Neuromorphic ionic computing in droplet interface synapses

Li, Zhongwu; Myers, Sydney K.; Xiao, Jingyi; Li, Yuhao; Noy, Natasha; Leuski, Anton; Noy, Aleksandr

doi:10.1126/sciadv.adv6603

Neuromorphic ionic computing in droplet interface synapses

Journal Article · Wed Jul 23 00:00:00 EDT 2025 · Science Advances

DOI:https://doi.org/10.1126/sciadv.adv6603· OSTI ID:2589375

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Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
University of California, Santa Barbara, CA (United States)
Google Research, Mountain View, CA (United States)
University of Southern California, Los Angeles, CA (United States)
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); University of California, Merced, CA (United States)

Ionic devices with memory capabilities can emulate neural functionality, enabling neuromorphic computing and biomedical applications. In this study, we report an ionic spiking synapse based on aqueous droplet interface bilayer assembly. Under stepwise triangular voltages, the device displays coupled memcapacitive-memristive behavior, showing noncrossing pinched hysteretic I-V loops. This hysteretic ion dynamics can be regulated by modifying bilayer components, reconstituting protein channels, or adjusting droplet assembly configuration. Droplet interface synapses (DIS) exhibit fundamental neuromorphic behaviors such as paired-pulse facilitation/depression, spike rate–dependent plasticity, Hebbian learning, and short-term associative learning under classical conditioning. We also used reservoir computing with DIS to implement two learning algorithms: a classification algorithm that recognizes handwritten digits and a reinforcement learning algorithm that learns to play a board game of tic-tac-toe.

View Accepted Manuscript (DOE)

Research Organization:: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Sponsoring Organization:: USDOE Laboratory Directed Research and Development (LDRD) Program; USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Basic Energy Sciences (BES). Materials Sciences & Engineering Division (MSE)

Grant/Contract Number:: AC02-05CH11231; AC52-07NA27344

OSTI ID:: 2589375

Journal Information:: Science Advances, Journal Name: Science Advances Journal Issue: 30 Vol. 11; ISSN 2375-2548

Publisher:: American Association for the Advancement of Science (AAAS)Copyright Statement

Country of Publication:: United States

Language:: English

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