Automated and autonomous experiments in electron and scanning probe microscopy
Machine learning and artificial intelligence (ML/AI) are rapidly becoming an indispensable
part of physics research, with domain applications ranging from theory and materials …
part of physics research, with domain applications ranging from theory and materials …
Machine learning for automated experimentation in scanning transmission electron microscopy
Abstract Machine learning (ML) has become critical for post-acquisition data analysis in
(scanning) transmission electron microscopy,(S) TEM, imaging and spectroscopy. An …
(scanning) transmission electron microscopy,(S) TEM, imaging and spectroscopy. An …
AtomAI framework for deep learning analysis of image and spectroscopy data in electron and scanning probe microscopy
Over the past several decades, electron and scanning probe microscopes have become
critical components of condensed matter physics, materials science and chemistry research …
critical components of condensed matter physics, materials science and chemistry research …
Machine vision automated chiral molecule detection and classification in molecular imaging
Scanning probe microscopy (SPM) is recognized as an essential characterization tool in a
broad range of applications, allowing for real-space atomic imaging of solid surfaces …
broad range of applications, allowing for real-space atomic imaging of solid surfaces …
Mechanisms of Biomolecular Self‐Assembly Investigated Through In Situ Observations of Structures and Dynamics
Biomolecular self‐assembly of hierarchical materials is a precise and adaptable bottom‐up
approach to synthesizing across scales with considerable energy, health, environment …
approach to synthesizing across scales with considerable energy, health, environment …
Machine learning for optical scanning probe nanoscopy
The ability to perform nanometer‐scale optical imaging and spectroscopy is key to
deciphering the low‐energy effects in quantum materials, as well as vibrational fingerprints …
deciphering the low‐energy effects in quantum materials, as well as vibrational fingerprints …
Towards automating structural discovery in scanning transmission electron microscopy
N Creange, O Dyck, RK Vasudevan… - Machine Learning …, 2022 - iopscience.iop.org
Scanning transmission electron microscopy is now the primary tool for exploring functional
materials on the atomic level. Often, features of interest are highly localized in specific …
materials on the atomic level. Often, features of interest are highly localized in specific …
Bridging microscopy with molecular dynamics and quantum simulations: An atomAI based pipeline
Recent advances in (scanning) transmission electron microscopy have enabled a routine
generation of large volumes of high-veracity structural data on 2D and 3D materials …
generation of large volumes of high-veracity structural data on 2D and 3D materials …
Artificial intelligence for materials research at extremes
Materials development is slow and expensive, taking decades from inception to fielding. For
materials research at extremes, the situation is even more demanding, as the desired …
materials research at extremes, the situation is even more demanding, as the desired …
A roadmap for edge computing enabled automated multidimensional transmission electron microscopy
The advent of modern, high-speed electron detectors has made the collection of
multidimensional hyperspectral transmission electron microscopy datasets, such as 4D …
multidimensional hyperspectral transmission electron microscopy datasets, such as 4D …