Artificial-intelligence-driven scanning probe microscopy - Krull, Alexander; Hirsch, P.; Rother, Carsten; Schiffrin, A.; Krull, C. (Communications Physics, 2020)
Enabling atomic-precision mapping and manipulation of surfaces, scanning probe microscopy requires constant human supervision to assess image quality and probe conditions. Here, the authors demonstrate DeepSPM, a machine learning approach allowing to acquire and classify data autonomously in multi-day Scanning Tunnelling Microscopy experiments.
Gesehen am 28.04.2020