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This illustration shows the nano-mechanical devices the researchers developed. Inspired by neurons, they can perform computing tasks with high energy efficiency.
Image Credit: Emily Theobald
(CC BY-NC-ND 3.0)
Scientific Frontline: Extended "At a Glance" Summary: Brain-Inspired Nanoscale Mechanics
The Core Concept: A new nanoscale computing platform uses the unique mechanical responses of soft polymers to perform functions like computing and memory in a single device, mimicking the behavior of biological neurons.
Key Distinction/Mechanism: Unlike conventional computing that separates processing and memory, this platform uses a super-thin film of a viscoelastic soft polymer (PDMS) sandwiched between two metal electrodes; as voltage is applied, the polymer compresses and "remembers" the applied force, accumulating charge until it fires like a biological neuron before returning to its original state.
Major Frameworks/Components:
- Bioinspired Computation: Modeled after biological systems (like the distributed nervous system of an octopus) that process information locally through physical changes without needing a central controller.
- Nanoscale Mechanical Computing: Executing calculations through physical transformations, such as movement and compression, at the nanometer scale.
- Viscoelastic Polydimethylsiloxane (PDMS): A soft polymer used as a "nano-spring" to balance adhesive forces between metal surfaces, allowing for controlled and reversible nanomechanical reconfiguration.
Branch of Science: Electrical Engineering, Computer Science, Materials Science, and Nanotechnology.
Future Application: Development of low-power edge computing devices, interactive medical and environmental monitoring systems, smart prosthetics that can process tactile data, and highly efficient, autonomous smart robots.
Why It Matters: This technology integrates complex computational functionalities into intrinsic material properties, drastically minimizing the required components and potentially leading to highly energy-efficient and compact systems that bypass the limitations of conventional computing platforms.
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| A researcher holds a chip containing hundreds of devices. Each contains a layer of viscoelastic polymer, only 2 nm in size. Photo Credit: Courtesy of the researchers (CC BY-NC-ND 3.0) |
MIT researchers have created a new computing platform that could be used to develop intelligent and adaptive next-generation electronics capable of simultaneously performing multiple functions, such as computing and memory, all within one extremely compact, energy-efficient device.
This 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 the way a structure changes when a force is applied.)
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 is 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 the 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."
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A microscope image of a chip to perform brain-inspired computing. The technology could be useful for applications on the edge, like wearable health devices.
Image Credit: Courtesy of the researchers
(CC BY-NC-ND 3.0)
Bioinspired Computation
Biological systems can leverage physical changes, such as motion or deformation, to process information efficiently and without needing access to a central controller.
For instance, an octopus has a highly distributed nervous system, 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 undergo 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 such as movement and compression.
While bioinspired mechanical computing platforms have been developed at the micro and macro scales, the MIT researchers shrank 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.
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 an ultrathin 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 irreversibly.
"The soft material 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 each other, 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.
The researchers used this performance to demonstrate an artificial neuron.
Brain-Inspired Information Processing
In the brain, each neuron accumulates an electrical charge incrementally 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 into its original state.
"We have this complex functionality, which is the basis of biological computing, all contained in one nanoscale device," Satterthwaite says.
Because computing and memory are incorporated within a single device with no need for external components, such as capacitors or complex circuitry, this platform can achieve high energy efficiency with a small footprint.
"The performance heavily 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 such as 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 plan to expand this work to further integrate sensing with computing and memory to realize nanomechanical computing matter with applications in intelligent and adaptive systems.
Funding: This work was funded in part by the US Defense Advanced Research Projects Agency (DARPA), the US 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.
Published in journal: Science Advances
Title: Viscoelastic nanomechanical devices for neuromorphic information processing
Authors: Peter F. Satterthwaite, Sarah O. Spector, Maxwell Conte, Teddy Hsieh, Eduard O. Bobylev, Srinidhi Venkatesh, Jeremiah A. Johnson, and Farnaz Niroui
Source/Credit: Massachusetts Institute of Technology | Adam Zewe
Edited by: Scientific Frontline
Reference Number: eng091626_01
