Automated laboratory x-ray diffractometer and fluorescence spectrometer for high-throughput materials characterization

TL;DR

This paper introduces an automated, high-throughput X-ray diffractometer and fluorescence spectrometer designed for rapid, spatially-resolved materials characterization, integrating automation and AI-driven data processing.

Contribution

The paper presents a novel instrument combining simultaneous X-ray diffraction and fluorescence measurements with automation for high-throughput materials analysis.

Findings

Achieves spatial resolution of ~200 μm with 1 s exposure times.

Automated specimen handling and data processing streamline high-throughput studies.

Demonstrates rapid data collection in a Cu-Ti alloy combinatorial study.

Abstract

The increasing importance of artificial intelligence and machine learning in materials research has created demand for automated, high-throughput characterization techniques capable of rapidly generating large data sets. We describe here a new instrument for simultaneous X-ray diffraction and X-ray fluorescence spectroscopy, optimized for high-throughput studies of combinatorial specimens. A bright, focused, high-energy X-ray beam (24 keV) combined with a pixel array area detector allows spatially-resolved (~200 {\mu}m) transmission diffraction measurements through thick (100 {\mu}m) specimens of structural metals with exposure times as short as 1 s. Simultaneously, a silicon drift detector records X-ray fluorescence from the specimen for spatially-resolved measurement of composition. Specimen handling is fully automated, with a robot inside the X-ray enclosure manipulating the sample for measurements at different locations. Data orchestration is also automated, with data streamed off the instrument and processed autonomously. In this paper we assess the performance of the instrument in terms of throughput, resolution, and signal-to-noise ratio, and provide an example of its capabilities through a combinatorial study of Cu-Ti alloys to demonstrate rapid data set creation.