Academic Journal
AXEAP: a software package for X-ray emission data analysis using unsupervised machine learning
| العنوان: | AXEAP: a software package for X-ray emission data analysis using unsupervised machine learning |
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| المؤلفون: | In-Hui Hwang, Mikhail A. Solovyev, Sang-Wook Han, Maria K. Y. Chan, John P. Hammonds, Steve M. Heald, Shelly D. Kelly, Nicholas Schwarz, Xiaoyi Zhang, Cheng-Jun Sun |
| المصدر: | Journal of Synchrotron Radiation, Vol 29, Iss 5, Pp 1309-1317 (2022) |
| بيانات النشر: | International Union of Crystallography, 2022. |
| سنة النشر: | 2022 |
| المجموعة: | LCC:Nuclear and particle physics. Atomic energy. Radioactivity LCC:Crystallography |
| مصطلحات موضوعية: | axeap, xes, unsupervised machine learning, user-friendly interface, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798, Crystallography, QD901-999 |
| الوصف: | The Argonne X-ray Emission Analysis Package (AXEAP) has been developed to calibrate and process X-ray emission spectroscopy (XES) data collected with a two-dimensional (2D) position-sensitive detector. AXEAP is designed to convert a 2D XES image into an XES spectrum in real time using both calculations and unsupervised machine learning. AXEAP is capable of making this transformation at a rate similar to data collection, allowing real-time comparisons during data collection, reducing the amount of data stored from gigabyte-sized image files to kilobyte-sized text files. With a user-friendly interface, AXEAP includes data processing for non-resonant and resonant XES images from multiple edges and elements. AXEAP is written in MATLAB and can run on common operating systems, including Linux, Windows, and MacOS. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1600-5775 16005775 |
| Relation: | http://scripts.iucr.org/cgi-bin/paper?S1600577522006786; https://doaj.org/toc/1600-5775 |
| DOI: | 10.1107/S1600577522006786 |
| URL الوصول: | https://doaj.org/article/6d67bb1b65cc4793aab931af1f673042 |
| رقم الانضمام: | edsdoj.6d67bb1b65cc4793aab931af1f673042 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 16005775 |
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| DOI: | 10.1107/S1600577522006786 |