TEM Software Publications Library

This dataset provides synchrotron small-angle X-ray scattering and wide-angle X-ray diffraction measurements. The collection supports methodological development, benchmarking, and materials characterization research.

The study compares segmentation techniques applied to SEM and optical micrographs for microstructural characterization. The analysis evaluates the effectiveness of different methods for extracting material features.

This work introduces impedance microscopy for spatially resolved imaging of solid-state battery interfaces. The technique improves characterization of electrochemical processes that are difficult to isolate using conventional impedance measurements.

This study investigates nanobubble growth and interaction dynamics in ethanol using liquid-cell TEM. The observations provide insight into nucleation mechanisms and gas-liquid behavior at small scales.

This work presents low-dose TEM imaging and diffraction strategies for highly beam-sensitive two-dimensional polymers. Advanced detector technology enables acquisition of useful structural information while minimizing radiation damage.

The authors describe open-source workflows for preprocessing and annotating satellite imagery through a stranded whale and dolphin case study. The framework promotes reproducible image-analysis practices for environmental monitoring applications.

This paper explores the use of artificial intelligence and machine learning to optimize big-data workflows. The proposed strategies improve resource utilization, processing efficiency, and decision support.

The study introduces a conditional-normalization approach for rapidly adapting SEM image denoising models. The method improves image quality while reducing the effort required for retraining.

This paper presents reproducible diffraction simulation workflows within abTEM, linking Bloch wave and multislice approaches. The framework promotes transparent comparisons and consistent computational experiments.

Shimexpy is a Python package developed for spatial harmonic imaging applications. The software provides tools for image analysis, processing, and research in advanced imaging techniques.

Torchmil is a PyTorch-based library designed for deep multiple-instance learning applications. The framework simplifies development of advanced machine learning models for complex data analysis tasks.

The authors develop an unsupervised denoising approach for STEM images that preserves atomic-scale information. The method improves image quality and strengthens the accuracy of quantitative structural measurements.

This article presents algorithms for classifying mineral dust particles using SEM-EDS data. The open-source approach supports automated identification of particle types and improves analysis efficiency for environmental and materials studies.

The authors propose an enhanced malware family classification framework that combines data balancing, feature optimization, and explainable AI methods. The methodology improves classification accuracy while providing interpretable insights into model behavior.

The authors benchmark population-based reinforcement learning techniques across robotic applications using GPU-accelerated simulation. The evaluation highlights scalability and performance differences among training strategies.

The paper discusses cryogenic electron microscopy and tomography approaches for characterizing beam-sensitive materials. Cryogenic conditions reduce radiation damage and enable preservation of delicate structural information.

The authors perform detailed in-situ TEM and EELS analysis of laser-induced reduction processes in graphene oxide. The results clarify structural and chemical transformations occurring during reduction.

This paper presents electron Fourier ptychography as a phase reconstruction technique for transmission electron microscopy. The method recovers detailed structural information from diffraction measurements while supporting both beam-sensitive and radiation-resistant specimens.

This article investigates elemental analysis of fine particles using SEM-EDS techniques. The method enables chemical characterization of small-scale particulates for materials and environmental studies.

ETSpy extends the HyperSpy ecosystem with dedicated tools for electron tomography reconstruction and analysis. The package supports preprocessing, alignment, and volumetric interpretation within a reproducible workflow environment.