NSF award 2611605 · University of Connecticut

EAGER: Artificial Intelligence (AI) and Machine Learning (ML)-Enhanced Multi-Molecular Proxies for Tracing Fire-Climate-Ecosystem Feedbacks

Final report due

28 November 2028

in 772 days · The award ends on 31 July 2028.

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award ending 2028-07-31 · Research.gov
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Extension request16 Jun 2028in 607 days
award ending 2028-07-31 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice21 Jul 2028in 642 days
award ending 2028-07-31 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Nov 2028in 772 days
award ending 2028-07-31 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Nov 2028in 772 days
award ending 2028-07-31 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Nov 2028in 772 days
award ending 2028-07-31 · Research.gov
PAPPG 24-1: “financially closed out 120 days after their expiration date”

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NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 November 2028.

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Award card

Award number: 2611605
Period of support: 15 Aug 2026 – 31 Jul 2028
Amount: $99,999
Awardee: University of Connecticut, Storrs, CT
Program: LET-Life & Enviro Through Time, ESH-Earth System Hazards
Directorate: GEO

Abstract

Wildfires are becoming larger, more frequent, and more destructive across western North America in response to drought and other changes in the regional environment. Although ancient organic molecules preserved in geological archives contain valuable information on past wildfire activity, scientists can currently interpret only a small fraction of these data. This project will pioneer the development of new…

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