Project Grant 2435905
Award Date
6/15/25
Completion Date
5/31/27
Dollars Obligated
$500K
Federal Agency
Division of Information and Intelligent Systems
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Atlanta, GA 30318, USA
Similar Awards
This $375,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) aims to accelerate the discovery, design, and implementation of new engineered photonic materials, particularly photonic metamaterials, through a data-driven deep learning approach. The project, led by the Georgia Tech Research Corporation, will establish deep learning frameworks to construct photonic metamaterials, integrate information on tailorable optical...
This $299,039 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports the development of computational techniques to accelerate the simulation and design of elastic metamaterials. The 5-year research project, which commenced on June 15, 2025, aims to create a new computational framework for fast periodic homogenization of nonlinear elasticity and optimal design of elastic metamaterials with target...
This $499,999 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop a computational framework that accelerates the prediction and optimization of microstructures in additive manufacturing (AM) processes. The project involves designing novel graph neural network models that incorporate physical laws to enable faster, more accurate, and generalizable microstructure predictions. This...
This National Science Foundation (NSF) Mathematical and Physical Sciences (CFDA 47.049) project grant to the Georgia Tech Research Corporation (Georgia Tech) in the amount of $330,000 will support 5 years of theoretical and computational research, as well as educational and outreach activities, focused on the geometric and topological mechanics of flexible structures. The research will explore the design and characterization of flexible mechanical metamaterials, which are systems composed of...
This Project Grant award from the National Science Foundation Division of Civil, Mechanical, and Manufacturing Innovation provides $1,177,594 to support research titled "DMREF/GOALI/COLLABORATIVE RESEARCH: PHYSICS-INFORMED ARTIFICIAL INTELLIGENCE FOR PARALLEL DESIGN OF METAL MATRIX COMPOSITES AND THEIR ADDITIVE MANUFACTURING." The funding period is from September 1, 2021 to August 31, 2025. The research is being conducted under the NSF Engineering program (CFDA 47.041), which aims to...
The National Science Foundation (NSF) Division of Civil, Mechanical, and Manufacturing Innovation awarded a $503,167 Project Grant to the University of Southern California (USC) for the project titled "CAREER: EFFECTIVE CONTINUUM MODELING OF MECHANISM-BASED METAMATERIALS". Under this 5-year award, effective from July 1, 2023 to June 30, 2028, USC will conduct fundamental research to develop modeling tools for predicting the mechanical behavior of morphing metamaterials. Metamaterials...
This $199,040 Project Grant, awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), aims to develop new classes of computational algorithms that combine the benefits of direct computer simulations and the speed of machine learning predictions. The project, titled "XTRIPODS: HYBRID SCIENCE-MACHINE LEARNING SOLVERS FOR NANOPHOTONICS AND METAMATERIALS," will embed scientific knowledge into the machine learning...
This $500,001 Project Grant was awarded by the National Science Foundation (CFDA #47.070 - Computer and Information Science and Engineering) to the Texas A&M Engineering Experiment Station (Tees) to conduct research on advancing autonomous, materials-on-demand manufacturing capabilities through the convergence of manufacturing, AI, and materials science. The key objectives are to develop foundational principles for shape-constrained machine learning, effective handling of...
This $549,365 Project Grant awarded by the National Science Foundation (NSF) Division of Civil, Mechanical, and Manufacturing Innovation will support Virginia Polytechnic Institute & State University (Virginia Tech) in designing cellular mechanical metamaterials (CMMs) under the effects of fabrication-related material uncertainty. The key objectives are to develop a multi-scale computational framework investigating the relationship between component-scale properties and underlying...
This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CFDA 47.070) program aims to develop software frameworks that can efficiently serve and deploy machine learning models for a variety of AI-powered applications. The $600,000 award, spanning from October 2024 to September 2027, tasks the prime awardee, Georgia Tech Research Corporation, with creating agile mechanisms and policies to serve a family of AI models across...