TEM Software Publications Library

The article reviews large-scale heterogeneous distributed systems used for machine learning workloads. It highlights frameworks such as TensorFlow and discusses scalable computing architectures for AI applications.

This work presents high-speed elemental mapping in SEM through the integration of micro-XRF and EDS technologies. The combined approach improves compositional imaging speed and analytical coverage.

The authors explore crystallization processes in amorphous iron particles using in-situ TEM. Real-time observations reveal structural transitions and thermal stability characteristics at the nanoscale.

This paper evaluates the thermal stability of hydroxyapatite nanobelts through in-situ TEM experiments. The results provide insight into morphological and structural changes occurring during heating.

The authors develop interactive parallel workflows for synchrotron tomography experiments. The framework accelerates data processing and enables near real-time analysis of large imaging datasets.

PyNX is a high-performance computing toolkit for coherent X-ray imaging and simulation. GPU-based processing supports advanced imaging reconstruction and analysis workflows.

LiberTEM provides a high-performance framework for analyzing large electron microscopy datasets. Its distributed architecture enables rapid data exploration and supports real-time scientific workflows across multiple computing environments.

This study maps the zonal structure of Titan’s northern polar vortex using atmospheric observations and modeling. The analysis reveals circulation patterns that improve understanding of climate dynamics on Saturn’s largest moon.

The paper demonstrates the use of pulsed-beam TEM to reduce radiation damage in hybrid perovskite materials. The approach helps preserve specimen integrity while maintaining imaging performance.

Topaz employs neural networks for both particle identification and image denoising in cryo-EM workflows. The framework improves data quality and enhances downstream structural reconstruction tasks.

The authors present open-source software tools developed for SEM metrology applications. The framework improves accessibility, reproducibility, and measurement capabilities for microscopy-based dimensional analysis.

This study uses machine learning models and openly available aviation datasets to predict aircraft go-around events. The approach supports operational analysis and improved understanding of flight safety factors.

The authors describe open-source methods for processing and indexing electron backscatter diffraction patterns. Principal component analysis and related techniques are used to enhance signal quality and improve EBSD data interpretation.

This work presents XRFtomo, a software tool for processing X-ray fluorescence tomography data. The package supports reconstruction, visualization, and analysis of elemental imaging datasets.

This work presents a method for determining secondary-phase area fractions using quantitative SEM-EDS mapping. Automated compositional analysis improves the assessment of multiphase material microstructures.

The chapter describes virtual imaging methods for simulating holographic reconstructions. The framework explains how computational models can generate and analyze reconstructed wavefronts from synthetic data.

This article introduces a sparse phase-retrieval algorithm for coherent X-ray diffraction imaging. The method improves reconstruction quality while leveraging sparse representations of the sample structure.

STEMTooL provides an open-source collection of Python utilities for processing electron microscopy datasets. The framework simplifies image handling, quantitative measurements, and custom analytical workflows for researchers.

This review highlights the applications of synchrotron XRF, XRD, and XAFS methods in advanced mineralogy. These techniques provide complementary information about composition, structure, and chemical states.

The article reviews radiation damage mechanisms in beam-sensitive TEM specimens. Understanding these effects helps researchers optimize imaging conditions and preserve delicate materials.