In the 24 years I’ve worked as a materials scientist, I’ve always been inspired by hierarchical patterns found in nature that repeat all the way down to the molecular level. Such patterns induce remarkable properties—they strengthen our bones without making them heavy, give butterfly wings their color, and make a spiderweb silk both durable and pliant.
What if we could engineer such properties directly into manufactured materials? This could remove the need for complicated manufacturing processes to create devices like stents, microprocessors, and batteries. And eventually, we may even be able to program some degree of intelligence directly into the materials that make up such devices, which could make new features and functionality possible.
In my research group at Caltech, I study new properties of materials that emerge when you take nanoscale building blocks and organize them into 3D structures known as architectures. I predict that architected materials—substances built from the nanoscale up to have useful properties—will eventually replace conventional materials, not only in science and engineering but in many areas of daily life.
Lately, advances in 3D printing and other forms of additive manufacturing have made it possible to organize micro- and nano-size building blocks of matter into complex structures with great precision. We can now make new materials from components that range from just a little larger than 100 atoms to several millimeters in size.
This means scientists can decouple properties that have historically been linked together. For example, strong materials are typically heavy, and insulating materials like dinnerware are often brittle. But when ceramics and glass are architected by replacing solid blocks of material with a structure of the same size built of small struts, they can deform and reform like a sponge.
And there’s more—architected materials can evolve in space and time in response to a pre-programmed trigger. They can morph into different shapes to respond or adapt to a new environment or a stimulus. They can be made to release objects by relaxing their grip when heated or break apart at designated locations when strained.
This essay is part of MIT Technology Review’s 2022 Innovators Under 35 package recognizing the most promising young people working in technology today. See the full list here or explore the winners in this category below.
Thanks to this built-in responsiveness, future materials could be made with some decision-making capabilities and adaptability. Intelligent materials may be able to automatically release precise amounts of medication, heal themselves when damaged, or perform logical operations when exposed to light. In fact, some architected materials have already incorporated new kinds of logic gates that respond to either mechanical or chemical stimuli.
One area where I see great potential involves using machine learning to predict new architectures for materials that can emulate computationally trained neural networks using light instead of digital input. Eventually, artificial neural networks could be integrated into architected physical materials to make decisions, eliminating the need to first convert the input into digital signals and then process them in computers. This means materials themselves could someday be made to recognize faces or objects, process language, and classify text or numbers.
To realize this vision, we will need new computational models that can accurately capture the mechanics and physics of the additive manufacturing process for an affordable price. Additional models must be able to perform diagnostics, in real time, to determine whether any defects that form will affect performance.
And as if designing, discovering, and demonstrating new material properties weren’t hard enough, we’ll then have to turn prototypes into technology and manufacture the materials at scale. These tasks represent a major challenge, in part because the models haven’t yet been developed.
Knowing there are many talented people working on these problems, I look forward to the day when we can create architected materials and devices imbued with the ability to make decisions on their own.
Julia R. Greer is a materials scientist at the California Institute of Technology, and was a 35 Innovators honoree in 2008 and a judge for this year’s competition.
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