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Research Article | Open Access | Just Accepted

A bioinspired neuromorphic tactile system: Merging MXene nanosheet sensors and MXene quantum dots memristor

Xiangxiang Yang1,§Wei Li2,§Wenshan Qu1( )Lijuan Zhang5Meng Yuan2Junchuan Yang2Dongxue Li1Jiakuo Qiao1Zihan Guo1Jiawei Xie1Jinrong Zhang1Chao Yin1Kai Guo3( )Lin Bao4( )Zhixiang Gao1Lijuan Dong1Jinjin Zhao1( )

1 School of Chemistry and Chemical Engineering, Shanxi Province Key Laboratory of Microstructure Electromagnetic Functional Materials, Shanxi Datong University, Datong 037009, China

2 State Key Laboratory of Bioinspired Interfacial Materials Science, Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou 215123, China

3 Michigan State University, East Lansing, MI 48824, USA

4 State Key Laboratory of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications, Beijing 100876, China

5 Intelligence Technology of CEC Co., Ltd., Beijing 102209, China

§ Xiangxiang Yang and Wei Li contributed equally to this work.

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Abstract

Inspired by biological sensory processing, this study presents a bioinspired neuromorphic tactile system that synergistically integrates an MXene nanosheet-based sensor and MXene quantum dots (MQDs) based memristor. The MXene-based sensor achieves multimodal perception of pressure, weight, curvature, roughness, and temperature through a comprehensive optimization strategy involving sensitivity enhancement via a vacuum-assisted approach, mechanical reinforcement by mixing sodium alginate (SA) to form composite networks, and environmental stabilization through polyimide encapsulation. The memristor based on MQDs exhibits digital and analog resistive switching behaviour with a high switching ratio and wide resistance range, enabling synaptic plasticity for data storage and computation. Feature signals from the sensor are directly processed by an artificial neural network constructed with these memristors. This tactile system demonstrates high accuracy (> 90%) in recognizing objects with different attributes. This work sets out a feasible approach towards the construction of a neuromorphic tactile system for human-machine interfaces, wearable electronics, and soft robotics.

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Cite this article:
Yang X, Li W, Qu W, et al. A bioinspired neuromorphic tactile system: Merging MXene nanosheet sensors and MXene quantum dots memristor. Nano Research, 2025, https://doi.org/10.26599/NR.2026.94908337
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Received: 03 November 2025
Revised: 07 December 2025
Accepted: 11 December 2025
Available online: 11 December 2025

© The Author(s) 2025. Published by Tsinghua University Press.

This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0, https://creativecommons.org/licenses/by/4.0/)