Ontology highlight
ABSTRACT:
SUBMITTER: Salmenjoki H
PROVIDER: S-EPMC6294252 | biostudies-literature | 2018 Dec
REPOSITORIES: biostudies-literature
Nature communications 20181213 1
Plastic deformation of micron-scale crystalline solids exhibits stress-strain curves with significant sample-to-sample variations. It is a pertinent question if this variability is purely random or to some extent predictable. Here we show, by employing machine learning techniques such as regression neural networks and support vector machines that deformation predictability evolves with strain and crystal size. Using data from discrete dislocations dynamics simulations, the machine learning model ...[more]