FANTASIA ANDREA

Martín-Encinar, L., Lanzoni, D., Fantasia, A., Rovaris, F., Bergamaschini, R., Montalenti, F. (2025). Quantitative analysis of the prediction performance of a Convolutional Neural Network evaluating the surface elastic energy of a strained film. COMPUTATIONAL MATERIALS SCIENCE, 249(5 February 2025) [10.1016/j.commatsci.2024.113657]. Detail

Fantasia, A., Rovaris, F., Abou El Kheir, O., Marzegalli, A., Lanzoni, D., Pessina, L., et al. (2024). Development of a machine learning interatomic potential for exploring pressure-dependent kinetics of phase transitions in germanium. THE JOURNAL OF CHEMICAL PHYSICS, 161(1), 1-11 [10.1063/5.0214588]. Detail

Lanzoni, D., Rovaris, F., Martìn-Encinar, L., Bergamaschini, R., Fantasia, A., Montalenti, F. (2024). Simulations of strained films evolution: extending accessible timescales through Convolutional Neural Networks. In Abstract book of "Multiscale Materials Modeling - MMM11". Detail

Rovaris, F., Marzegalli, A., Lanzoni, D., Fantasia, A., Ge, G., Montalenti, F., et al. (2024). Unravelling Atomistic Mechanisms of Pressure-Induced Phase Transitions in Silicon Nanoindentation. In Abstract Book. Detail

Lanzoni, D., Bergamaschini, R., Fantasia, A., Montalenti, F. (2024). Convolutional Recurrent Neural Networks for tackling materials dynamics at the mesoscale. In Abstract book of "Multiscale Materials Modeling - MMM11". Detail