[16a-A404-1~7] Machine learning on dielectrics study

▲ [16a-A404-3] Machine learning for discovery of meaningful chemical and physical contributors to piezoresponse force microscopy

〇Nazanin Bassiri-Gharb¹ (1.Georgia Tech)

Keywords:machine learning, piezoresponse force microscopy, PFM

This talk provides an overview of machine learning methods applied to characterization of ferroelectric materials through piezoresponse force microscopy (PFM), and particularly the resonant PFM approaches. I will specifically discuss data curation to apply physical and chemical constraints to machine learning, as well as a method to mask or enhance different contributions to the signal.