no code implementations • 11 Feb 2020 • Maxim Ziatdinov, Chris Nelson, Xiaohang Zhang, Rama Vasudevan, Eugene Eliseev, Anna N. Morozovska, Ichiro Takeuchi, Sergei V. Kalinin
Machine learning has emerged as a powerful tool for the analysis of mesoscopic and atomically resolved images and spectroscopy in electron and scanning probe microscopy, with the applications ranging from feature extraction to information compression and elucidation of relevant order parameters to inversion of imaging data to reconstruct structural models.
Materials Science
no code implementations • 2 Mar 2021 • Chris Nelson, Anna N. Morozovska, Maxim A. Ziatdinov, Eugene A. Eliseev, Xiaohang Zhang, Ichiro Takeuchi, Sergei V. Kalinin
The evolution of the atomic structures of the combinatorial library of Sm-substituted thin film BiFeO3 along the phase transition boundary from the ferroelectric rhombohedral phase to the non-ferroelectric orthorhombic phase is explored using scanning transmission electron microscopy (STEM).
Data Analysis, Statistics and Probability Materials Science