TEM Software Publications Library

TopoTEM introduces a Python package for quantifying and visualizing polar topologies observed in STEM datasets. The toolkit streamlines extraction of structural metrics and supports analysis of complex ferroic domain configurations.

TrackMate 7 enhances object tracking workflows by integrating modern segmentation algorithms into a unified framework. The software supports robust analysis of particle, cell, and object dynamics in imaging experiments.

The authors present a modular platform that automates cryo-focused ion beam preparation workflows. The system reduces manual effort and increases throughput for cryo-electron tomography sample preparation.

This research uses synchrotron soft X-ray scanning transmission microscopy to investigate chromium bioremediation by Citrobacter freundii. Chemical mapping reveals biosorption and reduction mechanisms involved in contaminant removal.

The study investigates factors that influence leadership using both covariance-based SEM and partial least squares SEM approaches. The comparative analysis validates relationships among leadership antecedents and organizational variables.

The authors review computational approaches for investigating two-dimensional materials. The discussion covers modeling techniques that predict structural, electronic, and optical behavior at the nanoscale.

This paper describes customized automation strategies for routine electron probe microanalysis using vendor-supplied application programming interfaces. Automation improves efficiency, consistency, and throughput in analytical workflows.

DeepImageJ provides a user-friendly environment for applying deep-learning models within the ImageJ ecosystem. The framework enables researchers to use advanced artificial intelligence methods without extensive coding requirements.

The authors develop software for reciprocal-space mapping in single-crystal diffraction experiments. The package improves analysis efficiency and facilitates interpretation of complex diffraction measurements.

This paper presents Python-based workflows for conducting survey simulations at extreme computing scales. The framework coordinates distributed resources and streamlines execution of large scientific campaigns.

The paper describes FIB-SEM workflows tailored for the study of aquatic organisms. The methodology supports high-resolution volumetric imaging and detailed biological structure reconstruction.

This article explores applications of generative deep learning within digital pathology workflows. The methods support data augmentation, image synthesis, and computational assistance for diagnostic research.

This work demonstrates live processing capabilities for high-speed 4D-STEM acquisitions at extremely high detector frame rates. The approach enables high-fidelity measurements while providing immediate experimental feedback.

This research captures atomic-scale coalescence processes of silver nanoparticles in liquid environments. Real-time imaging sheds light on particle interactions and growth mechanisms in solution.

This study introduces 2D-heterostructure liquid cells for in-situ TEM imaging of solution-phase chemical reactions. The platform enables high-resolution observation of nanoscale reaction pathways and dynamic processes in liquid environments.

This article reviews the application of in-situ TEM to solid-state phase transformations and chemical reactions. The approach allows researchers to track structural evolution during thermal treatment and processing.

The study examines high-entropy alloy nanoparticles under gas and liquid environments using in-situ TEM. Real-time imaging reveals structural evolution and stability under changing operating conditions.

This review examines the use of in-situ transmission electron microscopy to study dynamic processes in materials. By introducing external stimuli during imaging, researchers gain direct insight into atomic-scale structural evolution and material behavior.

This chapter surveys the use of in-situ transmission electron microscopy for lithium-ion battery research. The methodology reveals structural transformations and degradation pathways during charge and discharge cycles.

This study introduces interferometric 4D-STEM for measuring lattice distortions and interlayer spacing in layered 2D materials. The approach captures both in-plane and out-of-plane structural variations with high precision.