MIT researchers have developed a mathematical framework that translates biological movements into manufacturing code for 3D-printed adaptive materials. The system maps hierarchical mechanics in organisms directly into engineered designs.
Lee Marom, an MIT graduate student in mechanical engineering and architecture, led the study published in the Journal of the Mechanics and Physics of Solids. Co-authors include MIT faculty members Markus Buehler, Gioele Zardini, and Skylar Tibbits.
Translating natural hierarchies
Pine cones open in dry conditions and close in damp ones through structural interactions spanning microscopic cellulose fibers, fiber groupings called laminas, and tissue layers. The framework uses category theory, a mathematical method for composing complex systems from smaller parts, to map how a stimulus drives responses across each physical scale. It assigns synthetic counterparts to each biological building block, ensuring transitions between hierarchical layers remain mathematically valid.
The framework extends previous work from Buehler's laboratory, which used category theory to evaluate hierarchical materials and prototype molecular-scale mechanics in 3D-printed models. The new setup connects multiscale biological mechanics directly to fabrication code for additive manufacturing.
Actuator demonstration
To demonstrate the system, the researchers mapped humidity-driven bending behavior from pine cones and twisting behavior from wheat awns into distinct sets of building blocks. By combining components from both models, the team designed and fabricated a 3D-printed actuator that twists in response to temperature shifts without requiring new design work.
The research team plans to integrate artificial intelligence models into the pipeline to identify additional adaptive material designs. Funding for the study came from the MIT Lemelson Engineering Fellowship, Singapore DSO National Laboratories, and the MIT Generative AI Impact Consortium.
