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

• 成果类型: Article
• 署名作者: Robin, P.; Emmerich, T.; Ismail, A.; Nigues, A.; You, Y.; Nam, G. -H.; Keerthi, A.; Siria, A.; Geim, A. K.; Radha, B.; Bocquet, L.
• 署名单位: Sorbonne Universite; Universite PSL; Ecole Normale Superieure (ENS); Centre National de la Recherche Scientifique (CNRS); Universite Paris Cite; University of Manchester; University of Manchester; University of Manchester
• 刊物名称: SCIENCE
• ISSN/ISSBN: 0036-8863
• DOI: 10.1126/science.adc9931
• 发表日期: 2023-01-13
• 页码: 161-167
• 关键词: transport; potentiation; graphene

摘要

Fine-tuned ion transport across nanoscale pores is key to many biological processes, including neurotransmission. Recent advances have enabled the confinement of water and ions to two dimensions, unveiling transport properties inaccessible at larger scales and triggering hopes of reproducing 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 unveil two types of nanofluidic memristors depending on channel material and confinement, with memory ranging from minutes to hours. We explain how large time scales could emerge from interfacial processes such as ionic self-assembly or surface adsorption. Such behavior allowed us to implement Hebbian learning with nanofluidic systems. This result lays the foundation for biomimetic computations on aqueous electrolytic chips.