BERGAMASCHINI, ROBERTO
BERGAMASCHINI, ROBERTO
DIPARTIMENTO DI SCIENZA DEI MATERIALI
A Neural-Network surrogate for microstructure dynamics and crystal growth
2025 Lanzoni, D; Fantasia, A; Rigoni, M; Montalenti, F; Bergamaschini, R
Deep learning for simulating the evolution of condensed matter systems at the continuum scale: methods and applications
2025 Lanzoni, D; Montalenti, F; Bergamaschini, R
Interface energies of Ga2O3 phases with the sapphire substrate and the phase-locked epitaxy of metastable structures explained
2025 Bertoni, I; Ugolotti, A; Scalise, E; Bergamaschini, R; Miglio, L
Interpretation of the competition between beta and kappa phases with supersaturation in MOVPE growth of Ga2O3 on c-oriented sapphire
2025 Ugolotti, A; Bergamaschini, R; Bertoni, I; Bosi, M; Seravalli, L; Mezzadri, F; Cora, I; Fogarassy, Z; Mazzolini, P; Fornari, R; Miglio, L
ML-enabled boosting of growth simulations
2025 Lanzoni, D; Fantasia, A; Rovaris, F; Bergamaschini, R; Montalenti, F
Phase-field modelling of anisotropic solid-state dewetting on patterned substrates
2025 Radice, E; Salvalaglio, M; Bergamaschini, R
Progressing strained layer growth by deep learning
2025 Lanzoni, D; Fantasia, A; Rovaris, F; Bergamaschini, R; Montalenti, F
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
Supersaturation-Dependent Competition between β and κ Phases in the MOVPE Growth of Ga2O3on Al2O3(0001) and GaN (0001) Substrates
2025 Seravalli, L; Ugolotti, A; Bergamaschini, R; Bosi, M; Cora, I; Mezzadri, F; Mazzolini, P; Cademartiri, L; Bertoni, I; Fogarassy, Z; Pécz, B; Bierwagen, O; Ardenghi, A; Leone, S; Nasi, L; Miglio, L; Fornari, R
Accelerating Crystal Growth Simulations by Convolutional Neural Networks
2024 Lanzoni, D; Martín-Encinar, L; Rovaris, F; Fantasia, A; Montalenti, F; Bergamaschini, R
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
Convolutional Recurrent Neural Networks for tackling materials dynamics at the mesoscale
2024 Lanzoni, D; 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
Interplay of crystal faceting, wetting interactions and substrate geometry in solid-state dewetting and selective-area growth: a phase-field approach
2024 Radice, E; Miglio, L; Montalenti, F; Bergamaschini, R
Near-Infrared Light Trapping and Avalanche Multiplication in Silicon Epitaxial Microcrystals
2024 Falcone, V; Barzaghi, A; Signorelli, F; Valente, J; Firoozabadi, S; Zucchetti, C; Bergamaschini, R; Ballabio, A; Bottegoni, F; Zappa, F; Montalenti, F; Miglio, L; Volz, K; Paul, D; Biagioni, P; Tosi, A; Isella, G
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
Ge and Si Microcrystal Photodetectors with Enhanced Infrared Responsivity
2023 Falcone, V; Barzaghi, A; Signorelli, F; Bergamaschini, R; Valente, J; Paul, D; Tosi, A; Isella, G
In-Plane Nanowire Growth of Topological Crystalline Insulator Pb₁₋ₓSnₓTe
2023 Schellingerhout, S; Bergamaschini, R; Verheijen, M; Montalenti, F; Miglio, L; Bakkers, E