Pine cones may seem simple, but their ability to react automatically to changing humidity could inspire a new generation of smart materials.
Researchers at MIT have developed a new design system that helps engineers copy useful behaviors found in nature and turn them into 3D-printed materials.
Their approach could eventually lead to building materials that respond to weather, robotic devices that move without complicated electronics, and aircraft parts that change shape when conditions change.
The research was published in the Journal of the Mechanics and Physics of Solids.
The team demonstrated its approach using pine cones. When the air is dry, pine cone scales open, helping seeds escape and spread. When conditions become damp, the scales close, protecting the seeds from moisture.
Remarkably, the pine cone doesn’t need muscles, nerves or a brain to make this happen. Instead, its movement comes from the way its internal structure responds to water.
Changes in humidity affect tiny cellulose fibers inside the pine cone. Those changes influence larger groups of fibers and layers of tissue, eventually causing the entire scale to bend. In other words, a small change at the microscopic level produces visible movement at a much larger scale.
Engineers have long been interested in copying such abilities. But understanding a behavior in nature and successfully reproducing it in an artificial material are very different challenges.
MIT graduate student Lee Marom and his colleagues developed a mathematical framework to make that process more systematic. Rather than simply copying the appearance of a pine cone, their system identifies the underlying steps that produce its movement.
The framework breaks a natural structure into smaller building blocks and maps how each part responds to a stimulus such as humidity. It then finds artificial components that can reproduce those same relationships.
Importantly, the process continues all the way to manufacturing. Once a design has been mathematically checked, the system can generate specifications and instructions that can be used to 3D-print the material.
This could reduce the trial-and-error normally involved in developing new adaptive materials, potentially saving researchers time, computing power and the cost of unsuccessful prototypes.
The researchers also showed that biological ideas could be mixed and matched. They studied the humidity-driven bending of pine cones and the twisting behavior of wheat awns, the bristle-like structures found on certain grasses.
Using parts of both designs, they created a new artificial structure that twists in response to temperature. When they manufactured and tested it, the structure behaved as predicted.
The approach could eventually help engineers develop materials for soft robots, medical devices, wearable technology and buildings. One possibility is moisture-responsive roofing that could automatically adjust to help cool buildings.
The researchers now want to study biological systems with more complicated behaviors and incorporate artificial intelligence into the process.
Their long-term goal is especially ambitious: AI systems that can study how nature works, identify useful physical mechanisms, design new materials based on those principles and produce instructions for manufacturing them.
Nature, in effect, could become a vast library of engineering ideas—and something as ordinary as a pine cone could provide the blueprint for materials that automatically adapt to the world around them.
