Efficient Proton Rectification in Quasi-Solid-State Nanofluidic Diode Membrane for Ionic Signal Processing and Computing

Constructing ion channels to mimic the diode characteristics of protein channels in living organisms is crucial for realizing ionic signal transmission and brain-like computing with logical capabilities. Nonetheless, it is challenging to achieve unidirectional transport of protons due to their high mobility and small volume for the dimensions of most nanochannels (>0.5 nm). Herein, drawing inspiration from the architecture of human skin, composed of dry epidermis and wet dermis that features an inherent electrochemical ion gradient and asymmetric transport routes, we present a quasi-solid-state heterogeneous ionic diode membrane by integrating two layers of poly(vinyl alcohol)-based hydrogels, which synergize the intrinsic electrochemical gradient with asymmetric structure and functional groups. Such membranes exhibit a remarkable proton rectification ratio of 47, which can be further amplified to 65 in response to external pressure, representing the state-of-the-art. Experimental and theoretical results reveal that the difference in proton migration energy barriers at the heterogeneous membrane interface is the key reason for the unidirectional proton transport behavior. With this membrane, we have successfully simulated the signal transmission and computation between neuronal synapses by constructing voltage-adaptive ionic transistor devices. This work demonstrates a general route for designing a high-rectifying proton diode, enabling advanced functionalities in biosensing and neuromorphic computing.

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Publication Details

Journal
ACS Nano
Published
2026-01-21
DOI
https://doi.org/10.1021/acsnano.5c17577
Primary Topic
Nanopore and Nanochannel Transport Studies
Type
article
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article

Efficient Proton Rectification in Quasi-Solid-State Nanofluidic Diode Membrane for Ionic Signal Processing and Computing

Tianyun Jing, Yifan Guo, QH Zhang, Naijia Zhao et al.
ACS Nano
Nanopore and Nanochannel Transport Studies
article

Efficient Proton Rectification in Quasi-Solid-State Nanofluidic Diode Membrane for Ionic Signal Processing and Computing

Tianyun Jing, Yifan Guo, QH Zhang, Naijia Zhao, Lei Jiang, Kai Chen, Xi Wang, Zhen Zhang, Zhe Li
article en

Abstract

Constructing ion channels to mimic the diode characteristics of protein channels in living organisms is crucial for realizing ionic signal transmission and brain-like computing with logical capabilities. Nonetheless, it is challenging to achieve unidirectional transport of protons due to their high mobility and small volume for the dimensions of most nanochannels (>0.5 nm). Herein, drawing inspiration from the architecture of human skin, composed of dry epidermis and wet dermis that features an inherent electrochemical ion gradient and asymmetric transport routes, we present a quasi-solid-state heterogeneous ionic diode membrane by integrating two layers of poly(vinyl alcohol)-based hydrogels, which synergize the intrinsic electrochemical gradient with asymmetric structure and functional groups. Such membranes exhibit a remarkable proton rectification ratio of 47, which can be further amplified to 65 in response to external pressure, representing the state-of-the-art. Experimental and theoretical results reveal that the difference in proton migration energy barriers at the heterogeneous membrane interface is the key reason for the unidirectional proton transport behavior. With this membrane, we have successfully simulated the signal transmission and computation between neuronal synapses by constructing voltage-adaptive ionic transistor devices. This work demonstrates a general route for designing a high-rectifying proton diode, enabling advanced functionalities in biosensing and neuromorphic computing.

ACS NanoVol. 20(4)
University of Science and Technology of China (CN), Chinese Academy of Sciences (CN), Technical Institute of Physics and Chemistry (CN)
Openalex Percentile: Top 82%
Nanopore and Nanochannel Transport Studies
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Efficient Proton Rectification in Quasi-Solid-State Nanofluidic Diode Membrane for Ionic Signal Processing and Computing — Tianyun Jing, Yifan Guo, et al. · ACS Nano (2026) | TGRS Research Map | TGRS