DMREF: NSF-NSERC: Collaborative Research: Codesign of Highly Entangled Materials through the Lens of Network Science

Entangled materials—such as polymer networks, textiles, and steel-cable structures—are found across length scales and exhibit remarkable mechanical properties driven by both fiber properties and the complex ways fibers entangle and self-contact. However, their behavior remains difficult to predict and design due to the lack of simple models capturing their intricate geometries and physical interactions. This Designing Materials to Revolutionize and Engineer our Future (DMREF) project will address that gap by developing quantitative metrics of entanglement through experiments and microscopy across scales. These metrics will connect entanglement geometries to physical properties, enabling the creation of simplified digital network representations of complex entanglements. These representations will guide the design of future entangled materials with user-defined properties. The project will provide open-source tools and data to support scalable design and optimization of fabrics, textiles, and knits, particularly at industrial scales. Broader impacts include educational integration of network science across institutions and a public art exhibit that will focus on visualizing networks, aiming to raise awareness of network-science-driven materials engineering. The project will establish a closed-loop framework for describing entangled matter using physical networks, correlating structural features with mechanical performance, and using these insights for targeted design. It consists of three unified thrusts that combine theory, computation, and experimentation. To span multiple length scales, the team will use testbeds made of 3D-printed textile architectures and woven metamaterials. Quantitative mechanical measures of entanglement will be obtained both experimentally and numerically. This data will inform the development of network models in which filaments are converted into skeleton and contact networks with geometric and topological attributes. These models will then be used to optimize entanglement geometries for desired performance using graph neural networks and gradient-based refinements. The result will be new material prototypes with engineered entanglements and mechanical properties, along with a broadly applicable design methodology for entangled filament-based materials. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. NSF Award ID: 2523080 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Carlos Portela | Institution: Massachusetts Institute of Technology, CAMBRIDGE, MA | Award Amount: $499,581 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2523080 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2523080.html