Underwater target detection is an important topic in the field of Marine technology, covering multiple scenarios such as scientific research (such as Marine biology and environmental monitoring), industrial (such as underwater surveillance of mining and oilfield extraction operations), and military (such as threat detection). For example, by monitoring the signals emitted by Marine life in specific waters, it is possible to classify populations, identify exotic species, and protect the balance of regional ecosystems. However, the effects of dielectric attenuation, signal interference and different water environment make the non-contact underwater target detection face great challenges.

In this study, a self-adhesive pressure sensor, which can be used for underwater target detection, is prepared by a hybrid configuration carbon nanotubes array, including array and non-array parts. Due to the dense tube contact between the array parts under pressure, it can achieve a weak pressure signal detection of 18 mPa underwater, and maintain 99.82% linearity in the pressure detection range of 18 mPa to 178 mPa. In addition, the non-array segment exhibits a shear adhesion strength of 23.24 N/cm2, allowing the sensor to remain stable on a carrier operating at 10 km/h. Combined with artificial neural network, the sensor can recognize different underwater targets, providing a new possibility for non-contact pressure detection and underwater target recognition.

On January 2, 2024, The results are published in Device, a journal of Cell Press, under the title "Underwater target detection using hybrid carbon nanotube self-adhesive sensors." Professor Xu Ming, School of Materials Science and Engineering, Huazhong University of Science and Technology, is the corresponding author of the paper, and Li Huajian, a doctoral candidate, Huazhong University of Science and Technology, is the first author.