Long-term memory and synapse-like dynamics in two-dimensional nanofluidic channels

Autor: Robin, P., Emmerich, T., Ismail, A., Niguès, A., You, Y., Nam, G. -H., Keerthi, A., Siria, A., Geim, A. K., Radha, B., Bocquet, L.
Rok vydání: 2022
Předmět:
Zdroj: Science 379, 161-167 (2023)
Druh dokumentu: Working Paper
DOI: 10.1126/science.adc9931
Popis: Fine-tuned ion transport across nanoscale pores is key to many biological processes such as neurotransmission. Recent advances have enabled the confinement of water and ions to two dimensions, unveiling transport properties unreachable at larger scales and triggering hopes to reproduce the ionic machinery of biological systems. Here we report experiments demonstrating the emergence of memory in the transport of aqueous electrolytes across (sub)nanoscale channels. We unveiled two types of nanofluidic memristors, depending on channel material and confinement, with memory from minutes to hours. We explained how large timescales could emerge from interfacial processes like ionic self-assembly or surface adsorption. Such behavior allowed us to implement Hebbian learning with nanofluidic systems. This result lays the ground for biomimetic computations on aqueous electrolytic chips.
Databáze: arXiv
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