ePDFpy: A Python-based interactive GUI tool for electron pair distribution function analysis of amorphous materials

• Published in: Computer physics communications Vol. 299; p. 109137
• Main Authors: Kim, Minhyo, Kim, Pilsung, Bassiri, Riccardo, Prasai, Kiran, Fejer, Martin M., Lee, Kyung-ha
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.06.2024
• Subjects: Amorphous material; Electron diffraction pattern; Electron pair distribution function; ePDFpy; Short range order; Transmission electron microscope; Electron pair distribution function; Amorphous material; Short range order; Electron diffraction pattern; ePDFpy; Transmission electron microscope
• ISSN: 0010-4655; 1879-2944
• DOI: 10.1016/j.cpc.2024.109137

ePDFpy is an interactive analysis program with a graphical user interface (GUI), designed to process the electron Pair Distribution Function (PDF) analysis of diffraction patterns from Transmission Electron Microscope (TEM), to identify the local atomic structure of amorphous materials. The program offers a user-friendly Python-based interface, providing a straightforward and adaptable workflow for PDF analysis. Various optimization and fitting processes were implemented to accurately reduce the electron diffraction data, including center-fitting and elliptical correction of diffraction data. An improved parameter-estimation feature is available to enhance the efficiency of the fitting process, along with an interactive GUI. ePDFpy will be freely distributed for academic purposes, with additional features, including a beam mask drawing module. Program Title: ePDFpy CPC Library link to program files:https://doi.org/10.17632/sym3sfnh7w.1 Developer's repository link:https://github.com/GWlab-SKKU/ePDFpy Licensing provisions: GNU GPLv3 Programming language: Python Nature of problem: The general process of pair distribution function analysis consists of two major steps: image process on diffraction pattern and fitting appropriate parameters. Both of the procedures are affected by the user's proficiency, which can be responsible for producing inconsistent results and inefficiency. Thus, accurate calculation methods along with fully automated feature are required to enhance the quality of the analysis result. Solution method: ePDFpy offers an unbiased automated image process based on a computer vision algorithm to produce the consistent output of intensity profiles from diffraction patterns. In addition, converting the data structures into a multi-dimensional array enables efficient multi-parameter fitting features by performing parallel computation. All of these features are accomplished using various open-source libraries in the Python community, along with an interactive GUI.