UMD Joins NSF's $400M AI Nanofabrication Initiative

The University of Maryland is part of a Virginia Tech-led team that has received a National Science Foundation award to build an AI-native, cloud-orchestrated self-driving nanofabrication node aimed at accelerating semiconductor research and education.

The project, "AI-Native, Cloud-Orchestrated Self-Driving Nanofabrication Node for Accelerating Semiconductor Research and Education," is one of 20 teams nationwide selected for NSF's new Test Bed: Toward a Network of Programmable Cloud Laboratories (NSF PCL Test Bed) initiative. The program supports the U.S. government's Genesis Mission and its "Achieving AI-Driven Autonomous Laboratories" challenge. The total investment across the 20 teams is $400 million, including $380 million in direct NSF funding matched by upwards of $20 million from the Astera Institute. Awardees will receive four years of funding to build out a national network of AI-enabled automated labs that can be programmed and accessed remotely.

The Virginia Tech-led team's node will focus on semiconductor fabrication, giving researchers and students around the country remote access to an AI-guided nanofabrication facility capable of running automated, self-directed experiments. It's part of a broader push across the PCL Test Bed network to speed up scientific discovery by pairing automated lab hardware with AI systems that can generate hypotheses, run experiments, and interpret results with researchers and students working alongside the automation at every step.

Ankur Srivastava, director of UMD's Semiconductor Initiative and Innovation and professor in the Department of Electrical and Computer Engineering, and Sudarsanam Suresh Babu, Clark Distinguished Chair and professor in the Department of Materials Science and Engineering, represent UMD on the project team.

The award adds to a growing portfolio of semiconductor-focused research at ISR and across the Clark School, as UMD continues to build its role in the national effort to strengthen U.S. leadership in AI-enabled science and semiconductor manufacturing.