2607553
Cooperative Agreement
Overview
Grant Description
PCL-TEST BED: REVOLUTIONIZING AI-DRIVEN AUTONOMOUS EXPERIMENTATION FOR NEXT-GENERATION SEMICONDUCTOR SYNTHESIS (READINESS) -PCL-TEST BED: REVOLUTIONIZING AI-DRIVEN AUTONOMOUS EXPERIMENTATION FOR NEXT-GENERATION SEMICONDUCTOR SYNTHESIS (READINESS) ADVANCED ELECTRONIC AND QUANTUM MATERIALS (EQMS) ARE ESSENTIAL FOR MANY TRANSFORMATIVE TECHNOLOGIES RANGING FROM ARTIFICIAL INTELLIGENCE (AI) AND HIGH-PERFORMANCE COMPUTING TO ENERGY SYSTEMS AND NATIONAL SECURITY APPLICATIONS. SYNTHESIZING, MANUFACTURING, AND OPTIMIZING THESE MATERIALS, HOWEVER, REMAINS SLOW, COSTLY, AND HEAVILY DEPENDENT ON TRIAL-AND-ERROR EXPERIMENTATION, WHICH CONTRIBUTES TO INDUSTRY?S RELUCTANCE TO RAPIDLY ADOPT NEW MATERIALS SYSTEMS THAT COULD OFFER DRAMATIC PERFORMANCE ADVANTAGES. THIS PROJECT DEVELOPS A NEW AI-DRIVEN AUTONOMOUS MATERIALS SYNTHESIS PLATFORM THAT COMBINES ROBOTICS, SIMULATIONS, AND AUTOMATED EXPERIMENTS COORDINATED BY AI AGENTS TO DRAMATICALLY ACCELERATE THE REPRODUCIBLE PRODUCTION OF ADVANCED MATERIALS. THE PLATFORM WILL FUNCTION AS A ?SELF-DRIVING LABORATORY? CAPABLE OF AUTONOMOUSLY DESIGNING, TESTING, AND IMPROVING MATERIAL-SYNTHESIS PROCESSES WITH MINIMAL HUMAN INTERVENTION. BY INTEGRATING DIGITAL AND PHYSICAL WORKFLOWS, THE PROJECT WILL SHORTEN THE TIME REQUIRED TO MOVE FROM SCIENTIFIC DISCOVERY TO SCALABLE MANUFACTURING FOR NEXT-GENERATION EQMS. BEYOND ADVANCING SCIENTIFIC INNOVATION, THE PROJECT WILL STRENGTHEN U.S. LEADERSHIP IN SEMICONDUCTOR AND ADVANCED MANUFACTURING TECHNOLOGIES, SUPPORT WORKFORCE TRAINING IN AI-ENABLED MATERIALS SCIENCE RESEARCH AND DEVELOPMENT AND CREATE REMOTELY ACCESSIBLE TOOLS THAT WILL BROADLY BENEFIT RESEARCHERS, STUDENTS, TECHNOLOGISTS, AND INDUSTRY PARTNERS NATIONWIDE. THIS NSF PROGRAMMABLE CLOUD LABORATORY (PCL) NODE WILL ESTABLISH A CLOSED-LOOP, AUTONOMOUS AND CLOUD-BASED PLATFORM TO ENABLE RAPID, SCALABLE MANUFACTURING OF NEXT-GENERATION EQMS. BY LEVERAGING THE COMPLEMENTARY STRENGTHS OF THE COLLABORATING INSTITUTIONS ? RICE UNIVERSITY, SUNY POLY, AND THE UNIVERSITY OF TEXAS AT AUSTIN ? THE PROJECT ENSURES ACCESS TO A BROAD RANGE OF EXPERTISE AND STATE-OF-THE-ART FACILITIES. THE CORE INTELLECTUAL MERIT LIES IN DEVELOPING AND VALIDATING A SEAMLESS SYSTEM THAT INCORPORATES ROBOT-SUPPORTED, AUTONOMOUS MATERIAL SYNTHESIS AND CHARACTERIZATION INFRASTRUCTURE AND DIGITAL TWINS, ALL TIED TOGETHER BY A SHARED-DATA-INFRASTRUCTURE AND A SELF-IMPROVING AI AGENT. THE AI AGENT INCLUDES THREE SYNERGISTIC CLASSES OF AI TOOLS: THE SKILLS TOOLKIT, THE SEGMENTED LATENT PLANNER, AND THE TRACE-GOVERNED OPTIMIZER ? THAT WILL ENABLE THE AGENT TO REASON, PLAN, AND ADAPT WITHIN THE COMPLEX CONSTRAINTS OF REAL-WORLD MATERIALS SYNTHESIS LABORATORIES. THE CREATION OF DIGITAL TWINS THAT DYNAMICALLY ANTICIPATE OUTCOMES AND HELP THE AI AGENT DESIGN EFFICIENT, SAFE EXPERIMENTAL PROGRAMS REPRESENTS A SIGNIFICANT CONTRIBUTION TO CYBER-PHYSICAL MATERIALS SCIENCE. FURTHERMORE, APPLYING THIS AUTONOMOUS FRAMEWORK TO SYNTHESIZE CHALLENGING NEXT-GENERATION MATERIALS, SUCH AS 2D MATERIALS, COMPLEX OXIDES, AND DIAMOND THIN FILMS, WILL YIELD NEW INSIGHTS INTO THEIR FORMATION MECHANISMS AND PHASE SPACES, DIRECTLY ACCELERATING THE REALIZATION OF MATERIALS PERFORMANCES WITH TARGETED EQM PROPERTIES. THE PCL NODE WILL ALSO ADDRESS CRITICAL CHALLENGES IN REPRODUCIBILITY AND TRANSFERABILITY BY CREATING INTEROPERABLE DATA STANDARDS AND INTEGRATING LABORATORY-SCALE DISCOVERY WITH PILOT-SCALE MANUFACTURING ENVIRONMENTS. EXPECTED OUTCOMES INCLUDE ACCELERATED DEVELOPMENT OF NEXT-GENERATION EQMS WITH TARGETED FUNCTIONALITIES, NEW METHODOLOGIES FOR AUTONOMOUS SCIENTIFIC REASONING, AND BROADLY ACCESSIBLE DATABASES, SOFTWARE, AND WORKFLOWS FOR THE MATERIALS RESEARCH AND DEVELOPMENT COMMUNITY. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE PLANNED FOR THIS AWARD.
Awardee
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "TEST BED: TOWARD A NETWORK OF PROGRAMMABLE CLOUD LABORATORIES", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF25541
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Houston,
Texas
77005
United States
Geographic Scope
Single Zip Code
Related Opportunity
William Marsh Rice University was awarded
AI-Driven Autonomous Experimentation Next-Gen Semiconductor Synthesis
Cooperative Agreement 2607553
worth $4,977,740
from National Science Foundation in August 2026 with work to be completed primarily in Houston Texas United States.
The grant
has a duration of 4 years and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
The Cooperative Agreement was awarded through grant opportunity Test Bed: Toward a Network of Programmable Cloud Laboratories.
Status
(Ongoing)
Last Modified 8/25/26
Period of Performance
8/1/26
Start Date
7/31/30
End Date
Funding Split
$5.0M
Federal Obligation
$0.0
Non-Federal Obligation
$5.0M
Total Obligated
Activity Timeline
Additional Detail
Award ID FAIN
2607553
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Private Institution Of Higher Education
Awarding Office
491502 INNOVATION AND TECHNOLOGY ECOSYSTEMS
Funding Office
491502 INNOVATION AND TECHNOLOGY ECOSYSTEMS
Awardee UEI
K51LECU1G8N3
Awardee CAGE
0K379
Performance District
TX-07
Senators
John Cornyn
Ted Cruz
Ted Cruz
Modified: 8/25/26