autoencoder 1graph neural networks 1high-entropy alloys 1long-term forecasting 1phase-field modeling 1surrogate modeling 1
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cond-mat.mtrl-sci2026
Deep Learning for Accelerated Long-Horizon Forecasting of Multicomponent Multiphase Microstructure Evolution in High-Entropy Alloys
Hamidreza Razavi, Nele Moelans
The paper introduces a surrogate model combining autoencoders, graph convolutional networks, and LSTM to rapidly predict long‑term microstructure evolution in multicomponent high‑e…
cond-mat.mtrl-sci2025
Physics-Informed GCN-LSTM Framework for Long-Term Forecasting of 2D and 3D Microstructure Evolution
Hamidreza Razavi, Nele Moelans
This paper presents a physics-informed framework that integrates graph convolutional networks (GCN) with long short-term memory (LSTM) architecture to forecast microstructure evolu…