journal article·2021-04-27

Strain Sensor with High Sensitivity and Large Response Range Based on Self-Assembled Elastic-Sliding Conductive Networks

Haicheng Wang, Jinlin Liu, Haoao Cui, Yijian Liu, Junze Zhu, Hongfei Wang, Ge Song, Zhongli Li, Da Chen

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Abstract

Flexible electronics intensely pursues the development of new-generation electronic skin and human–machine interfaces. However, monitoring human motions with both large dynamic range and high sensitivity effectively remains a challenge for the wearable strain sensors. In this study, we proposed a flexible strain sensor based on an elastic-sliding mechanism with a self-assembled PDMS/MoS2/MWCNT structure. The dense MWCNT networks could wrap and bridge the solid lubricant MoS2 particles to form elastic-sliding conductive paths. Even under a tiny stretch, the lubricant MoS2 islands could separate to enhance the sliding effect of the MWCNT conductive networks. Based on this property, the gauge factor of the sensor dramatically increases as an exponential function of stretching force. The proposed strain sensor has high sensitivity with a large response range (gauge factor of 3528 around 55% strain), a detection limit as low as 0.1%, a fast response time of 100 ms, and excellent cycling stability. Particularly, the strain sensor exhibits different sensitivities under various prestretching states. In addition, signal patterns with distinct features have been acquired in different applications. Such comprehensive performance of the strain sensor is applicable for the full range of human motion detection and integration of next-generation wearable systems.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Conducting polymers and applications · Tactile and Sensory Interactions

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

Affiliations

College of Electronic and Information Engineering, Shandong University of Science and Technology, 266590 Qingdao, China

Funding

Taishan Scholar Project of Shandong Province · Shandong University · National Natural Science Foundation of China · Key Laboratory for Robot and Intelligent Technology of Shandong Province

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