Physics-driven coarse-grained model for biomolecular phase separation with near-quantitative accuracy | Nature Computational Science
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EGQSJ - Grain-size distribution unmixing using the R package EMMAgeo
Grain size analysis in permanent magnets from Kerr microscopy images using machine learning techniques - ScienceDirect
Machine learning coarse grained models for water | Nature Communications
Molecular dynamics study of the effect of extended ingrain defects on grain growth kinetics in nanocrystalline copper | Scientific Reports
Modeling length scale effects on strain induced grain boundary migration via bridging phase field and crystal plasticity methods - ScienceDirect
Crystals | Free Full-Text | Use of the Correlation between Grain Size and Crystallographic Orientation in Crystal Plasticity Simulations: Application to AISI 420 Stainless Steel
EGQSJ - Grain-size distribution unmixing using the R package EMMAgeo
Phase-field modeling of grain evolutions in additive manufacturing from nucleation, growth, to coarsening | npj Computational Materials
Phase-field modeling of grain evolutions in additive manufacturing from nucleation, growth, to coarsening | npj Computational Materials
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Coarse-Grained Atomistics – Mechanics and Materials Laboratory | ETH Zurich
Mathematical modeling and multivariate analysis applied earliest soybean harvest associated drying and storage conditions and influences on physicochemical grain quality | Scientific Reports
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Accelerating phase-field-based microstructure evolution predictions via surrogate models trained by machine learning methods | npj Computational Materials
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EGQSJ - Grain-size distribution unmixing using the R package EMMAgeo
Modeling material variability with uncertainty quantification and machine learning techniques
Model Predictive Control of the Grain Drying Process
Discrete and continuum modelling of grain size segregation during bedload transport | Journal of Fluid Mechanics | Cambridge Core
Grain-size distribution unmixing using the R package EMMAgeo - EGQSJ
