High-entropy nanoparticles: Synthesis-structure-property relationships and data-driven discovery
High-entropy nanoparticles have become a rapidly growing area of research in recent years.
Because of their multielemental compositions and unique high-entropy mixing states (ie …
Because of their multielemental compositions and unique high-entropy mixing states (ie …
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 …
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 …
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 …
Electric field control of chirality
Polar textures have attracted substantial attention in recent years as a promising analog to
spin-based textures in ferromagnets. Here, using optical second-harmonic generation …
spin-based textures in ferromagnets. Here, using optical second-harmonic generation …
High entropy materials based electrocatalysts for water splitting: Synthesis strategies, catalytic mechanisms, and prospects
Among various electrocatalysts, high entropy materials (HEMs) have attracted great
attention due to the distinctive designing concept and unique properties with captivating …
attention due to the distinctive designing concept and unique properties with captivating …
Unsupervised machine learning and cepstral analysis with 4D-STEM for characterizing complex microstructures of metallic alloys
Four-dimensional scanning transmission electron microscopy, coupled with a wide array of
data analytics, has unveiled new insights into complex materials. Here, we introduce a …
data analytics, has unveiled new insights into complex materials. Here, we introduce a …
Direct Measurement of the Thermal Expansion Coefficient of Epitaxial WSe2 by Four-Dimensional Scanning Transmission Electron Microscopy
Current reports of thermal expansion coefficients (TEC) of two-dimensional (2D) materials
show large discrepancies that span orders of magnitude. Determining the TEC of any 2D …
show large discrepancies that span orders of magnitude. Determining the TEC of any 2D …
AtomAI: a deep learning framework for analysis of image and spectroscopy data in (scanning) transmission electron microscopy and beyond
AtomAI is an open-source software package bridging instrument-specific Python libraries,
deep learning, and simulation tools into a single ecosystem. AtomAI allows direct …
deep learning, and simulation tools into a single ecosystem. AtomAI allows direct …
[HTML][HTML] Scanning transmission electron microscopy for advanced characterization of ferroic materials
Scanning Transmission electron microscopy (STEM) technologies have undergone
significant advancements in the last two decades. Advancements in aberration-correction …
significant advancements in the last two decades. Advancements in aberration-correction …