Abstract Machine learning (ML) has become critical for post-acquisition data analysis in
(scanning) transmission electron microscopy,(S) TEM, imaging and spectroscopy. An …

A robust approach for real-time analysis of the scanning transmission electron microscopy
(STEM) data streams, based on ensemble learning and iterative training (ELIT) of deep …

Fluorescence spectroscopy serves as an ultrasensitive sophisticated tool where background
noises which serve as a major impediment to the detection of the desired signals can be …

Physics‐driven discovery in an autonomous experiment has emerged as a dream
application of machine learning in physical sciences. Here, this work develops and …

We pose that microscopy offers an ideal real-world experimental environment for the
development and deployment of active Bayesian and reinforcement learning methods …

The engineering of quantum materials requires the development of tools able to address
various synthesis and characterization challenges. These include the establishment and …

Exploring the structural, chemical, and physical properties of matter on the nano-and atomic
scales has become possible with the recent advances in aberration-corrected electron …