Accelerating phase-field-based microstructure evolution predictions via surrogate models trained by machine learning methods

D Montes de Oca Zapiain, JA Stewart… - npj Computational …, 2021 - nature.com
The phase-field method is a powerful and versatile computational approach for modeling the
evolution of microstructures and associated properties for a wide variety of physical …

Viewpoint on the formation and evolution of annealing twins during thermomechanical processing of FCC metals and alloys

N Bozzolo, M Bernacki - Metallurgical and Materials Transactions A, 2020 - Springer
The question of the formation mechanism of annealing twins in face-centered cubic metals
and alloys, which is still not resolved in spite of the fact that the existence of these defects is …

A review of 3D-printed bimetallic alloys

MJ Shekh, LC Yeo, JL Bair - The International Journal of Advanced …, 2024 - Springer
This paper provides a critical overview of experimental and computational studies
conducted on additive manufacturing (AM) or 3D printing using bimetallic alloys. The review …

Ultra-large-scale phase-field simulation study of ideal grain growth

E Miyoshi, T Takaki, M Ohno, Y Shibuta… - NPJ Computational …, 2017 - nature.com
Grain growth, a competitive growth of crystal grains accompanied by curvature-driven
boundary migration, is one of the most fundamental phenomena in the context of metallurgy …

Influence of grain boundary energy anisotropy on the evolution of grain boundary network structure during 3D anisotropic grain growth

JD Niño, OK Johnson - Computational Materials Science, 2023 - Elsevier
In this paper, we present the results of grain growth simulations in three-dimensions using
an existing level set method. Most of the previous grain growth studies have been either …

Accelerating microstructure modeling via machine learning: A method combining autoencoder and convlstm

O Ahmad, N Kumar, R Mukherjee, S Bhowmick - Physical Review Materials, 2023 - APS
Phase-field modeling is an elegant and versatile computation tool to predict microstructure
evolution in materials in the mesoscale regime. However, these simulations require rigorous …

Phase-field model for anisotropic grain growth

P Staublin, A Mukherjee, JA Warren, PW Voorhees - Acta Materialia, 2022 - Elsevier
Grain boundary properties may depend on the five macroscopic crystallographic degrees of
freedom of the boundary, these being the misorientation between crystals and the inclination …

GrainNN: A neighbor-aware long short-term memory network for predicting microstructure evolution during polycrystalline grain formation

Y Qin, S DeWitt, B Radhakrishnan, G Biros - Computational Materials …, 2023 - Elsevier
High fidelity simulations of grain formation in alloys are an indispensable tool for process-to-
mechanical-properties characterization. Such simulations, however, can be computationally …

Large-scale phase-field study of anisotropic grain growth: Effects of misorientation-dependent grain boundary energy and mobility

E Miyoshi, T Takaki, S Sakane, M Ohno… - Computational Materials …, 2021 - Elsevier
Three-dimensional grain growth behaviors under anisotropic (misorientation-dependent)
grain boundary energy and mobility are investigated via phase-field simulations. Based on a …

Evolution of crystallographic texture and grain boundary network structure during anisotropic grain growth

J Niño, OK Johnson - Computational Materials Science, 2024 - Elsevier
In this paper, we present the results of 426 anisotropic grain growth simulations in two-
dimensions using a diverse set of initial microstructures. We consider anisotropy by using a …