Scanning electrochemical microscope based on visual recognition and machine learning
Date
2023Author
Subačiūtė-Žemaitienė, Jurga
Dzedzickis, Andrius
Zinovičius, Antanas
Ivinskij, Vadimas
Rožėnė, Justė
Bagdonas, Rokas
Bučinskas, Vytautas
Morkvėnaitė-Vilkončienė, Inga
Metadata
Show full item recordAbstract
Scanning electrochemical microscopy is an advanced tool for studying electrochemically active surfaces, including biological ones. Experiments with biological systems must be performed fast since their reactions and states change very fast. SECM can be easily equipped with a top-mounted light microscope with a known distance between the probe and the camera. This hardware solution, in combination with machine learning algorithms, would allow for the automatic finding of target locations, selecting exact positions for measurements, and compensating for positioning inaccuracies. This article demonstrates a newly constructed SECM setup. In addition, it allows faster user adaptation to unknown topography and shortened scanning times.