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Machine-learning-based surrogate modeling of microstructure evolution using phase-field2022 Computational Materials Science article Materials Science Machine Learning in Materials Science
Iman Peivaste, Nima Hamidi Siboni, Ghasem Alahyarizadeh, Reza Ghaderi, Bob Svendsen, Dierk Raabe, +1 more
62citations -
An automated approach for developing neural network interatomic potentials with FLAME2021 Computational Materials Science article Materials Science Machine Learning in Materials Science Open access
Hossein Mirhosseini, Hossein Tahmasbi, Sai Ram Kuchana, S. Alireza Ghasemi, Thomas D. Kühne
12citations -
Application of artificial neural networks for predicting viscoelastic properties of short-fiber reinforced thermoplastics2025 Computational Materials Science article Materials Science Machine Learning in Materials Science
Sally Rüschendorf, Alexander Kriwet, Fabian Urban, Kai‐Uwe Schröder
3citations -
Multi-objective optimization and quantum hybridization of equivariant deep learning interatomic potentials2026 Computational Materials Science article Materials Science Machine Learning in Materials Science Open access
G. Laskaris, D. Morozov, D. Tarpanov, A. Seth, J. Procelewska, G. Sai Gautam, +3 more
1citations
5 results