Deep learning to predict structure property relationships with AFM

D. Yablon, I. Chakraborty
SurfaceChar LLC, Cognite,
United States

Keywords: machine learning, characterization


AFM images were collected on a variety of (ICP) samples that differ in bulk mechanical properties and microstructure. A deep learning model based on a convolutional neural net (CNN) successfully classified various combinations of ICP’s pointing to real and meaningful differences in their microstructure. A separate regression-based CNN was built to correlate the AFM images with various bulk mechanical properties. The results observed from the deep learning model reveal a relationship between the microstructures as captured by the AFM images with the different bulk material properties.