journal article·2025-05-13

Liquid Interference Mitigation in Capacitive Sensors Using Cassie–Baxter State Based on Superhydrophobic Surfaces

Yifei Xiao, Ziyi Dai, Yu Wang, Zejian Yan, Yimeng Xu, Mingrui Wang, Ming Lei, Qingmeng Zhang, Kai Qian

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Abstract

Flexible capacitive sensors are essential for human-machine interaction and Industry 4.0, enabling applications from humanoid robotic skin to wearable healthcare devices. However, their accuracy is often compromised by liquid interference due to the stark dielectric contrast between air and water. This study presents a superhydrophobic modification of the dielectric layer via spray-coated surface-modified silica nanoparticles, achieving contact angles >150° and rolling angles <10°. The resulting Cassie–Baxter state enables both active (tilting-induced) and passive (compression-release) liquid removal mechanisms, effectively minimizing liquid-sensor contact. This approach demonstrates universal liquid resistance across diverse liquids, including beverages and corrosive solutions, and maintains stable performance under various humidity conditions. Using a dome-array structure as a demonstration, the modified sensor exhibits reliable pressure sensing performance with a detection range of 0–3 MPa and high sensitivity in the low-pressure region (3.601 × 10 –2 kPa –1 ). The sensor maintains consistent performance over 1000 cycles under repeated liquid exposure, demonstrating excellent durability and reliability. The practical utility of this approach is demonstrated through a custom-designed Morse code recognition system that maintains reliable signal processing in liquid-rich environments, while the sensor’s broader applicability is validated through stable operation under harsh industrial conditions, including acid, alkali, and salt spray exposure.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Advanced Fiber Optic Sensors · Surface Modification and Superhydrophobicity

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

Affiliations

School of Integrated Circuits

Shandong University

Joint Key Laboratory of the Ministry ofEducation, Institute of Applied Physics andMaterials Engineering, University of Macau, Avenida da Universidade, Taipa 999078, Macau, China

Department of Mechanical Engineering

University of Auckland

Department of Orthopaedics

Qilu Hospital of Shandong University

Funding

National Natural Science Foundation of China · Natural Science Foundation of Shandong Province

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