LANZONI, DANIELE
LANZONI, DANIELE
DIPARTIMENTO DI SCIENZA DEI MATERIALI
Atomistic Mechanisms of dc-hd Phase Transition in Si Nanoindentation
2024 Rovaris, F; Ge, G; Lanzoni, D; Marzegalli, A; Barbisan, L; Tang, X; Miglio, L; Scalise, E; Montalenti, F
Deep Learning methods for the investigation of temporal evolution of materials
2024 Lanzoni, D
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
Silicon phase transitions in nanoindentation: Advanced molecular dynamics simulations with machine learning phase recognition
2024 Ge, G; Rovaris, F; Lanzoni, D; Barbisan, L; Tang, X; Miglio, L; Marzegalli, A; Scalise, E; Montalenti, F
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
Accurate generation of stochastic dynamics based on multi-model generative adversarial networks
2023 Lanzoni, D; Pierre-Louis, O; Montalenti, F
Machine learning potential for interacting dislocations in the presence of free surfaces
2022 Lanzoni, D; Rovaris, F; Montalenti, F
Morphological evolution via surface diffusion learned by convolutional, recurrent neural networks: Extrapolation and prediction uncertainty
2022 Lanzoni, D; Albani, M; Bergamaschini, R; Montalenti, F
A machine learning approach for studying low-energy dislocation distributions: methodology and applications to Ge/Si(001) films
2021 Lanzoni, D; Rovaris, F; Montalenti, F
Computational analysis of low-energy dislocation configurations in graded layers
2020 Lanzoni, D; Rovaris, F; Montalenti, F