Automatic Rietveld refinement by robotic process automation with RIETAN-FP. Issue 1 (31st December 2022)

• Record Type: Journal Article
• Authors: Tamura, Ryo; Sumita, Masato; Terayama, Kei; Tsuda, Koji; Izumi, Fujio; Matsushita, Yoshitaka
• Is Part Of: Science and Technology of Advanced Materials: Methods. Volume 2:Issue 1(2022)
• Page Start: 435
• Page End: 444
• Publication Date: 2022-12-31
• Subjects: Rietveld analysis -- robotic process automation -- machine learning -- RIETAN-FP
• DOI: 10.1080/27660400.2022.2146470
• Languages: English
• ISSNs: 2766-0400

Abstract

ABSTRACT: Rietveld analysis necessitates the manual trial-and-error refinement of various parameters. To reduce human costs and resources, we have developed a robotic process automation (RPA) system for the Rietveld analysis program RIETAN-FP. By executing our proposed RPA programs, the background parameters of intensities can be determined, and black-box optimizations used to automatically search for peak profile parameters with a small R w p value. Additionally, we evaluated the programs for analyzing X-ray powder diffraction patterns of anatase TiO2, Ca5 (PO4 )3 F, and BaSO4 . Consequently, it was verified that RPA can be utilized to automate Rietveld analysis in simple cases. This indicates that RPA can be used for conducting black-box optimizations for graphical user interface (GUI) applications in materials science. Graphical abstract: uf0001