• Advanced sensors
• Robotics and embodied AI systems (machines whose "intelligence" lives inside physical hardware, like a robot body rather than a server)
• Human-robot interfaces
• Cyber-physical systems (networks where software and physical processes continuously exchange signals, such as a smart grid or autonomous-vehicle fleet)

NSF says successful teams should produce platform tools useful across many application domains. Examples listed include healthcare, national defense, emergency response, advanced manufacturing, and scientific discovery.

What are the two future topics?

NSF released early details so applicants can begin assembling large, multidisciplinary teams in advance.

• From Sequence to Function — Aims to close the gap between predicting a protein's 3D structure and understanding its dynamic behavior. The goal is platform technologies that let scientists design proteins or entire genomes with predictable, controllable function, replacing accidental discovery with deliberate engineering.
• Computation at the Limit of Physics — Targets the widening gap between today's energy-efficient silicon chips (CMOS, or complementary metal-oxide-semiconductor technology, the dominant transistor design in modern processors) and the physical limits of computation. Teams will pursue new paradigms to dramatically narrow that gap.

NSF does not accept proposals for these topics at this stage. Full timelines and guidance will follow in later announcements.

When can teams apply or learn more?

An introductory webinar is scheduled for Wednesday, Oct. 14, 2026, at 1 p.m. EDT. Registration is required through the NSF X-Labs webpage.

NSF also issued a Request for Information asking the public to suggest topics for future funding rounds. Responses are due Oct. 30, 2026.

Why X-Labs work differently

Erwin Gianchandani, NSF Assistant Director for Technology, Innovation and Partnerships, said the initiative tries to shorten the path from lab insight to real-world use.

"The NSF X-Labs initiative is investing in high-risk, high-impact research that requires substantial resources beyond traditional funding mechanisms, reducing the time it takes to go from insight to impact," Gianchandani said. "Today's announcement expands the pathways for a wide range of institutions and teams to identify and overcome key bottlenecks."

NSF describes the program as guided by administration priorities to revitalize U.S. science and technology through fresh funding and infrastructure-sharing models. Design choices draw on input from think tanks, metascience researchers (scholars who study how science itself runs, including funding, publishing, and replication practices), congressionally chartered study commissions, and the wider scientific community.