TEM Software Publications Library

PyPhase is a Python package developed for X-ray phase imaging and phase-retrieval applications. The software provides accessible reconstruction methods that facilitate broader adoption of phase-contrast imaging techniques.

This study explores operando and in-situ TEM imaging at cryogenic temperatures. The platform enables direct observation of material behavior and dynamic processes under low-temperature conditions.

This work applies deep learning techniques to reconstruct phase objects from 4D-STEM measurements. The approach extracts quantitative structural information from diffraction datasets while improving reconstruction efficiency and robustness.

Prismatic 2.0 delivers GPU-enabled simulations for STEM and HRTEM applications. The software accelerates image generation and allows researchers to investigate complex electron-specimen interactions efficiently.

Probelab ReImager is an open-source application designed to streamline image processing in electron microscopy laboratories. The software simplifies preparation of publication-quality figures and analytical outputs.

Pycro-Manager provides an open-source platform for customizable and reproducible microscope control. The software integrates automation, scripting, and data acquisition within flexible experimental workflows.

The paper presents radiomics software designed for breast imaging optimization and simulation research. The platform facilitates image quality assessment and evaluation of diagnostic workflow improvements.

The authors use SEM-EDS to analyze pigments recovered from the archaeological site of Nauportus. Elemental characterization provides information about historical materials and manufacturing practices.

The paper investigates optimization of speckle patterns for digital image correlation applications. Improved pattern design enhances measurement accuracy and reliability in experimental mechanics.

The authors outline strategies for combining EELS and EDS measurements within unified analytical workflows. The approach enhances compositional interpretation by leveraging complementary spectroscopic information sources.

This chapter reviews synchrotron beamlines, instrumentation, and their contributions to advanced imaging research. The discussion highlights the capabilities of modern synchrotron facilities in supporting cutting-edge scientific investigations.

This paper discusses TEM-, SEM-, and STEM-based immuno-CLEM workflows and their complementary advantages. The methods integrate molecular labeling with ultrastructural imaging to improve biological tissue characterization.

This article presents abTEM, a simulation package designed to model TEM imaging and diffraction from atomic structures. The framework bridges atomistic calculations and experimental observations through flexible first-principles-inspired workflows.

This work proposes a total deep variation approach for reconstructing electron exit waves from noisy microscopy measurements. The method combines deep learning with variational optimization to improve image fidelity and recover fine structural details.

This work investigates vacancy-assisted diffusion mechanisms in single-atom surface alloys. The findings provide insight into atomic mobility, surface stability, and catalytic behavior under operating conditions.

The paper reviews data-acquisition and reduction pipelines used for X-ray computed tomography at synchrotron facilities. It highlights workflow optimization, automation, and efficient management of large imaging datasets.

This contribution describes abTEM as a platform for generating realistic electron microscopy image simulations. The software supports atomistic modelling and helps researchers compare theoretical predictions with measured results.

The authors introduce a Python-based multislice simulation package for transmission electron microscopy. The project emphasizes openness, flexibility, and accessibility while providing accurate electron scattering calculations.

The authors use cryo-TEM to investigate interfacial structures in rechargeable lithium batteries. The observations provide valuable insight into degradation mechanisms and electrochemical performance.

DAQling introduces a modular data acquisition framework designed around reusable software components. The system simplifies development and deployment of scalable data-collection infrastructures.