Applying machine learning to atomically-thin material characterisation
23 May 2024
|By David Haworth
Applying machine learning to automated characterisation of atomically-thin materials
Just as James Cameron’s Terminator-800 was able to discriminate between “clothes, boots, and a motorcycle”, machine-learning could identify different areas of interest on 2D materials.
The simple, automated optical identification of fundamentally different physical areas on these materials (eg, areas displaying doping, strain, and electronic disorder) could significantly accelerate the science of atomically-thin materials.