About $4.67M to CUNY City College — a self-driving national laboratory where AI agents discover, design and produce bio-inspired materials (estimated total about $18.14M)
An award combining robotics, AI and autonomous experimentation to accelerate discovery of materials drawn from biological design principles. Remote cloud-lab access is to be provided to universities, national laboratories, industry and small businesses. The budget code is 47.084, covering technology, innovation and partnerships.
Grant overview (primary data)
- Award amount$4,667,934 / Est. total $18,142,384
- RecipientCUNY City College (New York)
- ProgramPCL-Programmable Cloud Labs
- Period2026-08-01 〜 2030-07-31
- FunderU.S. National Science Foundation (NSF) / NSF
Key points
- Combines robotics, AI and autonomous experimentation to accelerate discovery of materials drawn from biological design principles.
- Remote cloud-lab access is to be provided to universities, national laboratories, industry and small businesses.
- Named targets include advanced plastics, medical and industrial formulations, and optical coatings for imaging, sensing and communications.
- The budget code 47.084 accounts for 23 of the 120 NSF awards this site holds as of 2026-09-01, second most.
- The obligated amount is about $4,667,934 against an estimated total of about $18,142,384, roughly 26 percent.
- Budget code 47.084 accounts for 23 awards, second after 47.076 for education at 26.
1Running the experiment itself from a distance
What this award builds is not a facility holding instruments but a base for experiments reachable from a distance. The abstract uses the phrase self-driving: rather than a person moving their hands, an AI agent decides what to try next and a robot carries it out.
The users named are universities, national laboratories, industry and small businesses. Where the reach of participation is settled by who can own the equipment, remote access is meant to change that.
2Drawing on biological design principles
Materials discovery is a field where candidates are vast and the number of attempts is limited. This project takes as its clue the structures and mechanisms biology reached over long spans. Advanced plastics, smart medical and industrial formulations, and optical coatings for imaging, sensing and communications are named.
Combined with autonomous experimentation, the pace of search changes. Placing AI in the part that decides what to try also means that a bias in the search carries straight into the results, a point the abstract does not raise.
3The budget code is technology, innovation and partnerships
The budget code is 47.084, covering technology, innovation and partnerships. Among the 120 NSF awards this site holds as of 2026-09-01 it accounts for 23, second after 47.076 for education at 26.
The obligated amount is about $4,667,934 against an estimated total of about $18,142,384, so about 26 percent stands committed. On large multi-year projects the obligation is made year by year. The period runs four years, from 2026-08-01 to 2030-07-31.
Why it matters
Materials discovery is bounded by how many attempts cost and time allow. Concentrating instruments in one place and reaching them remotely opens that constraint beyond one organisation. Shifting the condition of participation from owning equipment to qualifying for access carries practical weight for small firms and universities without facilities.
FAQ
What is a self-driving laboratory?
Who may use it?
Why is the obligation below the estimated total?
Sources (primary)
Source: NSF Award Search (U.S. National Science Foundation, public domain). Amounts are the obligated amount. For privacy, we do not handle principal investigator names.
- NSF Award (original, official)
- NSF Award ID: 2607601