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An AI-driven, Cloud-based, Materials Discovery Platform for Nanomaterial Structure: PDFitc

May 28, 2024

•Discovery of novel functional materials relies on a quantitative understanding of nanostructure

•There is a need for advanced artificial intelligence  (AI) and machine learning (ML) approaches to nanostructure determination

•We have developed a cloud-based, AI driven, platform for nanomaterial structure determination: “PDF in the cloud” (PDFitc.org).

•It consists of various applications for nanostructure determination, including a ML-based classifier for discovering material symmetry from a measured dataset, a high-throughput structure screening tool for predicting the structure of a measured signal, and a data-similarity visualization tool for finding changes in a signal in a time or temperature series.

•Uploaded data may be shared with collaborators and machine learned in the future for new materials discoveries.

The suite of Apps will be augmented over time allowing a wider range and more sophisticated analyses to be carried out and enriching the underlying database of PDFs that can then be used for machine learning

Authors

S. Billinge, Q. Du, D. Hsu (Columbia U.)

Additional Materials

U.S. National Science Foundation and NSF DMREF, Materials for Our Future

This material is based upon work supported by the U.S. National Science Foundation Award No. 2015237. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the U.S. National Science Foundation. This site is maintained collaboratively by principal investigators with NSF DMREF awards, independent of the NSF.