Matmerize To Develop Low-flammability Polymer Composite Materials With Advanced AI
KUALA LUMPUR, Nov 8 (Bernama) -- Matmerize Inc has announced its selection by the United States Department of Defense (DOD) for a Small Business Innovation Research (SBIR) contract aimed at advancing artificial intelligence (AI) methodologies for accelerating the design of novel low-flammability polymer composite materials.
In a statement, Matmerize said the transformative potential of this project will not only enhance fire safety for Navy ships and submarines, but will also find applications in a wide range of industries, including construction, aerospace, automotive and consumer products.
This award comes at the heels of another SBIR recently awarded to Matmerize by the National Science Foundation (NSF) to develop physics-informed and physics-enforced machine learning (ML) architectures to advance materials development.
Matmerize Director of Research Innovation, Huan Tran said this collaboration signified a major achievement in the pursuit of safer, lower-flammability polymer composites.
“We take great pride in spearheading the development of cutting-edge AI-driven solutions for low-flammability composite materials that not only meet rigorous ASTM testing standards but also address the vital safety requirements mandated for our Navy ships,” said Tran.
The company will collaborate with DOD to develop a Polymer Informatics capability using suitable curated data and advanced AI/ML techniques, aimed at the accelerated design of low-flammability polymer matrix composites that meet other critical mechanical and thermal performance targets needed by the Navy.
The flammability of polymer composites is quantified by a set of quantitative parameters, typically measured using highly standardised instruments/tests defined by the American Society for Testing and Materials (ASTM) and other agencies.
Desirable polymeric materials that meet the specific values of ASTM and non-ASTM standardised tests require an optimal combination of base polymers, functional additives, flame retardants, and processing conditions.
Key highlights of the contract include creation of a composite materials database with flammability and other relevant properties; as well as development of AI models trained on the database to predict the relevant properties for new composite formulations.
-- BERNAMA
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