6 citations · 14 across the 10 of their papers we have counts for
4 papers · 1 filter
Unraveling the Atomic-Scale Pathways Driving Pressure-Induced Phase Transitions in Silicon
Fabrizio Rovaris, Anna Marzegalli, Francesco Montalenti +1
Silicon exhibits several metastable allotropes which recently attracted attention in the quest for materials with superior (e.g. optical) properties, compatible with Si technology.…
Polytypic Quantum Wells in Si and Ge: Impact of 2D Hexagonal Inclusions on Electronic Band Structure
Anna Marzegalli, Francesco Montalenti, Emilio Scalise
Crystal defects, traditionally viewed as detrimental, are now being explored for quantum technology applications. This study focuses on stacking faults in silicon and germanium, fo…
Extreme time extrapolation capabilities and thermodynamic consistency of physics-inspired Neural Networks for the 3D microstructure evolution of materials via Cahn-Hilliard flow
Daniele Lanzoni, Andrea Fantasia, Roberto Bergamaschini +2
A Convolutional Recurrent Neural Network (CRNN) is trained to reproduce the evolution of the spinodal decomposition process in three dimensions as described by the Cahn-Hilliard eq…
Quantitative analysis of the prediction performance of a Convolutional Neural Network evaluating the surface elastic energy of a strained film
Luis Martín Encinar, Daniele Lanzoni, Andrea Fantasia +3
A Deep Learning approach is devised to estimate the elastic energy density at the free surface of an undulated stressed film. About 190000 arbitrary surface profiles h(x) are r…