Automatic Rietveld refinement by robotic process automation with RIETAN-FP

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 $${R_{{\rm{wp}}}}$$ value. Additionally, we evaluated the programs for analyzing X-ray powder diffraction patterns of anatase TiO2, Ca5(PO4)3F, 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.

Keywords

• rietveld analysis
• robotic process automation
• machine learning
• rietan-fp