As the interest in using machine learning techniques for electron microscopy grows so does the need for labeled datasets and automated labeling strategies. Here we exploit the nature …
The computational cost of simulating scanning transmission electron microscopy (STEM) images limits the curation of large enough data sets to train accurate and robust machine …
Data management is a critical component of modern experimental workflows. As data generation rates increase, transferring data from acquisition servers to processing servers …
Y Cho, J Cho, J Park, J Wang, S Jeong, J Lee… - Communications …, 2024 - nature.com
Abstract Scanning Electron Microscopy (SEM) leverages electron wavelengths for nanoscale imaging, necessitating precise parameter adjustments like focus, stigmator, and …
Hollow vaterite microspheres are important materials for biomedical applications such as drug delivery and regenerative medicine owing to their biocompatibility, high specific …
In photon upconverting core–shell nanoparticles, structure strongly dictates performance. Typical imaging in scanning transmission electron microscopy has sufficient resolution to …
The digitization of controls, data, and analysis in microscopy is bringing the idea of autonomous microscopes closer to reality than ever before. Automated transmission …
Scanning transmission electron microscopy is a key tool for characterizing material structure and composition at atomic scales [1]. More recently, the development of high-speed …
Photon avalanching (PA) nanomaterials exhibit some of the most nonlinear optical phenomena reported for any material, allowing them to push the frontiers of applications …