Automated collection and categorisation of STM images and STS spectra with and without machine learning.

ABSTRACT: Atomic resolution scanning probe microscopy, and in particular scanning tunnelling microscopy (STM) allows for high-spatial-resolution imaging and also spectroscopic analysis of small organic molecules. However, preparation and characterisation of the probe apex in situ by a human operator is one of the major barriers to high-throughput experimentation and to reproducibility between experiments. Characterisation of the probe apex is usually accomplished via assessment of the imaging quality on the target molecule and also the characteristics of the scanning tunnelling spectra (STS) on clean metal surfaces. Critically for spectroscopic experiments, assessment of the spatial resolution of the image is not sufficient to ensure a high-quality tip for spectroscopic measurements. The ability to

SUBMITTER: Barker DS 

PROVIDER: S-EPMC12415897 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature