NSF award 2532771 · Rochester Institute of Tech

LEAPS-MPS: Machine Learning the Variational Space for Efficient Quantum Embedding Simulations of Strongly Correlated Matter

Final report due

28 January 2028

in 467 days · The award ends on 30 September 2027.

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Decide about an extension2 Jun 2027in 227 days
award ending 2027-09-30 · Research.gov
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Extension request16 Aug 2027in 302 days
award ending 2027-09-30 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice20 Sep 2027in 337 days
award ending 2027-09-30 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Jan 2028in 467 days
award ending 2027-09-30 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Jan 2028in 467 days
award ending 2027-09-30 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Jan 2028in 467 days
award ending 2027-09-30 · 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 2027.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 January 2028.

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Award card

Award number: 2532771
Period of support: 1 Oct 2025 – 30 Sep 2027
Amount: $249,556
Awardee: Rochester Institute of Tech, Rochester, NY
Program: OFFICE OF MULTIDISCIPLINARY AC
Directorate: MPS

Abstract

NON-TECHNICAL SUMMARY The objective of this project is to develop a new computational method to accelerate the design and discovery of advanced materials. Many materials with potential for transformative applications, such as clean energy and next-generation electronics, exhibit quantum properties that are too complex to simulate efficiently with existing tools, creating a bottleneck for scientific progress. This…

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