Deep learning to classify and establish structure property predictions with PeakForce QNM atomic force microscopy

Machine learning, is a powerful tool to establish the presence (or absence) of correlations between microstructure and bulk properties with its ability to flesh out relationships and trends that are difficult to establish otherwise. In this application note from Bruker, explore the use of deep learning tools, such as convolutional neural nets (CNNs), to explore atomic force microscopy (AFM) phase and PeakForce QNM® images of impact copolymers, a polymer blend of polypropylene with micro-sized domains of rubber.