ArticleScientific reports2026
Numerical analysis of a THz sensor for atmospheric pollutant detection in agricultural areas of Hail, Saudi Arabia.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
This paper presents a terahertz (THz) gas sensor based on a planar structure consisting of three cascaded spiral resonators incorporating graphene, black phosphorus (BP), and vanadium dioxide (VO[Formula: see text]). The integration of these advanced two-dimensional materials enhances both sensitivity and adaptability for gas detection. The Wave Concept Iterative Process method is employed to model the interactions with various gases, and a novel implementation enables extensive simulations that exhibit excellent agreement with theoretical predictions. To further optimize performance, a machine learning model is developed to predict sensitivity based on key material parameters, including the conductivities of graphene, BP, and VO[Formula: see text]. The model achieves its highest predictive accuracy for ammonia (NH[Formula: see text]), with an R[Formula: see text] of 0.991, a mean absolute error of 0.008, and a mean squared error of 0.00020 using an 80% training set. The proposed sensor exhibits sensitivities of 2.256, 2.371, 2.462, 2.413, and 2.391 THz/RIU for CH[Formula: see text], N[Formula: see text]O, NH[Formula: see text], CO[Formula: see text], and H[Formula: see text]S, respectively. Compared to existing designs, it offers superior sensitivity, room-temperature operation, and rapid response, thereby advancing THz gas sensing technology and enabling highly sensitive and adaptable detection for practical applications.
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