Collaborative Research: NanoMine: Data Driven Discovery for Nanocomposites

Project: Research project

Project Details

Description

In the past 15 years, research into nanoreinforced polymers has exploded, providing numerous examples of property enhancements ranging from altered thermal, mechanical, electrical, diffusion, optical and other properties. The amount of experimental data and simulation data, compounded with the data on the individual constitutent phase materials is staggering. At the same time, while some mechanistic principles underlying property changes have been slowly uncovered, our ability to both deeply understand the underlying principles and to design new nanostructured polymers with desired properties is severely limited by the lack of integration of the information. To determine the type of property changes that have been observed requires manual searching of online journal databases, full reading of the articles, and manual accumulation and then synthesis of the information. This approach ensures that many relevant papers and articles are overlooked and allows only rudimentary synthesis of data and trends. The birth of the materials genome concept provides a new paradigm for developing understanding of materials and designing new material concepts. In this proposal, we tackle this challenge in the domain of polymer nanocomposites. While the MG approach has had some success in the metals field, the polymers area is considerably less developed and no resources exist for nanocomposite systems. Yet with the infinite design space available to polymer nanocomposites, it is a prime system for a new data driven approach. The Intellectual Merit of the proposed work is 1) application of materials genome concepts to the complex material system of polymer nanocomposites, 2) development of a data resource for housing and exchange of polymer nanocomposite data, 3) development of reduced descriptor sets to characterize data, 4) development of new data mining methods to enable discovery of underlying material physics based upon the accumulated data, 5) integration of simulation tools to augment experimental data and enable exploration of design concepts.
StatusFinished
Effective start/end date9/15/138/31/17

Funding

  • National Science Foundation (DMR-1310292)

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