TEM Software Publications Library

This research examines deformation mechanisms in neutron-irradiated aluminum-boron materials using SEM-based digital image correlation. Full-field strain measurements reveal the impact of irradiation-induced microstructural changes.

This chapter discusses elemental analysis using synchrotron-radiation X-ray fluorescence. High sensitivity and spatial resolution make the method valuable for biological and materials research.

This paper presents the FAIR Data Pipeline, a provenance-driven framework for managing scientific data and workflows. The approach improves traceability, reproducibility, and transparency in data-intensive research environments.

This study introduces accelerated orientation mapping workflows in Pyxem using multi-core CPUs and GPUs. The implementation speeds up template matching for large 4D-STEM datasets while maintaining accuracy for crystallographic characterization.

The study presents high-angle liquid-cell TEM tomography for three-dimensional reconstruction of materials in liquid environments. The method enables in-situ visualization of structures and processes with enhanced volumetric detail.

KNoC delivers cloud-native workflow capabilities for high-performance computing environments. The platform simplifies interactive application deployment and improves accessibility to distributed computing resources.

Tofu is a user-friendly toolkit for computed-tomography image processing and reconstruction. Workflow-based design enables efficient handling of large imaging datasets and complex processing tasks.

This review summarizes the growing role of machine learning in scanning transmission electron microscopy. The field leverages artificial intelligence for image interpretation, automation, and materials discovery.

MudrockNet uses deep learning for semantic segmentation of mudrock scanning electron microscopy images. The framework enables automated identification of geological features within complex microstructures.

This study applies neural networks trained with semi-synthetic datasets to detect nanoparticles in scanning electron microscopy images. The approach automates particle identification and measurement while reducing manual annotation effort.

The authors explore object segmentation techniques for cryo-electron tomography datasets. The approach helps identify biological structures within noisy volumetric data and supports automated analysis workflows.

This publication promotes transparent and reproducible practices for electron microscopy data analysis. The framework emphasizes open workflows, shareable tools, and reliable scientific results.

The authors combine computer vision and deep learning techniques to recognize nanoparticles in transmission electron microscopy images. The workflow supports automated characterization of catalytic materials and particle populations.

The study uses in-situ TEM to monitor structural changes in nanoparticles during carbon monoxide oxidation reactions. The observations connect catalytic activity with dynamic morphological transformations.

This article discusses approaches for quantifying amyloid deposition using nuclear imaging agents originally developed for bone scans. The methodology supports assessment of disease burden and diagnostic evaluation.

This article describes Python-based automation of SEM-EDS spectral map analysis using the edxia framework. The workflow reduces manual effort and improves reproducibility in microstructural investigations.

The work presents simulation techniques for Bragg coherent diffraction imaging. Modeling diffraction patterns helps researchers interpret crystal defects, lattice distortions, and nanoscale structural features.

STracking provides a free and open-source Python library for particle tracking and motion analysis. The framework supports construction of reproducible pipelines for studying dynamic biological systems.

This protocol outlines procedures for subtomogram averaging and classification of macromolecular structures within cryotomograms. The workflow enhances signal quality and supports higher-resolution structural interpretation.

Tomviz combines visualization, reconstruction, and analysis capabilities in a single open-source platform for electron tomography. The environment promotes interactive exploration of volumetric datasets and reproducible processing pipelines.