Formal Methods for Nature-Derived Material Design
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Marom-lmarom-smarchs-arch-2026-thesis.pdf
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Author(s)
Marom, Lee
Advisor(s)
Tibbits, Skylar
Buehler, Markus J.
Date Issued
May 2026
Publisher
Massachusetts Institute of Technology
Abstract
Natural materials achieve adaptive behavior through hierarchical organization across scales. Wheat awns drive seeds into soil through humidity cycles, nacre stiffens under impact, and Venus flytraps snap shut on contact. Biological material intelligence has motivated a tradition of bioinspired and biomimetic design, yet translation into engineered systems remains largely heuristic. What is missing is a formal translation framework that carries biological logic into engineered form while preserving physical consistency across scales. This thesis presents a category-theoretic compositional framework for verified naturederived material design. The framework defines a category of stimulus-response dynamical systems with natural and artificial subcategories, introduces a structure-preserving implementation functor from biological mechanics to engineered systems, and formalizes a machine-agnostic specification layer that compiles behavioral intent into executable fabrication programs. Instantiated on the hygromorphic pinecone hierarchy, the pipeline is implemented in Grasshopper as modular parametric scripts that preserve the compositional structure of the model. The resulting designs are fabricated by fused filament fabrication and tested against model predictions. The current implementation generates four actuator classes spanning two stimulus types and two kinematic responses. One actuator arises purely through composition of previously validated components. Compositionality functions here not only as a descriptive language but as a generative and verifiable method for nature-derived material design. It offers a concrete route for embedding multiscale reasoning within computational, generative, and physics-driven design workflows. It also serves as a symbolic scaffold for computational design as it turns to generative AI. The designer is no longer solely the author of artifacts, but the architect of the data structures and frameworks through which artifacts are composed and verified. What nature has composed, design can now compose with.
MIT Department
Massachusetts Institute of Technology. Department of Architecture
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