NSF award 2625877 · University of Nebraska-Lincoln

FDT-BioTech:Hybrid Digital Twins for Predicting Skeletal Muscle Adaptation Across Activity and Metabolic States

Final report due

28 January 2030

in 1,198 days · The award ends on 30 September 2029.

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award ending 2029-09-30 · Research.gov
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Extension request16 Aug 2029in 1033 days
award ending 2029-09-30 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice20 Sep 2029in 1068 days
award ending 2029-09-30 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Jan 2030in 1198 days
award ending 2029-09-30 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Jan 2030in 1198 days
award ending 2029-09-30 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Jan 2030in 1198 days
award ending 2029-09-30 · 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 30 September 2029.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 January 2030.

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Award card

Award number: 2625877
Period of support: 1 Oct 2026 – 30 Sep 2029
Amount: $525,000
Awardee: University of Nebraska-Lincoln, Lincoln, NE
Program: OFFICE OF MULTIDISCIPLINARY AC, Disability & Rehab Engineering, MSPA-INTERDISCIPLINARY
Directorate: MPS

Abstract

Skeletal muscle is essential for movement, strength, and healthy metabolism. When muscles do not respond well to aging, illness, or recovery from injury, people are more likely to become weak and have serious health problems. This project will develop a digital twin model, which is an accurate virtual replica, of skeletal muscle to better understand why muscle function declines in aging and disease, and how to…

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