Mechanical tolerance of cascade bioreactions via adaptive curvature engineering for epidermal bioelectronics

• Main Authors: Wang, Ting, Lei, Qun-Li, Wang, Ming, Deng, Guoying, Yang, Le, Liu, Xijian, Li, Chunlin, Wang, Qi, Liu, Zhihua, Wang, Jianwu, Cui, Zequn, Kevin Goldio Utama, Ni, Ran, Chen, Xiaodong
• Other Authors: School of Materials Science and Engineering
• Format: Article
• Language: English
• Published: 2021
• Subjects: Science::Chemistry::Analytical chemistry; Cascade Reaction; Epidermal Biosensors
• Online Access: https://hdl.handle.net/10356/147124
• Institution: Nanyang Technological University

Epidermal bioelectronics that can monitor human health status noninvasively and in real time are core to wearable healthcare equipment. Achieving mechanically tolerant surface bioreactions that convert biochemical information to detectable signals is crucial for obtaining high sensing fidelity. In this work, by combining simulations and experiments, a typical epidermal biosensor system is investigated based on a redox enzyme cascade reaction (RECR) comprising glucose oxidase/lactate oxidase enzymes and Prussian blue nanoparticles. Simulations reveal that strain-induced change in surface reactant flux is the key to the performance drop in traditional flat bioelectrodes. In contrast, wavy bioelectrodes capable of curvature adaptation maintain the reactant flux under strain, which preserves sensing fidelity. This rationale is experimentally proven by bioelectrodes with flat/wavy geometry under both static strain and dynamic stretching. When exposed to 50% strain, the signal fluctuations for wavy bioelectrodes are only 7.0% (4.9%) in detecting glucose (lactate), which are significantly lower than the 40.3% (51.8%) in flat bioelectrodes. Based on this wavy bioelectrode, a stable human epidermal metabolite biosensor insensitive to human gestures is further demonstrated. This mechanically tolerant biosensor based on adaptive curvature engineering provides a reliable bio/chemical-information monitoring platform for soft healthcare bioelectronics.