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Harnessing Biological Nanopores for Sustainable Neuromorphic Computing: Toward Scalable, Biocompatible, and Energy-Efficient Neural Networks

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Harnessing Biological Nanopores for Sustainable Neuromorphic Computing: Toward Scalable, Biocompatible, and Energy-Efficient Neural Networks Artificial intelligence is reshaping our world, but its progress carries an escalating energy crisis. Inspired by the brain’s unmatched efficiency, ionic neuromorphic computing offers a path to sustainable hardware, uniting biocompatibility, energy efficiency, multi-charge carriers, and scalability. Recent demonstrations of ionic memristors and reservoir computing show promise, yet devices remain difficult to reproduce and poorly integrated. Biological nanopores offer a compelling solution: they are nanometer-scale, self-assembling, atomically uniform, and tunable by mutation. Their ability to display memristive or volatile rectifying behaviour positions them as natural candidates for neuromorphic hardware. However, the unresolved physical basis of their stochastic conductance gating remains a barrier for computation integration. To date, neither nanopores nor other ionic platforms have

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award

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SIGNED

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EU

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307958.88

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EUR