Lab news

The U.S. National Science Foundation has funded COAST PCL, a four-year, $20 million award led by the University of California, Santa Barbara to build a national network of programmable cloud laboratories. Rutgers will receive approximately $4.5 million of that award, and our lab is helping lead the work here. The project is funded through the NSF Test Bed: Toward a Network of Programmable Cloud Laboratories program, run by the agency’s Directorate for Technology, Innovation and Partnerships. The four-year award began August 1, 2026; Rutgers announced it on August 6.

At Rutgers the effort is led by Adam Gormley together with Kostas Bekris (Professor and Chair of Computer Science). It joins two halves of the same problem: deciding what to test next, and getting a machine to carry that experiment out safely. Our team will develop and test the software, robotic procedures, and experimental workflows before they’re deployed at UC Santa Barbara for soft materials research.

The work starts with what we know best — discovering new polymers and soft materials, with applications in drug delivery, medical devices, and more sustainable plastics. It also expands the Rutgers Scientific Hub for Orchestrated Research and Experimentation (SHORE), and funds hands-on student opportunities including summer workshops on building robotics and AI systems.

A programmable cloud lab is a self-driving lab you don’t have to stand next to: a researcher without the right instruments nearby can design an experiment and have it run somewhere that does. Scientists still decide what to study and what the results mean — the robots take the repetitive parts.

Read the Rutgers announcement: Rutgers Scientists Are Building a Self-Driving Lab to Help Make Discoveries Faster.

Welcome to the new Gormley Lab website. We’re repositioning around our core differentiator: self-driving labs that close the loop between robotic synthesis, high-throughput characterization, and machine learning to discover bioactive polymers faster than human-led design.

More news — publications, people, and results — will follow as we migrate content from the previous site.

We’re excited to share the lab’s latest self-driving-lab result: Self-driving lab for the data-driven design of single-chain polymer nanoparticles, led by Alex Suponya with the whole team.

The platform runs the full Design → Build → Test → Learn loop on its own — robotic synthesis makes candidate polymers, high-throughput characterization measures them, and active learning decides what to make next. It’s a concrete step toward discovering bioactive polymers faster than human-led design can.

Congratulations to everyone who kept the loop turning on this one.

How do you actually build a self-driving lab? Our new tutorial in Digital Discovery — A user’s guide to your first self-driving liquid handling lab, led by Apostolos Maroulis with collaborators including the Webb lab — walks through it end to end: the hardware, the software, and the active-learning loop that ties them together.

The goal is to lower the barrier to entry so more labs can close the loop between automated experimentation and machine learning. Pairs naturally with our open tools and guides.

The lab came together this month to celebrate Dr. Gormley’s tenure and Presidential Fellowship. It was a chance to mark the milestone with the people who made it possible — the students, postdocs, and collaborators who keep the loop turning. On to what’s next.

We’re thrilled to share that Dr. Adam Gormley has been granted tenure and promoted to Associate Professor of Biomedical Engineering. Alongside the promotion, he was awarded a Presidential Fellowship for Teaching Excellence in recognition of his work with students in the classroom and the lab.

Thank you to everyone — past and present lab members, collaborators, and mentors — who has been part of this journey.

Congratulations to Jules Lee, whose master’s research — A fully automated platform for photoinitiated RAFT polymerization — is featured in Digital Discovery. The platform automates oxygen-tolerant polymer synthesis end to end, a key building block for the lab’s self-driving approach to biomaterials discovery.