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Informatics derived materials databases for multifunctional properties.

Scott Broderick1, Krishna Rajan1

  • 1Institute for Combinatorial Discovery and Department of Materials Science and Engineering, Iowa State University, Ames, IA 50011, USA.

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|November 24, 2016
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Summary
This summary is machine-generated.

This review introduces informatics-based quantitative structure-property relationships (QSPR) that incorporate data uncertainty. This approach enables the creation of materials databases for targeted multifunctional properties, moving beyond single-parameter design.

Keywords:
materials informaticsquantitative structure–property relationshipsscintillator

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Area of Science:

  • Materials Science
  • Computational Chemistry
  • Data Science

Background:

  • Traditional materials databases rely on design parameters, limiting property optimization.
  • Developing large datasets from small, limited knowledge sets presents challenges in data uncertainty.
  • Current methods often focus on single material characteristics rather than multifunctional properties.

Approach:

  • Develops quantitative structure-property relationships (QSPR) by incorporating data uncertainty.
  • Utilizes an informatics-based approach for concurrent identification of key structure-property metrics.
  • Builds virtual materials databases based on design 'intent' rather than solely design parameters.

Key Points:

  • Enables rapid development of new and larger databases from limited initial data.
  • Facilitates the creation of materials databases for targeted multifunctional properties.
  • Allows for a shift from single-characteristic design to holistic material design.

Conclusions:

  • This informatics-driven methodology enhances materials discovery and design.
  • The approach is particularly relevant for complex inorganic solids, such as those used in scintillator applications.
  • Establishes a foundation for designing materials with tailored, multiple functionalities.