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A proxy for oxygen storage capacity from high-throughput screening and automated data analysis.

Jack J Quayle1, Alexandros P Katsoulidis1, John B Claridge1

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Researchers developed a high-throughput method to predict oxygen storage capacity (OSC) in catalysts. This accelerates the discovery of new materials for heterogeneous catalysis by using fast analytical techniques for OSC prediction.

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Area of Science:

  • Materials Science
  • Catalysis
  • Chemical Engineering

Background:

  • Oxygen storage and release are crucial in heterogeneous catalysis, particularly in Mars-van Krevelen mechanisms.
  • Direct measurement of oxygen storage capacity (OSC) is a bottleneck due to its time-consuming and difficult-to-parallelize nature.
  • Accelerating the discovery of high-performance oxygen storage catalysts is essential for advancing catalytic processes.

Purpose of the Study:

  • To develop a high-throughput synthesis and characterization workflow for rare-earth doped ceria-zirconia oxygen storage catalysts.
  • To create a predictive model for OSC based on data from automated characterization techniques.
  • To identify key material properties that correlate with high OSC performance.

Main Methods:

  • A robotic-based co-precipitation synthesis route was employed to create material libraries.
  • Sequentially automated powder X-ray diffraction (PXRD), Raman spectroscopy, and thermogravimetric analysis (TGA) were used for characterization.
  • A predictive model for OSC was developed using data from fast-to-measure analytical techniques.

Main Results:

  • Automated data extraction facilitated rapid trend identification.
  • The developed OSC prediction model incorporated variables from rapid analytical techniques.
  • Predicted OSC values showed strong agreement with experimental observations on an independent validation set.
  • Identified material properties serve as effective proxies for OSC performance.

Conclusions:

  • The developed high-throughput workflow and predictive model significantly accelerate the discovery of high-capacity oxygen storage materials.
  • The study highlights the potential of using fast analytical techniques for predicting catalytic performance.
  • This approach can be extended to discover candidate catalysts for other heterogeneous transformations.