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

Hyun Sang Park, Timothy Long, Michael Wall, Alexander deJong, Ali Rachidi, Kacper Kowalik, David Elbert, Robert Drake, Todd C. Hufnagel

TL;DR

The paper addresses the need for automated, high-throughput bulk-material characterization and introduces MAXIMA, a multi-modal instrument that simultaneously performs transmission XRD at 24 keV and XRF, using a CdTe pixel detector and an SDD, with automated sample handling and autonomous data workflows. It demonstrates performance in throughput and resolution and validates the approach with a combinatorial Cu–Ti study, showing rapid data-set creation and the ability to extract lattice parameters and phase information across compositional gradients. The work provides a scalable, FAIR data-generating platform that supports ML-driven, self-driving laboratory workflows in materials discovery. Overall, MAXIMA enables rapid, spatially-resolved structural and compositional analysis of bulk metals, accelerating high-throughput experimental campaigns and data-driven materials design.

Abstract

The increasing importance of artificial intelligence and machine learning in materials research has created demand for automated, high-throughput characterization techniques capable of generating large data sets rapidly. 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 rapid, spatially-resolved (250 μm) transmission diffraction measurements through thick (100 μm) 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.

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

TL;DR

The paper addresses the need for automated, high-throughput bulk-material characterization and introduces MAXIMA, a multi-modal instrument that simultaneously performs transmission XRD at 24 keV and XRF, using a CdTe pixel detector and an SDD, with automated sample handling and autonomous data workflows. It demonstrates performance in throughput and resolution and validates the approach with a combinatorial Cu–Ti study, showing rapid data-set creation and the ability to extract lattice parameters and phase information across compositional gradients. The work provides a scalable, FAIR data-generating platform that supports ML-driven, self-driving laboratory workflows in materials discovery. Overall, MAXIMA enables rapid, spatially-resolved structural and compositional analysis of bulk metals, accelerating high-throughput experimental campaigns and data-driven materials design.

Abstract

The increasing importance of artificial intelligence and machine learning in materials research has created demand for automated, high-throughput characterization techniques capable of generating large data sets rapidly. 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 rapid, spatially-resolved (250 μm) transmission diffraction measurements through thick (100 μm) 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.

Paper Structure

This paper contains 14 sections, 5 equations, 10 figures.

Table of Contents

  1. Introduction
  2. Instrument configuration
  3. AIMD-L
  4. X-ray source and optics
  5. Detectors
  6. Sample handling
  7. Data streaming and workflows
  8. Performance
  9. Throughput
  10. Resolution
  11. High-throughput combinatorial study
  12. Discussion
  13. Conclusions
  14. Acknowledgments

Figures (10)

  • Figure 1: Absorption lengths of various elements for MAXIMA (In $K\alpha_1$, 24.21keV) and a standard laboratory source (Cu $K\alpha_1$, 8.05keV). The atomic numbers of three representative metals are indicated.
  • Figure 2: Schematic of MAXIMA performing XRD in transmission and XRF in reflection geometries. Red lines depict X-ray paths relevant to experiments.
  • Figure 3: Diffraction patterns from a 250 m thick specimen of nearly pure Cu at $D_\mathrm{ODD}=\qty{63.7}{mm}$ from the detector for collections times from 1100s.
  • Figure 4: Effect of beam convergence/divergence on angular resolution
  • Figure 5: Effect of finite sample thickness and beam size on angular resolution.
  • ...and 5 more figures