NSF award 2543840 · William Marsh Rice University

CAREER: Physics-Informed, AI-Driven Prediction and Optimization of Concrete for Resilient Infrastructure

Final report due

28 November 2031

in 1,867 days · The award ends on 31 July 2031.

GrantClerk is a private service. We are not NSF or any government agency.

Dates this award owes

NSF emails you about this too.

Decide about an extension2 Apr 2031in 1627 days
award ending 2031-07-31 · Research.gov
This one is ours, not NSF’s.
Extension request16 Jun 2031in 1702 days
award ending 2031-07-31 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice21 Jul 2031in 1737 days
award ending 2031-07-31 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Nov 2031in 1867 days
award ending 2031-07-31 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Nov 2031in 1867 days
award ending 2031-07-31 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Nov 2031in 1867 days
award ending 2031-07-31 · Research.gov
PAPPG 24-1: “financially closed out 120 days after their expiration date”

Annual report dates come from the budget period on your award notice. That date is not public, so it is not shown here.

How we got this date

NSF lists this award's end date as 31 July 2031.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 November 2031.

Read the rule on Research.gov

Get a note before each report date

Add this award to your desk. We email you before each date and keep the dates in one place.

Renews each year until you cancel. Cancel any time from your account.

Already a member? Sign in

Award card

Award number: 2543840
Period of support: 1 Aug 2026 – 31 Jul 2031
Amount: $669,852
Awardee: William Marsh Rice University, Houston, TX
Program: ECI-Engineering for Civil Infr
Directorate: ENG

Abstract

This Faculty Early Career Development Program (CAREER) award will advance the predictive design of concrete, the most widely used construction material, by developing new data-driven approaches to improve performance, cost efficiency, and resource utilization. Concrete production currently relies on empirical, trial-and-error methods that often lead to suboptimal mixtures and increased costs. These limitations are…

Is this right?

We copy this from the public NSF award record. Your award notice and NSF always win. If a date looks wrong, check Research.gov.