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  1. Home
  3. Automated Laboratory X-ray Diffractometer And Fluorescence Spectrometer For High-throughput Materials Characterization.
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  3. Automated Laboratory X-ray Diffractometer And Fluorescence Spectrometer For High-throughput Materials Characterization.

Related Experiment Video

Light-driven Molecular Motors on Surfaces for Single Molecular Imaging
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Published on: March 13, 2019

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

Hyun Sang Park1, Timothy Long1, Michael Wall1

  • 1Johns Hopkins University, Baltimore, Maryland 21218, USA.

The Review of Scientific Instruments
|June 24, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

A new automated instrument enables simultaneous X-ray diffraction and fluorescence spectroscopy for rapid materials characterization. This high-throughput system accelerates data generation for artificial intelligence and machine learning in materials research.

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Area of Science:

  • Materials Science
  • Analytical Chemistry
  • Instrumentation

Background:

  • Growing demand for automated, high-throughput characterization in materials research.
  • Need for rapid large dataset generation for AI and machine learning applications.
  • Limitations of existing techniques in speed and automation.

Purpose of the Study:

  • Introduce and evaluate a novel instrument for simultaneous X-ray diffraction (XRD) and X-ray fluorescence (XRF) spectroscopy.
  • Optimize the instrument for high-throughput studies of combinatorial specimens.
  • Demonstrate the instrument's capability in rapid dataset creation for materials research.

Main Methods:

  • Development of a new instrument integrating XRD and XRF spectroscopy.
  • Utilized a bright, focused, high-energy X-ray beam (24 keV) and a pixel array area detector for spatially resolved transmission diffraction.
  • Employed a silicon drift detector for spatially resolved elemental composition analysis via XRF.
  • Implemented fully automated specimen handling and data orchestration for autonomous processing.

    • Main Results:

    • Achieved spatially resolved (∼200 μm) diffraction measurements on thick specimens (>100 μm) with short exposure times (as low as 1 s).
    • Enabled simultaneous, spatially resolved elemental composition measurement using XRF.
    • Demonstrated high-throughput data generation through automated sample manipulation and data processing.
    • Successfully applied the instrument to a combinatorial study of Cu-Ti alloys.

    Conclusions:

    • The developed instrument significantly enhances throughput for materials characterization.
    • Automated XRD and XRF spectroscopy facilitates rapid data acquisition for AI-driven materials discovery.
    • The system provides a powerful tool for combinatorial materials studies and large dataset generation.