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Automated Meshing of Evolving Microstructures from High-Throughput Grain Growth Simulations
Phase-field modeling of grain evolutions in additive manufacturing from nucleation, growth, to coarsening | npj Computational Materials
Modeling material variability with uncertainty quantification and machine learning techniques
EGQSJ - Grain-size distribution unmixing using the R package EMMAgeo
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Grain size analysis in permanent magnets from Kerr microscopy images using machine learning techniques - ScienceDirect
Modeling length scale effects on strain induced grain boundary migration via bridging phase field and crystal plasticity methods - ScienceDirect
Accelerating phase-field-based microstructure evolution predictions via surrogate models trained by machine learning methods | npj Computational Materials
Machine learning coarse grained models for water | Nature Communications
EGQSJ - Grain-size distribution unmixing using the R package EMMAgeo
Phase-Field Simulation of Grain Boundary Evolution In Microstructures Containing Second-Phase Particles with Heterogeneous Thermal Properties | Scientific Reports
Discrete and continuum modelling of grain size segregation during bedload transport | Journal of Fluid Mechanics | Cambridge Core
Phase-field modeling of grain evolutions in additive manufacturing from nucleation, growth, to coarsening | npj Computational Materials
Ultra-Coarse-Grained Models Allow for an Accurate and Transferable Treatment of Interfacial Systems | Journal of Chemical Theory and Computation
Grain-size distribution unmixing using the R package EMMAgeo - EGQSJ
Finite element model of the RVE of wrought polycrystalline IN718 alloy.... | Download Scientific Diagram
Coarse-Grained Atomistics – Mechanics and Materials Laboratory | ETH Zurich
Step-by-Step Guide for Grain Size Analysis | Geoengineer.org
Mathematical modeling and multivariate analysis applied earliest soybean harvest associated drying and storage conditions and influences on physicochemical grain quality | Scientific Reports
Physics-driven coarse-grained model for biomolecular phase separation with near-quantitative accuracy | Nature Computational Science
