@article{Fu2025, 
author = {Chuanjie Fu and Chao Rong and Bowei Zhang and Fu-Zhen Xuan},
title = {High-sensitivity omnidirectional recognition strain sensor based on two-dimensional materials},
year = {2025},
journal = {Nano Research},
volume = {18},
number = {6},
pages = {94907411},
keywords = {MXene, flexible strain sensor, omnidirectional strain detection, machine learned},
url = {https://www.sciopen.com/article/10.26599/NR.2025.94907411},
doi = {10.26599/NR.2025.94907411},
abstract = {Flexible strain sensors are essential in fields such as medicine, sports, robotics, and virtual reality but face challenges in achieving excellent sensing performance and accurate multi-directional detection simultaneously. To address this issue, we have developed a spider-web structured multi-directional flexible strain sensor using Ti3C2Tx (MXene) conductive ink and three-dimensional (3D) printing technology. Combined with a multi-class, multi-output neural network model algorithm, the sensor achieves signal decoupling from the sensor array, allowing for precise detection of strain direction and intensity. It exhibits good sensitivity (gauge factor ~ 26.3), a moderate sensing range (0%–10%), and high reliability (1000 stretching cycles). Using neural network algorithms, a four-unit spider-web sensor array achieves approximately 97% accuracy in identifying strain intensity and direction within the 0%–10% strain range under various surface stimuli. Additionally, it can track complex human motions, demonstrating significant potential in applications such as motion monitoring and human–machine interaction.}
}