NSF award 2602544 · Rensselaer Polytechnic Institute

Collaborative Research: CDS&E: Motif-Based Deep Learning for Discovery and Chemical Insights into Disordered Phases

Final report due

28 November 2029

in 1,137 days · The award ends on 31 July 2029.

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award ending 2029-07-31 · Research.gov
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Extension request16 Jun 2029in 972 days
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PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice21 Jul 2029in 1007 days
award ending 2029-07-31 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Nov 2029in 1137 days
award ending 2029-07-31 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Nov 2029in 1137 days
award ending 2029-07-31 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Nov 2029in 1137 days
award ending 2029-07-31 · Research.gov
PAPPG 24-1: “financially closed out 120 days after their expiration date”

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NSF lists this award's end date as 31 July 2029.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 November 2029.

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Award card

Award number: 2602544
Period of support: 15 Aug 2026 – 31 Jul 2029
Amount: $300,880
Awardee: Rensselaer Polytechnic Institute, Troy, NY
Program: CONDENSED MATTER & MAT THEORY
Directorate: MPS

Abstract

Nontechnical Description: Modern technologies, from energy-efficient electronics to batteries, depend on discovering new materials with tailored properties. Today, powerful computer models help identify promising materials before they are synthesized, greatly accelerating scientific discovery. This project develops a machine learning framework that explicitly learns and predicts atomic disorder in crystalline…

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