Can Neural Networks Learn Nanoscale Friction?
Can Neural Networks Learn Nanoscale Friction?
Current nanofriction experiments on crystals, both tip-on-surface and surface-on-surface, provide force traces as their sole output, typically exhibiting atomic size stick-slip oscillations. Physically interpreting these traces is a task left to the researcher. Historically done by hand, it generally consists in identifying the parameters of a Prandtl-Tomlinson (PT) model that …