This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports a collaborative research effort between Georgia Southern University and the University of Texas at Austin to design novel bio-based thermoset materials. The key products or services to be delivered include: High-throughput production and characterization of bio-based monomers derived from microbial triglycerides, with the goal of developing thermosets with...
The National Science Foundation (NSF) Division of Materials Research awarded a $262,500 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) to the Georgia Tech Research Corporation (Georgia Tech) for the "DMREF/Collaborative Research: Active Learning-based Material Discovery for 3D Printed Solids with Locally-Tunable Electrical and Mechanical Properties" project. This multi-disciplinary effort aims to establish an active learning approach to rapidly...
This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program provides $273,291 to the University of California, Santa Barbara to develop computational tools that combine machine learning and scientific computing for the exploration and prediction of polymer systems. The goal is to accelerate the discovery of new materials and provide a framework for computationally costly problems across various scientific domains. The research...
This $250,000 National Science Foundation project grant will support research at the University of Massachusetts Boston and the University of California-Santa Barbara to advance machine learning techniques for predicting the behavior of dynamic materials. Jason Green of UMass Boston and Igor Mezic of UC Santa Barbara will combine machine learning and physical theory methods to create new approaches for designing functional materials with tailored optical, mechanical, or photonic properties on...
This $420,887 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences Program (CFDA 47.049) supports the development of a specialized biomaterial for efficient and sustainable degradation of plant biomass. The University of Missouri System, the prime awardee, will immobilize a multi-enzyme system including cellulases, a lipase, and a protease within a metal-organic material scaffold. This 5-in-1 biocatalyst will rapidly break down the complex plant...
This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program, CFDA 47.049, provides $310,000 to Arizona State University to develop new computational algorithms for identifying critical microstructural features that influence material properties. The goal is to create a more efficient and explainable approach to material design, particularly for disordered or random structures found in composites, biological systems, and climate modeling. The...
This is a $675,234 Project Grant awarded on August 1, 2024 by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (MPS) program (CFDA 47.049). The grant recipient is the Texas A&M Engineering Experiment Station (Tees), a state government agency and institute of higher learning. The grant will fund research to develop a new class of "shape-morphing" polymer materials that can transform their shape in response to temperature changes, without requiring...
This $254,856 federal Project Grant award from the National Science Foundation (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports data-intensive and computational research and education at the University of Illinois. The project aims to develop a new machine learning framework for the inverse design of sequence-defined macromolecules that can self-assemble into targeted morphologies and properties. The research will leverage generative deep learning models to predict the...
The National Science Foundation (NSF) awarded a $2,574,835 Project Grant under its Integrative Activities program (CFDA 47.083) to the University of Illinois at Urbana-Champaign. The award supports the acquisition of an automated, high-throughput system for the combinatorial design and development of complex polymer systems. This state-of-the-art system integrates component dispensing, mixing, and processing with high-throughput rheological, optical, and thermal characterization of materials....
This $640,000 Project Grant award from the National Science Foundation's (NSF) Division of Chemistry, under the Mathematical and Physical Sciences (CFDA 47.049) Federal Grant Program, supports a collaborative research effort between Professors Wooley and Darensbourg of Texas A&M University. The objective is to develop sustainable synthetic methodologies that harness the chemical diversity of natural products to produce next-generation macromolecular materials. The proposed work aims to...
This $285,435 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports a collaborative research effort between Georgia Southern University and the University of Texas at Austin. The goal is to develop a novel machine learning-assisted materials design cycle for creating bio-based thermoset materials with designer properties. The key products to be delivered include:
High-throughput production and characterization of novel bio-based monomers derived from microbial oils.
Development of data-driven models to predict the relationship between monomer chemical composition and material properties like glass transition temperature, crosslink density, and storage modulus.
Incorporation of machine learning to enhance the materials design process and enable the prediction of optimal starting molecules to achieve desired performance targets.
This research aims to establish sustainable approaches for advanced materials production while providing training opportunities for undergraduate students across disciplines. The project period runs from June 1, 2025 to May 31, 2028.