journal article·2025-01-01Open access

Resistive flexible pressure sensor based on AgNWs–MXENE sponge for robot skin

Xiaoli Wang, Shuai Liu, Weidong Kang, Yanan Zhang, Hairong Kou

AIP Advances· Volume 15· Issue 1

Abstract

With the rapid development of electronic devices, flexible pressure sensors have been widely used in many fields such as robot skin and wearable devices. However, designing a flexible pressure sensor with high sensitivity, a wide detection range, and easy preparation remains a formidable challenge. In this study, high-elastic sponge is selected as the base material, and silver nanowires (AgNWs) and two-dimensional transition metal carbides (MXENEs) are used as conductive materials. At the same time, AgNWs and PI tape are used as the electrode layer and encapsulation layer, respectively. A resistive flexible pressure sensor based on AgNWs–MXENE sponge is successfully prepared using sandwich encapsulation, and a series of performance tests and practical application tests are carried out on it. The test results show that the sensor has a wide detection range (0–1000 kPa). When the concentration of AgNWs–MXENE is 6%, the sensitivity of the prepared sensor reaches the highest value. Under the pressure of 0–2 kPa, it has a high sensitivity of 0.4901 kPa−1, as well as good response time (100 ms), good stability, and repeatability. It can also accurately detect the tiny and large pressures generated by activities such as pressing, making sounds, swallowing, and bending. This is of great significance for the accurate operation of robots, the functional optimization of wearable devices, and the improvement of the accuracy of health monitoring, and it has broad application prospects in the fields of robot skin, wearable electronic devices, health monitoring, and human–machine interaction.
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Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Gas Sensing Nanomaterials and Sensors · Conducting polymers and applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Jinxi Industries Group Co., Ltd. 1 , Taiyuan 030024,

Fourth Representative Office in Taiyuan Region 2 , Taiyuan 030000,

Shanxi Provincial Key Laboratory of Intelligent Sensing and Multi-Dimensional Information Processing, Taiyuan University 3 , Taiyuan 030032,

Funding

The Natural Youth Science Foundation of Shanxi Province

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