LANZONI DANIELE

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

(2024). Deep Learning methods for the investigation of temporal evolution of materials. (Tesi di dottorato, Università degli Studi di Milano-Bicocca, 2024). 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