“We discovered how to use mathematics and kinematics — how the individual constituents of a system move — in mechanical-electrical networks,” Harne said. “This allowed us to realize a fundamental form of intelligence in engineering materials by facilitating fully scalable information processing intrinsic to the soft material system.”
According to Harne, the material uses a similar ‘thinking’ process as humans and has potential applications in autonomous search and rescue systems, in infrastructure repairs and even in bio-hybrid materials that can identify, isolate and neutralize airborne pathogens.
“What makes humans smart is our means to observe and think about information we receive through our senses, reflecting on the relationship between that information and how we can react,” Harne said.
While our reactions may seem automatic, the process requires nerves in the body to digitize the sensory information so that electrical signals can travel to the brain. The brain receives this informational sequence, assesses it and tells the body to react accordingly.
For materials to process and think about information in a similar way, they must perform the same intricate internal calculations, Harne said. When the researchers subject their engineered material to mechanical information — applied force that deforms the material — it digitizes the information to signals that its electrical network can advance and assess.
The process builds on the team’s previous work developing a soft, mechanical metamaterial that could ‘think’ about how forces are applied to it and respond via programmed reactions, detailed in NatureCommunications last year. This earlier material was limited to only logic gates operating on binary input-output signals, according to Harne, and had no way to compute high-level logical operations that are central to integrated circuits.
The researchers were stuck, until they rediscovered a 1938 paper published by Claude E. Shannon, who later became known as the “father of information theory.” Shannon described a way to create an integrated circuit by constructing mechanical-electrical switching networks that follow the laws of Boolean mathematics — the same binary logic gates Harne used previously.
“Ultimately, the semiconductor industry did not adopt this method of making integrated circuits in the 1960s, opting instead to use a direct-assembly approach,” Harne said. “Shannon’s mathematically grounded design philosophy was lost in the sands of time, so, when we read the paper, we were astounded that our preliminary work exactly realized Shannon’s vision.”
However, Shannon’s work was hypothetical, produced nearly 30 years before integrated circuits were developed, and did not address how to scale the networks.
“We made considerable modifications to Shannon’s design philosophy in order for our mechanical-electrical networks to comply with the reality of integrated circuit assembly rules,” Harne said. “We leapt off our core logic gate design philosophy from the 2021 research and fully synchronized the design principles to those articulated by Shannon to ultimately yield mechanical integrated circuit materials — the effective brain of artificial matter.”
The researchers are now evolving the material to process visual information like it does physical signals.
“We are currently translating this to a means of ‘seeing’ to augment the sense of ‘touching’ we have presently created,” Harne said. “Our goal is to develop a material that demonstrates autonomous navigation through an environment by seeing signs, following them and maneuvering out of the way of opposing mechanical force, such as something stepping on it.”
Other authors of the paper include Charles El Helou, doctoral student in mechanical engineering at Penn State, and Benjamin Grossman, Christopher E. Tabor and Philip R. Buskohl from the US Air Force Research Laboratory.
Harne’s National Science Foundation Early Career Development Award and the US Air Force funded this research.