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Most technologically useful materials spanning multiple length scales are polycrystalline. Polycrystalline microstructures are composed of a myriad of small crystals or grains with different lattice orientations which are separated by…

Analysis of PDEs · Mathematics 2026-05-13 Batuhan Bayir , Yekaterina Epshteyn , William M Feldman

We present a detailed analysis of the universal relationship between grain boundary (GB) free energy and GB self-diffusion coefficient derived by Borisov et al. (1964). This relationship was expressed by a simple equation that was used in…

Materials Science · Physics 2026-03-31 Yuri Mishin

High energy x-ray diffraction microscopy was used to image the microstructure of $\alpha$-Fe before and after a 600 $^\circ$C anneal. These data were used to determine the areas, curvatures, energies, and velocities of approximately 40,000…

Nanocrystalline (NC) materials are intrinsically unstable against grain growth. Significant research efforts have been dedicated to suppressing the grain growth by solute segregation, including the pursuit of a special NC structure that…

Materials Science · Physics 2024-12-09 Omar Hussein , Yuri Mishin

The gradient crystal plasticity framework of Wulfinghoff et al. [53] incorporating an equivalent plastic strain and grain boundary yielding, is extended with additional grain boundary hardening. By comparison to averaged results from many…

Computational Physics · Physics 2015-12-18 E. Bayerschen , M. Stricker , S. Wulfinghoff , D. Weygand , T. Böhlke

Understanding hydrogen-grain boundary (GB) interactions is critical to the analysis of hydrogen embrittlement in metals. This work presents a mesoscale fully kinetic model to investigate the effect of GB misorientation on hydrogen diffusion…

Materials Science · Physics 2024-12-31 Abdelrahman Hussein , Byungki Kim , Kim Verbeken , Tom Depover

One of the major challenges towards understanding and further utilizing the properties and functional behaviors of grain boundaries (GB) is the complexity of general GBs with mixed tilt and twist characters. Here, we report the correlations…

Materials Science · Physics 2024-09-04 Wei Wan , Changxin Tang , Eric R. Homer

We develop a polycrystal graph neural network (PGNN) model for predicting the effective properties of polycrystalline materials, using the Li7La3Zr2O12 ceramic as an example. A large-scale dataset with >5000 different three-dimensional…

Materials Science · Physics 2023-06-09 Minyi Dai , Mehmet F. Demirel , Xuanhan Liu , Yingyu Liang , Jia-Mian Hu

Grain growth is a ubiquitous and fundamental phenomenon observed in the cellular structures with the grain assembly separated by a network of grain boundaries, including metals and ceramics. However, the underlying mechanism of grain growth…

Materials Science · Physics 2021-02-18 Jianfeng Hu , Xianhao Wang , Junzhan Zhang , Zhijian Shen , Jun Luo , Jian Luo

Orientation effects on the resistivity of copper grain boundaries are studied systematically with two different atomistic tight binding methods. A methodology is developed to model the resistivity of grain boundaries using the Embedded Atom…

Grain Growth strongly influences the mechanical behavior of materials, making its prediction a key objective in microstructural engineering. In this study, several deep learning approaches were evaluated, including recurrent neural networks…

Machine Learning · Computer Science 2025-11-18 Eliane Younes , Elie Hachem , Marc Bernacki

A threshold dynamics model of grain growth that accounts for the anisotropy in the grain boundary energy has been used to simulate experimentally observed grain growth of polycrystalline Ni. The simulation reproduces several aspects of the…

Grain growth simulation is crucial for predicting metallic material microstructure evolution during annealing and resulting final mechanical properties, but traditional partial differential equation-based methods are computationally…

Materials Science · Physics 2025-05-09 Pungponhavoan Tep , Marc Bernacki

Effective properties of materials with random heterogeneous structures are typically determined by homogenising the mechanical quantity of interest in a window of observation. The entire problem setting encompasses the solution of a local…

Numerical Analysis · Mathematics 2021-10-22 Felipe Rocha , Simone Deparis , Pablo Antolin , Annalisa Buffa

In light of the race towards macroscale superlubricity of graphitic contacts, the effect of grain boundaries on their frictional properties becomes of central importance. Here, we elucidate the unique frictional mechanisms characterizing…

Mesoscale and Nanoscale Physics · Physics 2020-08-04 Xiang Gao , Wengen Ouyang , Oded Hod , Michael Urbakh

We investigate the influence of grain boundaries (GBs), line defects (LDs), and chirality on thermal transport in graphene using non-equilibrium Green's functions. At room temperature the ballistic thermal conductance is ~4.2 GW/m^2/K, and…

Materials Science · Physics 2013-02-22 Andrey Y. Serov , Zhun-Yong Ong , Eric Pop

A formula of grain growth rate, based on a nonlinear capillarity-driven relation, is derived to predict and interpret realistic growth processes in polycrystalline systems. The derived formula reveals how the growth and stagnation of grains…

Materials Science · Physics 2017-12-12 Jianfeng Hu , Xianhao Wang

A new method for estimation of intragranular strain fields in polycrystalline materials based on scanning three-dimensional X-ray diffraction data (scanning-3DXRD) is presented and evaluated. Given an apriori known anisotropic compliance,…

Materials Science · Physics 2021-06-16 Axel Henningsson , Johannes Hendriks

We design, fabricate and test heterogeneous architected polycrystals, composed of hard plastomers and soft elastomers, which thus show outstanding mechanical resilience and energy dissipation simultaneously. Grain boundaries that separate…

Soft Condensed Matter · Physics 2025-04-15 Seunghwan Lee , Hansohl Cho

Grain boundaries are commonly observed in carbon nanostructures, but their influence on thermal and electric properties are still not completely understood. Using a combined approach of density functional tight-binding theory and…

Materials Science · Physics 2015-06-30 Thomas Lehmann , Dmitry A. Ryndyk , Gianaurelio Cuniberti
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