Machine learning in scanning transmission electron microscopy
Scanning transmission electron microscopy (STEM) has emerged as a uniquely powerful
tool for structural and functional imaging of materials on the atomic level. Driven by …
tool for structural and functional imaging of materials on the atomic level. Driven by …
Synchrotron X-ray analytical techniques for studying materials electrochemistry in rechargeable batteries
Rechargeable battery technologies have ignited major breakthroughs in contemporary
society, including but not limited to revolutions in transportation, electronics, and grid energy …
society, including but not limited to revolutions in transportation, electronics, and grid energy …
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 …
Deep learning analysis on microscopic imaging in materials science
Microscopic imaging providing the real-space information of matter, plays an important role
for understanding the correlations between structure and properties in the field of materials …
for understanding the correlations between structure and properties in the field of materials …
Atomap: a new software tool for the automated analysis of atomic resolution images using two-dimensional Gaussian fitting
Scanning transmission electron microscopy (STEM) data with atomic resolution can contain
a large amount of information about the structure of a crystalline material. Often, this …
a large amount of information about the structure of a crystalline material. Often, this …
Materials informatics: From the atomic-level to the continuum
In recent years materials informatics, which is the application of data science to problems in
materials science and engineering, has emerged as a powerful tool for materials discovery …
materials science and engineering, has emerged as a powerful tool for materials discovery …
Surface-screening mechanisms in ferroelectric thin films and their effect on polarization dynamics and domain structures
SV Kalinin, Y Kim, DD Fong… - Reports on Progress in …, 2018 - iopscience.iop.org
For over 70 years, ferroelectric materials have been one of the central research topics for
condensed matter physics and material science, an interest driven both by fundamental …
condensed matter physics and material science, an interest driven both by fundamental …
Emergent interface vibrational structure of oxide superlattices
As the length scales of materials decrease, the heterogeneities associated with interfaces
become almost as important as the surrounding materials. This has led to extensive studies …
become almost as important as the surrounding materials. This has led to extensive studies …
Ensemble learning-iterative training machine learning for uncertainty quantification and automated experiment in atom-resolved microscopy
Deep learning has emerged as a technique of choice for rapid feature extraction across
imaging disciplines, allowing rapid conversion of the data streams to spatial or …
imaging disciplines, allowing rapid conversion of the data streams to spatial or …
Exploring order parameters and dynamic processes in disordered systems via variational autoencoders
We suggest and implement an approach for the bottom-up description of systems
undergoing large-scale structural changes and chemical transformations from dynamic …
undergoing large-scale structural changes and chemical transformations from dynamic …