Rapid Discovery of Tribological Materials with Improved Performance Using Materials Informatics

Abstract

Data mining and materials informatics methods were applied to the search for new, high-temperature solid-state lubricant materials. A predictive model was developed that enabled the efficient high-throughput screening of inorganic materials with input from atomic-scale modeling and experimental testing. It led to the identification of new solid-state lubricants for extreme environments. The project further identified a strong dependence of inorganic material wear on the direction of sliding and the quantification of the activation energy associated with the directionality of wear.

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Document Details

Document Type
Technical Report
Publication Date
Mar 10, 2014
Accession Number
ADA604507

Entities

People

  • Susan B. Sinnott

Organizations

  • University of Florida

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Chemistry
  • Data Mining
  • Data Sets
  • Databases
  • Department Of Defense
  • Energy
  • Extreme Environments
  • Heat Of Activation
  • High Temperature
  • Information Science
  • Inorganic Materials
  • Lubricants
  • Materials
  • Materials Science
  • Predictive Modeling
  • Statistical Analysis
  • Turbines

Fields of Study

  • Materials science

Readers

  • Molecular Genetics
  • Surface Engineering/Surface Coating Technology.
  • Tribology (the study of the boundary interaction between sliding surfaces, lubrication, wear and friction).

Technology Areas

  • AI & ML