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PCL-TEST BED: THE AI MATERIALS AND MANUFACTURING PILOT FACILITY NODE (PCL-AIMMPF) -NSF PCL-TEST BED: THE ARTIFICIAL INTELLIGENCE FOR MANUFACTURING AND MATERIALS PILOT FACILITY (AIMMPF) PCL NODE THE ARTIFICIAL INTELLIGENCE FOR MANUFACTURING AND MATERIALS PILOT FACILITY IS ONE NODE OF A NATIONAL NETWORK OF PROGRAMMABLE, AUTONOMOUS LABORATORIES THAT CAN BE ACCESSED BY U.S. RESEARCHERS USING WEB APPLICATIONS. IT EMPOWERS THEM TO INVENT, DEPLOY, DE-RISK, AND USE ARTIFICIAL INTELLIGENCE (AI) TO MORE RAPIDLY DISCOVER AND DEPLOY NEW MATERIALS AND MANUFACTURING TECHNOLOGIES USING AUTONOMOUS RESEARCH WORKFLOWS OF PROGRAMMABLE EXPERIMENTS AND SIMULATIONS. THIS INVESTMENT IN WORLD-LEADING AI-POWERED LABORATORIES INCREASES ACCESS TO ADVANCED SCIENTIFIC EQUIPMENT, ACCELERATES SCALING OF BASIC RESEARCH INTO INDUSTRY APPLICATIONS, AND IS AN ASSET IN ATTRACTING AND TRAINING FUTURE GENERATIONS OF SCIENTISTS AND ENGINEERS IN DISCOVERING, DEVELOPING, AND USING AI-ACCELERATED RESEARCH TECHNOLOGIES AND METHODOLOGIES. IT ALSO CREATES A TEST BED FOR DEVELOPING COMMUNITY NORMS, BEST PRACTICES, AND FORMAL STANDARDS FOR AUTOMATED LABORATORIES, INCLUDING THE DEVELOPMENT OF NEXT-GENERATION KNOWLEDGE SYSTEMS THAT ENABLE PEOPLE AT DIFFERENT LEVELS OF EDUCATION TO BE INFORMED AND TO BENEFIT FROM TAXPAYER-FUNDED RESEARCH DATA. THE PROGRAMMABLE CLOUD LABORATORIES - AI MANUFACTURING AND MATERIALS PILOT FACILITY NODE (PCL-AIMMPF) INTEGRATES THE GEORGIA TECH ADVANCED MANUFACTURING PILOT FACILITY (AMPF) USER FACILITY FOR AI-DRIVEN MATERIALS AND MANUFACTURING RESEARCH WITH THE DUKE AUTOMATIC FLOWS FOR MATERIALS DISCOVERY INTEGRATED COMPUTATIONAL MATERIALS ENGINEERING (ICME) SOFTWARE LIBRARIES USING THE CONTEXTUALIZE CARTA KNOWLEDGE AND DATA MANAGEMENT PLATFORM TO EMPOWER U.S. RESEARCHERS TO INVENT, DEPLOY, DE-RISK, AND USE AI TO MORE RAPIDLY DISCOVER AND DEPLOY NEW MATERIALS AND MANUFACTURING TECHNOLOGIES USING AUTONOMOUS RESEARCH WORKFLOWS OF PROGRAMMABLE EXPERIMENTS AND SIMULATIONS. IN TOTAL, PCL-AIMMPF PROVIDES REMOTE AND ON-PREMISES ACCESS TO UNPRECEDENTED SELF-DRIVING RESEARCH INFRASTRUCTURE AND SOFTWARE. THE DEVELOPMENT OF THE PCL-AIMMPF NODE IS GUIDED BY EIGHT RESEARCH OBJECTIVES: 1) CREATE THE ABILITY TO PROGRAM RESEARCH WORKFLOWS FROM THE CLOUD AND BY AI AGENTS, 2) DEVELOP OPEN METADATA AND DATA STANDARDS FOR SELF-DRIVING LABS, 3) DEVELOP AN INNOVATIVE AI-ORCHESTRATED DIGITAL TWIN THAT USES LLMS TO ASSIST USERS WHO PLAN, MONITOR, AND ANALYZE THEIR RESEARCH GOALS, 4) BOOST AI ABILITIES TO TRANSLATE MATERIALS AND MANUFACTURING SCIENTIFIC QUERIES INTO AUTONOMOUS RESEARCH AND DEVELOPMENT WORKFLOWS, 5) PIONEER AI-AGENTS THAT CONTINUOUSLY OPTIMIZE THE PLANNING AND SCHEDULING OPERATIONS OF PCL-AIMMPF WORKFLOWS IN UNCERTAIN ENVIRONMENTS, 6) CREATE AND DEPLOY DATA ASSIMILATION AI-AGENTS THAT USE SENSORS FROM THE FACILITY TO ESTIMATE THE STATE OF THE SCIENTIFIC RESEARCH PROGRESS, 7) INCREASE THE PCL-AIMMPF EQUIPMENT AND SIMULATIONS CAPABLE OF USE IN AUTONOMOUS WORKFLOWS, AND 8) DEVELOP TECHNOLOGIES AND STANDARDS THAT ALLOW SCIENTIFIC WORKFLOWS FROM ONE NODE TO BE COMBINED WITH THOSE OF OTHERS TO FORM TRANS-NODAL RESEARCH PATHWAYS.?? 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.

Cooperative Agreement (B) · National Science Foundation · to Georgia Tech Research Corp (UEI EMW9FC8J3HN4) · data as of 2026-09-30

Source: USAspending.gov prime award transactions and FSRS subaward reports, as loaded by SpendQuery (data as of 2026-09-30). Amounts are obligations (money committed), not outlays. The official record on USAspending.gov ↗