MIT researchers have created a new computing platform that could be used to develop intelligent and adaptive next-generation electronics that can simultaneously perform multiple functions, like computing and memory, all within one extremely compact, energy-efficient device.
Such a platform opens opportunities for low-power edge computing applications, interactive medical and environmental monitoring systems, and smart robots.
The researchers accomplished this by leveraging the unique mechanical response of soft polymers at the nanoscale. A mechanical response is how a structure changes when a force is applied to it.
They harnessed this response to create tiny mechanical devices that use reconfigurable motion to remember and process information in a way that mimics how neurons behave in the brain.
Because key computing functions are built into the intrinsic properties of the soft polymer material, the number of components needed to perform the functions are minimized, enabling a compact and versatile platform for information processing.
"Complex and coupled nanoscale phenomena can provide tremendous opportunities for new approaches to information processing and integrating multiple functionalities, such as computing, sensing, and actuation. This could enable levels of energy efficiency, autonomy, and reconfigurability in nanoscale devices and systems that are challenging to achieve with conventional computing platforms," says Farnaz Niroui, an associate professor of electrical engineering and computer science (EECS), a member of the Research Laboratory of Electronics (RLE), and senior author of a paper on this device. "Here, we harness the intrinsic mechanical properties of materials to engineer device-level dynamics, such that the material building blocks play a much more active role in defining device functionality than conventionally considered."
She is joined on the paper by co-lead authors Peter Satterthwaite and Sarah Spector, EECS graduate students; as well as Jeremiah Johnson, the A. Thomas Guertin Professor of Chemistry at MIT; Maxwell Conte, a graduate student in the Department of Materials Science and Engineering; Teddy Hsieh, an EECS graduate student; postdoc Eduard Bobylev; and Srinidhi Venkatesh '25. The research appears today in Science Advances .
Bioinspired computation
Biological systems can leverage physical changes, like motion or deformation, to process information efficiently and without needing access to a central controller.
For instance, an octopus has a highly distributed nervous systems, with about two-thirds of its neurons spread throughout its arms. This allows the octopus to sense and process information about its environment locally and generate responses without requiring access to the central brain.
As an example, an octopus can mechanically change the color cells in its skin, enabling it to go through a rapid and context-specific camouflage process.
"You can think of an octopus as continuous computing matter, with computing, memory, sensing, and actuation distributed throughout its body," Niroui adds.
Inspired by such performance, the researchers sought to develop a platform that can compute using mechanical transformations at the nanoscale. In mechanical computing, calculations are performed through physical transformations like movement and compression.
While bioinspired mechanical computing platforms have been developed at the micro and macro scales, the MIT researchers shrunk their device to the nanoscale. At this scale, even minute mechanical transformations can lead to drastic changes in a material's properties. This can enable complex computing in an energy-efficient platform.
But achieving the reversible nanomechanical transformations needed for such computing is a fundamental challenge. When two surfaces come very close, they experience strong adhesive forces that pull the surfaces together, making them impossible to unstick.
To overcome this fundamental challenge, the researchers built a device with a super-thin film of the soft polymer polydimethylsiloxane (PDMS) sandwiched between two metal electrodes. This soft spacer balances the adhesive forces between the two metal surfaces, keeping the electrodes from crashing together in an irreversible way.
"The soft material in serves as a 'nano-spring,' to help balance the forces to achieve nanoscale mechanical reconfiguration in a controlled and reversible manner," Niroui explains.
When the researchers apply a voltage to the device, the two metal plates attract to one another, compressing the soft material and altering the electrical current flowing through the device.
"PDMS is viscoelastic, which means that after being compressed, it takes time to return to its original state. This allows the devices to dynamically remember the history of forces and voltages applied to them, and convert that history into an electrical response," says Satterthwaite.
They researchers used this performance to demonstrate an artificial neuron.
Brain-inspired information processing
In the brain, each neuron accumulates an electrical charge a little bit at a time until it reaches a threshold and fires, passing information to other neurons in the network.
The researchers' device mirrors this behavior. As voltage is applied over time, it accumulates stimulus as the electrodes gradually compress the PDMS. After crossing a threshold, it "fires" like a neuron before relaxing back to its original state.
"We have this complex functionality, which is the basis of biological computing, all contained in one nanoscale device," Satterthwaite says.
Since computing and memory are incorporated within a single device with no need for external components, like capacitors or complex circuitry, this platform can achieve high energy efficiency with a small footprint.
"The performance highly relies on the memory introduced using the soft polymer. We can intentionally engineer this over a large design space to meet the requirements of the desired applications," Spector says.
The device can also be compatible with biological systems, Spector adds. For instance, it could be useful in applications like smart prosthetics that can rapidly process tactile data or low-power wearable patches that collect and analyze health indicators in real-time.
In the future, the researchers want to expand this work to further integrate sensing with computing and memory to realize nanomechanical computing matter with applications in intelligent and adaptive systems.
This work was funded, in part, by the U.S. Defense Advanced Research Projects Agency (DARPA), the U.S. National Science Foundation (NSF), an MIT EECS MathWorks Fellowship, and the Netherlands Organization for Scientific Research. Device fabrication was carried out, in part, using MIT.nano facilities.
