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Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

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Published on: March 9, 2019

Bioinspired Nanofluidic Memristors Based on Polyelectrolyte Conformation for Synaptic Learning and in-Memory Logic

Jun Li¹, Bozhong Song¹, Yanbo Liang¹

¹Institute of Marine Science and Technology, School of Biomedical Engineering, Shandong University, Jinan, China.

Advanced Materials (Deerfield Beach, Fla.)

|June 12, 2026

Summary

This summary is machine-generated.

We developed a polyelectrolyte conformational nanofluidic memristor (PCM) for bioinspired computing. This device enables synaptic plasticity, neuromorphic learning, and in-memory logic on a single platform.

Keywords:

bioinspired computing ionic logic circuit memristor nanofluidic

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Area of Science:

Nanotechnology
Neuroscience
Materials Science

Background:

Neuromorphic and in-memory computing demand devices mimicking biological synapses using ionic dynamics.
Existing technologies often struggle to integrate information storage and processing efficiently.

Purpose of the Study:

To introduce a novel polyelectrolyte conformational nanofluidic memristor (PCM).
To demonstrate its capability for synaptic plasticity, neuromorphic learning, and in-memory logic.
To establish a bioinspired nanofluidic computing platform.

Main Methods:

Fabrication of a PCM using polyelectrolytes confined in graphene oxide nanochannels.
Utilizing electric-field-driven conformational transitions for device operation.
Implementing synaptic functions and logic operations on the PCM platform.

Main Results:

The PCM exhibits analog conductance tuning, a tunable switching threshold, and an ON/OFF ratio over 160.
Demonstrated rich synaptic functions: long-term potentiation/depression, multilevel memory, and symmetric weight updates.
Achieved 97.1% accuracy on MNIST dataset for neuromorphic learning and performed universal in-memory logic operations (OR, IMP, NAND).

Conclusions:

The PCM integrates synaptic plasticity and in-memory logic within a single aqueous platform.
This bioinspired nanofluidic approach enables scalable, brain-like ionic processors.
The technology paves the way for advanced neuromorphic and in-memory computing systems.