Reproducible x-ray reflectometry optimization: statistical analysis of differential evolution fitting of multilayer structural models

TL;DR

This paper evaluates the reproducibility of X-ray reflectometry measurements and model fitting, providing best practices for consistent results across instruments and laboratories, based on extensive statistical analysis.

Contribution

It introduces concrete recommendations for reproducible XRR model fitting using common optimization methods, validated through bootstrap analysis.

Findings

Recommendations improve reproducibility of XRR results

Validated methods work across different instruments

Provides practical guidelines for research and industry

Abstract

We test the reproducibility of X-ray reflectometry(XRR) measurements and optimizations using an National Metrology Institute of Japan (NMIJ)/National Institute of Advanced Industrial Science and Technology (AIST) pre-standard. Based on bootstrap analysis of repeated refinements, using several CPU-years of time, we provide concrete recommendations of best practices for ensuring the reproducibility of XRR model fitting results. These recommendations can be used to study both instrument repeatability and cross-instrument reproducibility. Because the recommendations used optimizations methods available in commonly used commercial software, they can quickly be applied both in research and analytical laboratories, as well as fabrication environments.