A Monolithic Neuromorphic Device for In-Sensor Tactile Computing

To emulate the tactile perception of human skin, the integration of tactile sensors with neuromorphic devices has emerged as a promising approach to achieve near-sensor information processing. Here, we present a monolithic electronic device that seamlessly integrates tactile perception and neuromorphic computing functionalities within a single architecture, with synaptic plasticity directly tunable by tactile inputs. This unique capability stems from our engineered device structure employing SnO<sub>2</sub> nanowires as the conductive channel coupled with a pressure-sensitive chitosan layer ionic gating layer. The device demonstrates pressure-dependent memory retention and learning behaviors, effectively mimicking the enhanced cognitive functions observed in humans under stressful conditions. Furthermore, the integrated design exhibits potential for implementing bioinspired electronic systems requiring adaptive tactile information processing.

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Publication Details

Journal
The Journal of Physical Chemistry Letters
Published
2025-05-20
DOI
https://doi.org/10.1021/acs.jpclett.5c00583
Citations
4
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
2.92

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article

A Monolithic Neuromorphic Device for In-Sensor Tactile Computing

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4 citations
The Journal of Physical Chemistry Letters
Advanced Memory and Neural Computing
2.92
article

A Monolithic Neuromorphic Device for In-Sensor Tactile Computing

Jiahe Hu, Yang Lu, Wentao Xu, Yi Du, Shangda Qu, Hwa Sung Lee, Jiaxin Chen, Song Zhang, Jiaqi Liu, Jiangdong Gong
article en
4 citations

Abstract

To emulate the tactile perception of human skin, the integration of tactile sensors with neuromorphic devices has emerged as a promising approach to achieve near-sensor information processing. Here, we present a monolithic electronic device that seamlessly integrates tactile perception and neuromorphic computing functionalities within a single architecture, with synaptic plasticity directly tunable by tactile inputs. This unique capability stems from our engineered device structure employing SnO<sub>2</sub> nanowires as the conductive channel coupled with a pressure-sensitive chitosan layer ionic gating layer. The device demonstrates pressure-dependent memory retention and learning behaviors, effectively mimicking the enhanced cognitive functions observed in humans under stressful conditions. Furthermore, the integrated design exhibits potential for implementing bioinspired electronic systems requiring adaptive tactile information processing.

The Journal of Physical Chemistry LettersVol. 16(21)
Nankai University (CN), Hanyang University (KR)
Science and Technology Foundation of Shenzhen City, China Postdoctoral Science Foundation, Nankai University, Natural Science Foundation of Tianjin City, National Key Research and Development Program of China, National Science Fund for Distinguished Young Scholars
Affordable and clean energy
Openalex Percentile: Top 9%
Advanced Memory and Neural Computing
2.92
DOISourceOpenAlex
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