上海科技大学知识管理系统

Transpiration-driven electrokinetic power generators (TEPGs) hold promising potential for intelligent chemical sensing applications, enabling the efficient identification and screening of organic solvents. Here, we report a novel TEPG-based chemical sensor using MoS2-doped cellulose filter paper for efficient detection of poplar solvents like water, alcohols, and methanol. TEPGs operate by leveraging capillary-driven transpiration to induce solvent flow through porous materials, leading to ion migration and the formation of electrical double layers (EDLs) at the solid-liquid interfaces. This process generates a potential difference, enabling the conversion of the mechanical transpiration energy into electrical signals. Integrated with machine learning algorithms and IoT technologies, the sensor achieves real-time classification of the solvents. This TEPG-CS system offers enhanced sensitivity, reliability, and operational adaptability, overcoming the limitations of the traditional detection methods. This work has broad potential for environmental monitoring, industrial applications, and biomedical fields, offering another pathway for advanced solvent detection and classification systems.