NanoMine: an Online Platform of Materials Genome Prediction for Polymer Nanocomposites

Materials science is founded on the processing-structure-properties (p-s-p) paradigm. Understanding of mechanisms have built up over decades leading to a rich tapestry of knowledge which is used to select and design materials for applications. Unlike metallic alloy systems where databases and predictive tools have been built to up and can enable more rapid materials design, the polymer nanocomposite data/design space is considerably less developed due to the heterogeneity of constituent combinations as well as complexity in polymer and interphase behavior. 

Because of the complex mechanisms involved in nanocomposite formation and response, and the isolation of data sets from each other, both the fundamental understanding and the discovery of new nanocomposites is Edisonian and excruciatingly slow. We address this issue by creation of a living, open-source data resource for nanocomposites. NanoMine is built on both a schema and an ontology to provide a robustness to the FAIR (findable, accessible, interoperable and reusable) principles. Nanomine also allows for the registration of materials resources, bridging the gap between existing resources and the end users and making those existing resources available for research to material community. The data framework together with the module tools like microstructure characterization and the FEA simulation tools forms the nanocomposite data resource. Searching and visualization tools are being developed for user to query, visualize, and compare their data with the existing data in our system for design purposes. Tools and models utilizing data sciences and optimization concepts are being developed with the goal of data-driven materials design.

Our lab is making continuous efforts to improve the data curation experience by allowing customized Excel templates uploading in the front end and to ensure the data quality in the back end by developing autonomous agents to detect possible errors. We are now transitioning the back end system to a more extensible ontology-based system while maintaining an API to the Material Data Curator developed at NIST under the grand objective of the Materials Genome Initiative (MGI). A corresponding new front end javascript based user interface is also under development with more powerful dynamic features available.

You can access the prototype by clicking the button NanoMine link. Users without a Duke NetID can apply for a Duke Onelink account for access.

In addition to experimental data on polymer nanocomposites (PNCs), a copious amount of simulation data exists in the literature as well, which is informative for nanocomposite design. Modelling techniques such as density functional theory (DFT) and molecular dynamics (MD) can provide insights into various properties of PNCs, for example, electrical properties, thermal properties, and mechanical properties. To expand the scope of NanoMine, we are developing customized Excel templates for DFT and MD data curation.

Nanomine overview

Active Researcher on the Project:

Anqi Lin, Bingyin Hu

Relevant Publications

[1] Zhao, H., Li, X., Zhang, Y., Schadler, L. S., Chen, W., & Brinson, L. C. (2016). Perspective: NanoMine: A material genome approach for polymer nanocomposites analysis and design. APL Materials, 4(5), 053204.
[2] Zhao, H., Wang, Y., Lin, A., Hu, B., Yan, R., McCusker, J., ... & Brinson, L. C. (2018). NanoMine schema: An extensible data representation for polymer nanocomposites. APL Materials, 6(11), 111108.
[3] Brinson, L. C., Deagen, M., Chen, W., McCusker, J., McGuinness, D. L., Schadler, L. S., ... & Hu, B. (2020). Polymer nanocomposite data: curation, frameworks, access, and potential for discovery and design. ACS Macro Letters, 9(8), 1086-1094.