Sfoglia per Autore
Quantitative analysis of the prediction performance of a Convolutional Neural Network evaluating the surface elastic energy of a strained film
2025 Martín-Encinar, L; Lanzoni, D; Fantasia, A; Rovaris, F; Bergamaschini, R; Montalenti, F
Towards Hexagonal Germanium via Nanoindentation
2025 Marzegalli, A; Scalise, E; Bikerouin, M; Rovaris, F; Fantasia, A; Montalenti, F; Miglio, L; Mio, A; Bongiorno, C; Zaghloul, M; Maier-Kiener, V; Schaffar, G; Spirito, J; Corley-Wiciak, A; Capellini, G
Pressure-dependent kinetics of phase transitions in Si and Ge using machine learning interatomic potentials
2025 Rovaris, F; Fantasia, A; Lanzoni, D; Marzegalli, A; Montalenti, F; Scalise, E
Unraveling Atomistic Mechanisms of Pressure-Induced Phase Transitions in Silicon and Germanium
2025 Rovaris, F; Fantasia, A; Marzegalli, A; Montalenti, F; Scalise, E
Origin and Evolution of I3 defects in Hexagonal Silicon and Germanium
2025 Rovaris, F; Dellevoet, J; Marzegalli, A; Schouten, M; Fantasia, A; Tse, O; Baumeier, B; Verheijen, M; Montalenti, F; Miglio, L; Bakkers, E; Scalise, E
ML-enabled boosting of growth simulations
2025 Lanzoni, D; Fantasia, A; Rovaris, F; Bergamaschini, R; Montalenti, F
A Neural-Network surrogate for microstructure dynamics and crystal growth
2025 Lanzoni, D; Fantasia, A; Rigoni, M; Montalenti, F; Bergamaschini, R
Progressing strained layer growth by deep learning
2025 Lanzoni, D; Fantasia, A; Rovaris, F; Bergamaschini, R; Montalenti, F
Accelerating Crystal Growth Simulations by Convolutional Neural Networks
2024 Lanzoni, D; Martín-Encinar, L; Rovaris, F; Fantasia, A; Montalenti, F; Bergamaschini, R
Convolutional Recurrent Neural Networks for tackling materials dynamics at the mesoscale
2024 Lanzoni, D; Bergamaschini, R; Fantasia, A; Montalenti, F
Unravelling Atomistic Mechanisms of Pressure-Induced Phase Transitions in Silicon Nanoindentation
2024 Rovaris, F; Marzegalli, A; Lanzoni, D; Fantasia, A; Ge, G; Montalenti, F; Scalise, E
Simulating morphological evolutions by Convolutional Neural Networks
2024 Lanzoni, D; Rovaris, F; Fantasia, A; Martı́n-Encinar, L; Montalenti, F; Bergamaschini, R
Simulations of strained films evolution: extending accessible timescales through Convolutional Neural Networks
2024 Lanzoni, D; Rovaris, F; Martín-Encinar, L; Fantasia, A; Bergamaschini, R; Montalenti, F
Simulations of strained films evolution: extending accessible timescales through Convolutional Neural Networks
2024 Lanzoni, D; Rovaris, F; Martìn-Encinar, L; Bergamaschini, R; Fantasia, A; Montalenti, F
Extreme time extrapolation capabilities and thermodynamic consistency of physics-inspired neural networks for the 3D microstructure evolution of materials via Cahn–Hilliard flow
2024 Lanzoni, D; Fantasia, A; Bergamaschini, R; Pierre-Louis, O; Montalenti, F
Development of a machine learning interatomic potential for exploring pressure-dependent kinetics of phase transitions in germanium
2024 Fantasia, A; Rovaris, F; Abou El Kheir, O; Marzegalli, A; Lanzoni, D; Pessina, L; Xiao, P; Zhou, C; Li, L; Henkelman, G; Scalise, E; Montalenti, F
Accelerating simulations of strained-film growth by deep learning: Finite element method accuracy over long time scales
2024 Lanzoni, D; Rovaris, F; Martín-Encinar, L; Fantasia, A; Bergamaschini, R; Montalenti, F
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