TEM Software Publications Library

The study demonstrates how Python scripting can extend the functionality of TEM and STEM instruments. Customized automation routines allow researchers to streamline acquisition and analysis tasks.

The study demonstrates Python-enabled workflows for integrating diverse HVAC technologies within EnergyPlus simulations. The framework improves flexibility for building-performance and energy-efficiency analyses.

The paper presents a foundation deep-learning model for accurate SEM image segmentation in critical-dimension metrology. The approach improves measurement precision and robustness for semiconductor inspection applications.

This work examines the use of generative AI to create synthetic medical datasets for training artificial intelligence systems. The approach aims to improve data availability while addressing privacy and accessibility challenges.

This work describes cryoSPARC methods for helical reconstruction of amyloid filaments. The workflow facilitates detailed structural characterization of disease-related fibrillar assemblies.

The authors use in-situ TEM heating to study FeNiCr/C coatings developed for hydrogen evolution reactions. The observations reveal thermal stability and microstructural changes relevant to catalytic performance.

SDynPy introduces open-source tools for inverse source estimation within structural dynamics workflows. The package helps identify excitation sources and supports advanced vibration analysis studies.

This dataset captures activity patterns associated with Jupyter Notebook usage. The resource supports software engineering research focused on computational workflows and interactive programming practices.

Marimba is a Python framework for structuring and processing FAIR scientific image datasets. The platform promotes data discoverability, accessibility, interoperability, and reusability in research workflows.

PyCCAPT introduces an open-source Python platform for atom probe instrument control and data calibration. The package expands experimental flexibility and promotes reproducible workflows in atom probe tomography.

The authors combine 4D-STEM and EELS techniques to analyze battery cathode nanoparticles quantitatively. The workflow links structural and chemical information to support advanced energy materials research.

SAM-I-Am introduces a semantic boosting framework for zero-shot segmentation of atomic-scale electron microscopy images. The method improves feature recognition without requiring extensive task-specific training data.

This protocol describes SEM-based analysis of sclerotial morphology and specimen preparation procedures. The workflow enables detailed examination of structural changes in fungal samples.

SUN-DIC is an open-source Python software package for digital image correlation analysis. The tool enables accurate full-field displacement and strain measurements from image data in engineering applications.

TemCompanion is an open-source graphical application for TEM image processing and analysis across multiple operating systems. The software provides an accessible environment for visualization, measurement, and workflow management in electron microscopy.

The authors propose a tomographic reconstruction strategy that incorporates real-time prior information during data acquisition. The method aims to improve reconstruction efficiency and decision-making while imaging.

This paper explores explainable approaches to access-control systems within the BlueSky framework. The work aims to improve transparency and user understanding of authorization decisions in complex security environments.

This study explores explainable artificial intelligence techniques for SEM defect image classification in semiconductor manufacturing. The approach improves model transparency and helps experts understand the reasoning behind automated defect detection decisions.

This article discusses emerging approaches toward time-resolved electron tomography and four-dimensional STEM. The techniques aim to capture both spatial and temporal information from dynamic nanoscale systems.

The paper presents an ultrafast polymerase chain reaction platform based on a MEMS microheater. The technology enables rapid thermal cycling and improves the speed of molecular diagnostics workflows.