Entanglement-driven responses through multiscale 3D-printed knits
Abstract
Filamentous entanglements such as textiles achieve resilience and toughness through topology rather than material composition alone. Yet architected materials rarely exploit dense interlooping and sliding contacts to achieve extraordinary physical behavior. While research across mechanics, architecture, and design has linked stitch structure to physical behavior, a predictive quantitative framework has remained elusive. Here we show that knitting can be reinterpreted as a general strategy for designing three-dimensional entangled solids with programmable mechanics. Using a geometrically exact description of each stitch and multimaterial 3D printing—a topology-agnostic fabrication approach—we create planar and volumetric knits whose loop parameters directly control stiffness, strength, and energy dissipation. The printed fabrics faithfully reproduce the nonlinear, anisotropic, and hysteretic responses of conventional machine-knitted textiles. We identify a simple normalization that collapses stress–strain curves across stitch geometries, yarn architectures, constituent materials, and length scales, unifying the behavior of traditional and 3D-printed knits on a single master curve. Extending the topology into the “Z” or stacking direction yields volumetric knits whose stiffness and dissipation can be tuned by imposed prestrain. Finally, we realize the same architecture from centimeters down to micrometers, culminating in, to our knowledge, the smallest knitted structure ever fabricated. By demonstrating that 3D-printed knits can be interpreted both as a traditional fabric composed of a single yarn and as an architected material with defined periodicity, this work establishes entangled filaments as a foundation for a class of material architectures whose mechanics are encoded in their topology.
Article Details
Journal Info
Proceedings of the National Academy of Sciences
National Academy of Sciences
Authors (8)
Bradley Cline
Department of Mechanical and Aerospace Engineering, University of Houston
Catherine Bai
Department of Mechanical and Aerospace Engineering, University of Houston
Sehui Jeong
Department of Mechanical Engineering, Stanford University
Ling Xu
Yue Wang
James U. Surjadi
Department of Mechanical Engineering, Massachusetts Institute of Technology
Carlos M. Portela
Department of Mechanical Engineering, Massachusetts Institute of Technology
Tian Chen
Department of Mechanical and Aerospace Engineering, University of Houston