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cond-mat.mtrl-sci2025
A rigorous data-driven approach to the nucleation of defects in metals exploiting the link between kinetic properties and (dis)order parameters
Mattia Perrone, David D. Girardier, Giovanni M. Pavan +1
Nucleation processes, through which a new structure progressively forms within a pre-existing homogeneous phase, are fundamental in materials science, but are also typically non-tr…
cond-mat.mtrl-sci2025
Unsupervised Tracking of Local and Collective Defects Dynamics in Metals Under Deformation
Matteo Cioni, Mattia Perrone, Massimo Delle Piane +1
Metals owe their unique mechanical properties to how defects emerge and propagate within their crystal structure under stress. However, the mechanisms leading from the early emergi…
cond-mat.mtrl-sci2024
A data driven approach to classify descriptors based on their efficiency in translating noisy trajectories into physically-relevant information
Simone Martino, Domiziano Doria, Chiara Lionello +2
Reconstructing the physical complexity of many-body dynamical systems can be challenging. Starting from the trajectories of their constitutive units (raw data), typical approaches…