NSF award 2540353 · University of Wisconsin-Madison

Collaborative Research: EAGER: Low-Sintering 2D Materials for AI-Assisted On-Demand Manufacturing of Electronic Devices

Final report due

29 December 2027

in 437 days · The award ends on 31 August 2027.

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 extension3 May 2027in 197 days
award ending 2027-08-31 · Research.gov
This one is ours, not NSF’s.
Extension request17 Jul 2027in 272 days
award ending 2027-08-31 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice21 Aug 2027in 307 days
award ending 2027-08-31 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due29 Dec 2027in 437 days
award ending 2027-08-31 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due29 Dec 2027in 437 days
award ending 2027-08-31 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out29 Dec 2027in 437 days
award ending 2027-08-31 · 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 August 2027.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 29 December 2027.

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: 2540353
Period of support: 1 Sep 2025 – 31 Aug 2027
Amount: $70,000
Awardee: University of Wisconsin-Madison, Madison, WI
Program: Special Projects
Directorate: TIP

Abstract

The goal of the project is to develop novel advanced materials integrated with real-time process feedback, assisted by a machine learning algorithm, to enable scalable, autonomous in-situ manufacturing of electronics. The technology will provide capabilities for on-demand fabrication, adaptive repair, and dynamic reconfiguration of circuits, functions that are particularly critical for long-duration space missions…

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.