of 316L stainless steel in terms of grain size, mean values and histograms. Two kinds of microstructures are considered, some are generated…

Materials Science · Physics 2022-04-06 Brayan Murgas , Baptiste Flipon , Nathalie Bozzolo , Marc Bernacki

Understanding and controlling the properties and dynamics of topological defects is a lasting challenge in the study of two-dimensional materials, and is crucial to achieve high-quality films required for technological applications. Here…

Materials Science · Physics 2017-06-28 Doaa Taha , S. K. Mkhonta , K. R. Elder , Zhi-Feng Huang

Grain boundaries (GBs) and interfaces in polycrystalline materials are significant research subjects in the field of materials science. Despite a more than 50-year history of their study, there are still many open questions. The main…

Materials Science · Physics 2021-06-28 Arslan B. Mazitov , Artem R. Oganov

Amorphous grain boundary complexions lack long-range crystalline order but are not featureless, as distinct gradients in structural short-range order have been reported through their thickness. In this work, we test the hypothesis that the…

Materials Science · Physics 2023-09-19 Pulkit Garg , Timothy J. Rupert

Additively manufactured metals exhibit heterogeneous microstructure which dictates their material and failure properties. Experimental microstructural characterization techniques generate a large amount of data that requires expensive…

Image and Video Processing · Electrical Eng. & Systems 2021-05-10 Roberto Perera , Davide Guzzetti , Vinamra Agrawal

Atomistic simulations provide the most detailed picture of grain boundary (GB) migration currently available. Nevertheless, extracting unit mechanisms from atomistic simulation data is difficult because of the zoo of competing,…

Materials Science · Physics 2025-06-06 Ian Chesser , Brandon Runnels , Elizabeth Holm

In material science, image segmentation is of great significance for quantitative analysis of microstructures. Here, we propose a novel Weighted Propagation Convolution Neural Network based on U-Net (WPU-Net) to detect boundary in…

Computer Vision and Pattern Recognition · Computer Science 2025-07-11 Wei Liu , Jiahao Chen , Chuni Liu , Xiaojuan Ban , Boyuan Ma , Hao Wang , Weihua Xue , Yu Guo

Quantification of microstructures is crucial for understanding processing-structure and structure-property relationships in polycrystalline materials. Delineating grain boundaries in bright-field transmission electron micrographs, however,…

Grain boundaries, the two-dimensional (2D) defects between differently oriented crystals, control mechanical and transport properties of materials. Our fundamental understanding of grain boundaries is still incomplete even after nearly a…

In the literature, contradictory results have been published regarding the form of the limiting (long-time) grain size distribution (LGSD) that characterizes the late stage grain coarsening in two-dimensional and quasi-two-dimensional…

Materials Science · Physics 2017-05-24 Balint Korbuly , Tamas Pusztai , Herve Henry , Mathis Plapp , Markus Apel , Laszlo Granasy

Generative models, such as Generative Adversarial Networks (GANs), have been used for unsupervised anomaly detection. While performance keeps improving, several limitations exist particularly attributed to difficulties at capturing…

Machine Learning · Computer Science 2022-02-03 Nikolaos Dionelis , Mehrdad Yaghoobi , Sotirios A. Tsaftaris

Systematic microstructure design requires reliable thermodynamic descriptions of each and all microstructure elements. While such descriptions are well established for most bulk phases, thermodynamic assessment of crystal defects is…

Materials Science · Physics 2021-07-02 Reza Darvishi Kamachali

Convolutional neural networks are increasingly being used to analyze and classify material microstructures, motivated by the possibility that they will be able to identify relevant microstructural features more efficiently and impartially…

Computational Physics · Physics 2026-01-01 Shrunal Pothagoni , Dylan Miley , Tyrus Berry , Jeremy K. Mason , Benjamin Schweinhart

Grain boundaries affect properties of polycrystalline materials. The influence of a boundary is largely determined by its energy. Grain boundary energy is often portrayed as a function of macroscopic boundary parameters representing grain…

Materials Science · Physics 2025-01-07 Adam Morawiec

We have characterized the structure of 176 different single-layer graphene grain boundaries using $>$1000 experimental HRTEM images using a semi-automated structure processing routine. We introduce a new algorithm for generating grain…

Materials Science · Physics 2015-08-04 Colin Ophus , Ashivni Shekhawat , Haider I Rasool , Alex Zettl

The grain boundary (GB) energy has a profound influence on the grain growth and properties of polycrystalline metals. Here, we show that the energy of a GB, normalized by the bulk cohesive energy, can be described purely by four geometric…

Materials Science · Physics 2022-01-31 Weike Ye , Hui Zheng , Chi Chen , Shyue Ping Ong

The thermodynamic theory of dislocation/grain boundary interaction, including dislocation pile-up against, absorption by, and transfer through the grain boundary, is developed for nonuniform plastic deformations in polycrystals. The case…

Materials Science · Physics 2022-03-14 Yinguang Piao , Khanh Chau Le

Mg alloys are promising lightweight structural materials due to their low density and excellent mechanical properties. However, their limited formability and ductility necessitate improvements in these properties, specifically through…

The space of possible grain boundary structures is vast, with 5 macroscopic, crystallographic degrees of freedom that define the character of a grain boundary. While numerous datasets of grain boundaries have examined this space in part or…

Polycrystalline materials undergoing coarsening can be represented as evolving networks of grain boundaries, whose statistical characteristics determine macroscopic materials properties. The process of formation of various statistical…

Materials Science · Physics 2015-02-23 Claudio Torres , Maria Emelianenko , Dmitry Golovaty , David Kinderlehrer , Shlomo Ta'asan