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Unsupervised Tracking of Local and Collective Defects Dynamics in Metals Under Deformation
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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 emerging (local) defects to the amplification of dislocations (collective plastic events) are not easy to track. Here, using tensile-stress atomistic simulations of a Copper lattice as a case study, we revisit this classical problem under a new perspective based on local dynamics rather than on purely structural arguments. We use a data-driven approach that allows tracking how local fluctuations emerge and accumulate in the atomic lattice in space and time, anticipating/determining the emergence of local or collective structural defects during deformation. Building solely on the general concepts of local fluctuations and spatiotemporal fluctuation correlations, this approach allows characterizing in a unique way the evolution through the elastic, plastic, and fracture phases, describing metals as complex systems where collective phenomena originate from local dynamical triggering events.
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A rigorous data-driven approach to the nucleation of defects in metals exploiting the link between kinetic properties and (dis)order parameters
A data-driven Langevin-model analysis of nucleation trajectories ranks order parameters for dislocation nucleation in fcc copper and identifies non-affine displacements in the critical nucleus as the optimal reaction ...
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