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Context-Aware Deep Learning for Defect Classification in Atomic-Resolution STEM
Jiadong Dan, Cheng Zhang, Leyi Loh +5
Artificial intelligence is rapidly advancing materials characterization, yet most applications in electron microscopy rely solely on image contrast, overlooking the chemical and ex…
Symmetry quantification and segmentation in STEM imaging through Zernike moments
Jiadong Dan, Cheng Zhang, Xiaoxu Zhao +1
We present a method using Zernike moments for quantifying rotational and reflectional symmetries in scanning transmission electron microscopy (STEM) images, aimed at improving stru…
A multiscale generative model to understand disorder in domain boundaries
Jiadong Dan, Moaz Waqar, Ivan Erofeev +4
A continuing challenge in atomic resolution microscopy is to identify significant structural motifs and their assembly rules in synthesized materials with limited observations. Her…
Learning Motifs and their Hierarchies in Atomic Resolution Microscopy
Jiadong Dan, Xiaoxu Zhao, Shoucong Ning +4
Progress in functional materials discovery has been accelerated by advances in high throughput materials synthesis and by the development of high-throughput computation. However, a…