Deep underwater, an octopus can camouflage its skin instantly without sending every micro-decision back to a central brain. Its tentacles do the thinking locally. Now, researchers at the Massachusetts Institute of Technology have translated that exact squishy, decentralized magic into a microscopic computing innovation. The newly designed nanoscale computing device uses soft, flexible polymers to process information within a single microscopic unit. Interestingly, the platform mimics the way biological brains calculate using physical movement. It shrinks complex electronic systems into an ultrathin, energy-efficient package that could advance smart robotics, wearable medical patches, and biocompatible sensors. Remembers like an octopus Inspired by the distributed nervous systems of biological organisms like octopuses, the technology uses soft polymer materials that compress and bounce back under voltage to mimic how brain neurons store and fire information. Building these functions directly into the material reduces the need for bulky external circuits and heavy power supplies. However, it was not a straightforward task. In earlier attempts, other engineers building mechanical computers at the nanoscale faced a physical barrier. When two metallic surfaces get too close, intense intermolecular adhesive forces snap them together permanently. The components stick, and the device breaks. To beat this issue, the MIT team inserted a razor-thin layer of polydimethylsiloxane (PDMS) between two metal electrodes. PDMS is a squishy, viscoelastic polymer. This nanoscale device uses three core components that work together to mimic biological computing. Metal electrodes receive incoming electrical signals and compress when voltage is applied. Sandwiched between them, a soft PDMS layer acts as a viscoelastic nano-spring, balancing adhesion forces so the electrodes can move reversibly without permanently sticking. The polymer’s gradual rebound creates a mechanical memory that retains a history of past applied forces over time. “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,” said Peter Satterthwaite, co-lead author. Charge accumulates over time. Once it hits a specific threshold, the device fires — just like a biological neuron — before relaxing to reset. Future uses in medical devices Biological neurons accumulate electrical signals until they reach a threshold, at which point they fire and transmit information. The MIT team’s device replicates this mechanism: applied voltage slowly compresses the polymer layer until it crosses a threshold, triggering a biological-style firing before relaxing to reset. Modern artificial intelligence consumes massive amounts of electricity because hardware continuously shifts data back and forth between separate memory banks and processor units. The MIT platform eliminates that pipeline entirely. Memory, sensing, and logic happen in one spot. Integrating memory and computation directly into a single nanoscale component reduces the need for extra circuitry or capacitors. This squishy, brain-inspired hardware opens the door for adaptive next-generation electronics, including low-power edge computing, smart prosthetics, wearable health monitors, and autonomous environmental sensors. Up next, the researchers plan to integrate sensing directly with memory and computing to create fully adaptive nanomechanical computing systems. The study was published in the journal Science Advances. Get the latest in engineering, tech, space & science - delivered daily to your inbox.Mrigakshi is a science journalist who enjoys writing about space exploration, biology, and technological innovations. Her work has been featured in well-known publications including Nature India, Supercluster, The Weather Channel and Astronomy magazine. If you have pitches in mind, please do not hesitate to email her.
MIT researchers create brain-inspired computing platform using soft polymers
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