Deep Neural-Assisted Flexible MXene-Ag Composite Strain Sensor with Crack Dual Conductive Network for Human Motion Sensing

作者：Junheng Fu, Zichen Xia, Haili Zhong, Xiangmou Ding, Yijie Lai, Sisi Li, Mengjie Zhang, Minxia Wang, Yuhao Zhang, Gangjin Huang, Fei Zhan, Shuting Liang, Yun Zeng, Lei Wang, Yang Zhao · 发表于：Materials · 年份：2025 · DOI：10.3390/ma18153537 · 被引用次数：4 · 研究领域：Advanced Sensor and Energy Harvesting Materials、MXene and MAX Phase Materials、Conducting polymers and applications

Developing stretchable strain sensors that combine both high sensitivity and a wide linear range is a critical requirement for health electronics, yet it remains challenging to meet the practical demands of daily health monitoring. This study proposes a novel heterogeneous surface strategy by in situ silver deposition on modified PDMS followed by MXene spray coating, constructing a multilevel microcrack strain sensor (MAP) using silver nanoparticles and MXene. This innovative multilevel heterogeneous microcrack structure forms a dual conductive network, which demonstrates excellent detection performance within GFmax = 487.3 and response time ≈65 ms across various deformation variables. And the seamless integration of the sensor arrays was designed and employed for the detection of human activities without sacrificing biocompatibility and comfort. Furthermore, by adopting advanced deep learning technology, these sensor arrays could identify different joint movements with an accuracy of up to 95%. These results provide a promising example for designing high-performance stretchable strain sensors and intelligent recognition systems.