Webinars

Electrical atomic force microscopies (AFMs) in their various configurations, are powerful tools for characterizing 2D materials. However, standardizing data interpretation and accelerating material screening across multiple samples remains complex largely due to analysts-induced inconsistencies and preferences that can hinder standardization. Here, we review strategies with minimal human in the loop using conductive atomic force microscopy for electrical measurements in 2D materials. We propose a strategy to integrate computer vision techniques with automated image processing to be applied in 2D materials. The aim is to minimize human intervention and gain information on some of the most relevant electrical defects such as point defects, grain boundaries, cracks, and extended defects in MoS2 relying primarily on automated systems and techniques.