Cooperative Agreement DESC0024571

The Massachusetts Institute of Technology (MIT) was awarded a $100,000 Project Grant from the Department of Energy Office of Science to develop machine learning techniques for predicting the performance of tungsten alloy plasma facing components in fusion energy applications. The grant was awarded on September 1, 2022 under the Office of Science Financial Assistance Program (CFDA #81.049), with work to be completed by August 31, 2023. MIT will utilize the funding to assist the Office of...

The U.S. Department of Energy's Office of Science awarded a $876,564 Project Grant to the University of Massachusetts Lowell under the Office of Science Financial Assistance Program (CFDA 81.049). The funding will support a one-year research project focused on "MACHINE LEARNING-ENABLED MONITORING OF METALLIC SOLUTES VIA X-RAY ABSORPTION SPECTROSCOPY IN MOLTEN SALT FUSION BLANKETS". The project aims to develop advanced computational algorithms and data analytics capabilities to...

General Atomics was awarded a $376,789 Project Grant from the Department of Energy Office of Science under the Office of Science Financial Assistance Program (CFDA 81.049). The award will support the PROJECT ALF (AI LEARNS FUSION): SCIENCE DISCOVERY AND CONTROL WITH DATA DRIVEN MODELS project from September 1, 2021 through August 31, 2023. The project aims to advance science discovery and control using data-driven models through the development of artificial intelligence techniques applied to...

The federal Cooperative Agreement award DESC0025853 was granted by the U.S. Department of Energy's Office of Science Financial Assistance Program (CFDA 81.049) to the Massachusetts Institute of Technology (MIT) for the "FIRE COLLABORATIVE: ADVANCED PROFILE PREDICTION FOR FUSION PILOT PLANT DESIGN (APP - FPP)" project. The $2,347,609.00 award, effective January 1, 2025 through December 31, 2025, supports fundamental scientific research to advance U.S. energy, economic, and national...

This $265,965 Project Grant award from the National Science Foundation's (NSF) Technology, Innovation, and Partnerships program (CFDA 47.084) supports research and development by Nearstar Fusion Inc., a for-profit organization, on a new approach to fusion energy for grid-based electric power. The project aims to perform computational modeling, analytical calculations, and design work to de-risk and establish a point design for a "hypervelocity gradient field fusion" concept. This...

The U.S. Department of Energy (DOE) Office of Science awarded a $1,262,150.02 Project Grant to the Massachusetts Institute of Technology (MIT) to develop an open-source nuclear modeling ecosystem to support fusion pilot plant design. The award, which runs from September 1, 2024 to August 31, 2025, is funded under the Office of Science Financial Assistance Program (CFDA 81.049). This program supports fundamental scientific research across multiple disciplines, including nuclear physics and...

This $299,918 Project Grant award from the National Science Foundation (NSF) Office of Advanced Cyberinfrastructure, under the Computer and Information Science and Engineering program (CFDA 47.070), will fund the development of portable machine learning models to support nuclear physics experiments at the Facility for Rare Isotope Beams (FRIB) in Michigan. The project will create pre-trained machine learning models using self-supervised techniques that can be quickly adapted by FRIB users for...

This Cooperative Agreement award from the U.S. Department of Energy's Office of Science Financial Assistance Program (CFDA 81.049) provides $3,288,000.00 to the Massachusetts Institute of Technology (MIT) to generate rapid, high-fidelity bulk irradiated materials data to accelerate solutions for commercial fusion energy systems. The award, titled "FIRE COLLABORATIVE: RAPID HIGH-FIDELITY BULK IRRADIATED MATERIALS DATA GENERATION TO ACCELERATE SOLUTIONS FOR COMMERCIAL FUSION ENERGY...

This $2,250,000 Project Grant award from the Office of Advanced Cyberinfrastructure within the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program seeks to develop a software platform and infrastructure for training machine learning (ML) models at scale to predict the properties of molecular and materials systems. The key objectives are to: Establish a technological paradigm and software infrastructure for developing ML models capable of predicting...

The National Science Foundation awarded Avalanche Energy Designs Inc. a $274,890 Technology, Innovation, and Partnerships (CFDA 47.084) Project Grant to characterize the fusion gain factor Q for their Orbitron micro-fusion reactor technology. This Small Business Innovation Research (SBIR) Phase I project aims to use particle-in-cell code, experiments, and plasma loss mechanism analysis to optimize fusion gain factor modeling and enable mitigating solutions for future small-scale fusion reactor...