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Author Spotlight: Accelerating Discovery in Microporous Material Chemistry
Published on: October 6, 2023
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High-throughput determination of structural phase diagram and constituent phases using GRENDEL
A G Kusne1, D Keller, A Anderson
1Materials Measurement Science Division, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA.
Nanotechnology
|October 16, 2015
Summary
The Graph-based endmember extraction and labeling (GRENDEL) algorithm efficiently analyzes materials data. It determines phase diagrams and constituent phases from spectral data, enabling faster materials discovery.
Area of Science:
- Materials Science
- Data Science
- Crystallography
Background:
- High-throughput experimental techniques generate vast amounts of materials data.
- Analyzing this data for process-structure-property relationships is crucial for materials discovery.
- Existing methods struggle with the scale and complexity of modern materials datasets.
Purpose of the Study:
- To explore the Graph-based endmember extraction and labeling (GRENDEL) algorithm for high-throughput analysis of structural materials data.
- To determine phase diagrams and constituent phases from X-ray diffraction and Raman spectral data using GRENDEL.
- To demonstrate the integration of physical constraints and database data within the GRENDEL framework.
Main Methods:
- Application of the GRENDEL algorithm to analyze structural data from combinatorial material libraries.
- Utilizing physical constraints within GRENDEL to optimize the extraction of phase information.
- Integrating critically evaluated data from the Inorganic Crystal Structure Database (ICSD) for X-ray diffraction analysis.
- Employing Sunburst radial tree maps for visualizing material structure-property relationships.
Main Results:
- GRENDEL successfully determined phase diagrams and constituent phases from both X-ray diffraction and Raman spectral data.
- The algorithm demonstrated effective utilization of physical constraints for accurate data analysis.
- Integration of ICSD data enhanced the reliability of X-ray diffraction analysis.
- Sunburst radial tree maps provided insightful visualization of structure-property correlations.
Conclusions:
- The GRENDEL algorithm is a powerful high-throughput tool for analyzing complex materials data.
- GRENDEL facilitates the extraction of actionable knowledge regarding material phase behavior.
- The framework supports the incorporation of physics-based constraints and external databases for robust analysis and visualization.
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