About $4.87M to Scripps Research — an independent institute, neither university nor company, building an AI-guided chemistry lab usable from across the country (estimated total about $19.55M)
An award establishing the chemistry node of a national network of Programmable Cloud Labs. Robotic automation, an AI model broadly trained on chemical reactivity, and an open data format are integrated into one platform accessible to vetted users nationwide. The recipient is an independent research institute, neither a university nor a company.
Grant overview (primary data)
- Award amount$4,873,120 / Est. total $19,545,600
- RecipientThe Scripps Research Institute (California)
- ProgramPCL-Programmable Cloud Labs
- Period2026-08-01 〜 2030-07-31
- FunderU.S. National Science Foundation (NSF) / NSF
Key points
- Establishes the chemistry node of a Programmable Cloud Labs network as one platform accessible to vetted users across the country.
- Three components are integrated: robotic automation, an AI model broadly trained on chemical reactivity, and an open data format.
- The recipient is an independent research institute; only three of the 120 awards this site holds as of 2026-09-01 fall in that category.
- The obligated amount is about $4,873,120 against an estimated total of about $19,545,600, roughly 25 percent.
- The period runs four years, from 2026-08-01 to 2030-07-31.
- Three capabilities are integrated: robotic automation, an AI model trained broadly on reactivity, and open data formats.
1The recipient is neither a university nor a company
Among the 120 NSF awards this site holds as of 2026-09-01, the recipients break down as 104 universities and the like, 13 companies, and three independent research institutes that are neither. This award is one of those three.
An independent institute has no faculties and is run with research rather than teaching as its purpose. It neither carries students as a university does nor sells products as a company does. Few of them appear as recipients, yet people and equipment can be concentrated in a particular field.
2Making a laboratory usable from across the country
What this award builds is not a standalone laboratory but one node inside a national network. Three things are integrated: robotic automation capability, an AI model broadly trained on chemical reactivity, and an open data format.
The abstract observes that such capabilities are currently too expensive for broad adoption and that existing platforms are often optimised for niche needs. Rather than multiplying the places able to own the equipment, putting it in one place for vetted users to reach remotely reads as an attempt to lower the cost barrier.
Naming an open data format as one of the three pillars suggests weight placed on results surviving in a form usable elsewhere.
3The obligation is a quarter of the estimated total
The obligated amount is about $4,873,120 against an estimated total of about $19,545,600, so roughly 25 percent stands committed.
Among the 120 NSF awards this site holds as of 2026-09-01, the estimated total and the obligated amount match on 86 and differ on 34. In aggregate, about $678.43 million estimated stands against about $329.92 million obligated, or 48.6 percent. On multi-year awards the obligation is made year by year, so only part of the total appears in the record at the outset. Reading the figures means keeping the two apart.
4Three things that only work together
This node integrates three capabilities, and no one of them suffices. Instruments that run themselves stall without something to decide the next trial; a decision leads nowhere if the result is not left in a readable form.
- 1Robotic automationEverything from handling reagents to running the reaction turns without hands
- 2An AI model of chemical reactivityTrained broadly on reactivity rather than optimised for one use, it proposes the next candidates
- 3Open data formatsResults survive in a form readable elsewhere, usable for the next round of training and for reproduction
That open data formats stands among the three shows the node is not aiming at the efficiency of one facility. The abstract notes that such capabilities remain costly to adopt broadly and that existing infrastructure is often optimised for particular uses. Placing them in one location for national remote use answers both.
Why it matters
Concentrating equipment in one place for remote use, instead of holding it everywhere, is a known way to lower a cost barrier. That an open data format sits among the three pillars indicates weight placed not only on sharing instruments but on whether the results that come out are usable elsewhere.
FAQ
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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: 2607628