journal article·2026-03-24

Ionic-Based Electrochemical Gas Sensors for Low-Cost, High-Sensitivity SO 2 Detection

Francisco Lagunas, Hacksung Kim, Ella Myslo, Nick Schimp, Zachary D. Hood, Jianlin Li

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Abstract

Sulfur dioxide (SO 2 ) is a toxic gas associated with adverse health and environmental effects that necessitate reliable monitoring techniques. Here, we report the development of an all-solid-state electrochemical sensor utilizing a lithium borate (Li 3 BO 3 ) solid electrolyte capable of subppm of SO 2 detection. While subppm of SO 2 sensing has been previously demonstrated in other solid-state electrolyte systems─such as stabilized zirconia, natrium super ionic conductors (NASICON) under mixed-potential conditions─here we establish Li 3 BO 3 as an alternative solid electrolyte enabling equilibrium potentiometric sensing in an all-solid architecture. This sensor demonstrates a detection limit of at least 0.25 ppm, surpassing the human-olfactory threshold and meeting the rigorous requirements for industrial and personal monitoring applications. The sensing mechanism relies on the formation of Li 2 SO 4 on the electrode surface, as evidenced by multimodal characterization techniques, including Raman spectroscopy, scanning electron microscopy (SEM), and scanning transmission electron microscopy (STEM). The strong linear correlation between the open-circuit potential (OCV) and the logarithm of SO 2 concentration between 0.25 and 2 ppm indicates that the response is Nernstian in nature.
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Research context

OpenAlex topics: Gas Sensing Nanomaterials and Sensors · Advanced Chemical Sensor Technologies · Analytical Chemistry and Sensors

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

Affiliations

Applied Materials Division

Argonne National Laboratory

Institute for Material Science and Engineering

Washington University in St. Louis

Department of Mechanical Engineering and Material Science

Center for Catalysis and Surface Science

Northwestern University

Chemical Sciences and Engineering Division

Department of Electrical and Computer Engineering

Princeton University

Funding

Laboratory Directed Research and Development

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