A flexible and room-temperature operatable gas sensor for robotic olfaction: selective detection of formic acid via UV excitation
Year: 2026
Type: article
Abstract: Robotic olfaction requires gas sensors that are intrinsically safe, mechanically compliant, and capable of selective operation at room temperature. Here, we present a flexible and room-temperature operable gas sensor for formic acid (FA) detection based on a UV-assisted PAM/CA organohydrogel sensing layer. The sensing response is associated with FA adsorption, diffusion, dissociation in the local hydrogel environment, and interfacial electrochemical processes. Photocurrent and UPS measurements indicate that the UV effect should not be interpreted as semiconductor-like photogenerated carrier generation, but rather as UV-assisted physicochemical modulation of the hydrogel interface. The organohydrogel provides good conformability, environmental tolerance, and stable operation under bending deformation. By combining static UV excitation with dynamic UV-intensity modulation, the sensor achieves ppm-level FA detection and improved discrimination among homologous organic acids. Building on this platform, we develop a conformable electronic nose for robotic integration and demonstrate proof-of-concept FA leak inspection in a simulated factory scenario. This work provides a feasible system-level strategy for flexible, room-temperature gas sensing and robotic olfaction integration.
Source: npj Robotics
Authors: Shouwen Zhang, Wei Zhang, Ruixin Li, Bo Yang, Hanyang Ji, Zhenyu Yuan, Fanli Meng
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,990
Funders: National Natural Science Foundation of China, Natural Science Foundation of Hebei Province, Natural Science Foundation of Liaoning Province, Higher Education Discipline Innovation Project, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities
OpenAlex ID: W7165057599
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