Rapid Discovery of Tribological Materials with Improved Performance Using Materials Informatics

摘要

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. This finding is transformative because it indicates that the performance lifetime of inorganic, solid-state lubricants can be optimized through material texture design.