Skip to the ledger

GrantClerk

NSF award 2504340 · Ohio State University, the

Collaborative Research: SHF: Medium: OASIS: An Open-Source AI-Driven EDA Tool for Real-Time Synthesis of Short-Distance Wireless Interconnects on Silicon

Final report due

28 January 2030

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

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 Jun 2029in 958 days

    award ending 2029-09-30 · Research.gov

  • Extension request16 Aug 2029in 1033 days

    award ending 2029-09-30 · Research.gov

  • No-cost extension notice20 Sep 2029in 1068 days

    award ending 2029-09-30 · Research.gov

  • Final report due28 Jan 2030in 1198 days

    award ending 2029-09-30 · Research.gov

  • Project outcomes report due28 Jan 2030in 1198 days

    award ending 2029-09-30 · Research.gov

  • Award is closed out28 Jan 2030in 1198 days

    award ending 2029-09-30 · Research.gov

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

  1. NSF lists this award's end date as 30 September 2029.
  2. NSF rules say the final report is due no later than 120 days after that.
  3. So the final report is due by 28 January 2030.

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
2504340
Period of support
1 Oct 2025 – 30 Sep 2029
Amount
$300,000
Awardee
Ohio State University, the, Columbus, OH
Program
Software & Hardware Foundation
Directorate
CSE

Abstract

Physics-Informed Neural Networks (PINNs) are an emerging class of Artificial Intelligence (AI) models that incorporate physical laws directly into their architecture, enabling fast and accurate simulations even with limited or noisy data. They show significant promise for electromagnetic (EM) simulations, particularly in managing parameter variations in real time. However, ensuring both accuracy and stability in…

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.