Project Grant 2041577
- This $1,000,000 Cooperative Agreement award from the National Science Foundation's (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) program aims to accelerate R&D in the pharmaceutical industry through the development of streamlined machine learning algorithms for small data applications in advanced manufacturing. The project, awarded to Sunthetics Inc., seeks to save time and resources by up to 95% in lead optimization and route scouting during pre-clinical drug development by...
- This $271,320 National Science Foundation project grant supports research at Arizona State University to develop machine learning-assisted ultrafast physical vapor deposition of high-quality, large-area functional thin films. The goal is to apply machine learning algorithms to optimize thin film growth conditions and accelerate the development of thin films with targeted electronic and optical properties. This will enable faster and lower-cost manufacturing of functional oxides, chalcogenides...
- This project grant from the National Science Foundation (NSF) Engineering program (CFDA 47.041) supports the development of an artificial intelligence-assisted product design and production planning (AI-PDPP) system designed to improve manufacturing efficiencies. Awarded to the University of Oklahoma in May 2025 for $679,973, the three-year research initiative (completion date: April 30, 2028) focuses on integrating deep learning into three core manufacturing processes: product functional...
- The National Science Foundation awarded Lambda Function, Inc. a $256,000 Project Grant under the Engineering (47.041) federal grant program to develop an artificial intelligence system for autonomous numerical control programming for advanced manufacturing. The grant funded the creation of an AI system between December 1, 2021 and May 31, 2022 that automates the programming of computerized machine tools for complex manufacturing processes. The NSF Engineering program supports innovation and...
- This $485,752 Project Grant from the National Science Foundation's Engineering program (CFDA 47.041) supports collaborative research to develop a data-driven approach to microreaction engineering guided by autonomous robotic experimentation. Key products and services include the creation of an interdisciplinary knowledge framework to accelerate mechanistic reaction studies and synthesis process development for emerging materials and molecules with multi-stage chemistries. Researchers will...
- This Project Grant awarded by the National Science Foundation (CFDA 47.041 - Engineering) supports research into an innovative manufacturing technique for producing thin polymer films. The total award amount is $517,969.00 over the period from January 1, 2025 to December 31, 2027. The research aims to develop a comprehensive framework for the electrospray deposition process by integrating experiments, computational modeling, and artificial intelligence/machine learning methods. This will...
- The National Science Foundation (NSF) awarded a $273,706 Project Grant under the NSF Technology, Innovation, and Partnerships (CFDA 47.084) program to Matmerize, Inc., a for-profit organization, to develop a physics-informed/encoded polymer informatics platform to accelerate the development of advanced polymers and formulations. The project aims to transform the way polymeric materials are developed by adopting advanced artificial intelligence techniques to dramatically expedite the...
- The National Science Foundation awarded a $100,000 Project Grant to the University of Texas at Austin under the NSF Technology, Innovation, and Partnerships program (CFDA 47.084) to develop a scalable manufacturing process for three-dimensional nanostructured materials. The funding supports an I-Corps project to commercialize a lithographic nanomanufacturing technique using colloidal particles for volumetric patterning of photosensitive polymers. This bottom-up self-assembly approach aims to...
- The National Science Foundation (NSF) Directorate for Engineering (CFDA 47.041) awarded a $372,500 project grant to the Regents of the University of Minnesota to develop AI-enabled automated algorithms for solving complex mathematical optimization problems in chemical engineering. The 3-year research program will leverage state-of-the-art artificial intelligence and machine learning methods to automate the selection and configuration of optimization algorithms for problems arising in chemical...
- This National Science Foundation project grant of $272,581 supports research at Texas A&M Engineering Experiment Station to develop machine learning-assisted ultrafast physical vapor deposition of functional thin films. The goal is to produce high-quality, large-area functional thin films for applications in electronics, photonics, and energy industries. Researchers will apply machine learning algorithms to training data from experimental thin film growth and literature to optimize...
Sunthetics Inc. received a $256,000 Project Grant award from the National Science Foundation on April 1, 2021 to implement AI-enhanced machine learning for advanced electrochemical manufacturing. The funding supports Sunthetics' work under the NSF's Technology, Innovation, and Partnerships program (CFDA 47.084) through June 30, 2022. The grant enables Sunthetics to develop artificial intelligence and machine learning techniques to optimize electrochemical processes for manufacturing applications. By incorporating AI into manufacturing equipment, Sunthetics aims to accelerate product development, improve quality control, and enhance process efficiency. The project has the potential to advance science and engineering innovation leading to breakthrough manufacturing technologies. Work is being conducted in Temple, Texas, where Sunthetics is headquartered.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $0 | 3/7/22 | ||
| Not listed | $256.0k | 3/31/21 |