Experimental and modeling study of visible light responsive photocatalytic oxidation (PCO) materials for toluene degradation

对可见光响应型光催化氧化(PCO)材料降解甲苯进行实验和建模研究

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Abstract

Only limited research has examined the development and application of visible light responsive photocatalytic oxidation (PCO), although such materials have great potential for mitigating concentrations of volatile organic compounds (VOCs) when applied to building surfaces. This study evaluates the performance and characteristics of a visible light responsive photocatalyst, specially, a co-alloyed TiNbON compound with a band energy of 2.3 eV. The PCO material was developed using urea-glass synthesis, characterized by scanning electron microscopy (SEM), diffuse reflectance spectra (DRS), powder X-ray diffraction (PXRD), and Brunauer-Emmett-Teller (BET) methods, and VOC removal efficiency was measured under visible light for toluene (1-5 ppm) at room temperature (21.5°C) and a range of relative humidity (RH: 25 to 65%), flow rate (0.78 to 7.84 cm/s), and irradiance (42 to 95 W/m(2)). A systematic parametric evaluation of kinetic parameters was conducted. In addition, we compared TiNbON with a commercial TiO(2)-based material under black light, estimated TiNbON's long-term durability and stability, and tested its ability to thermally regenerate. Using mass transfer and kinetic analysis, three different Langmuir-Hinshelwood (LH) type reaction rate expressions were proposed and evaluated. A LH model considering one active site and competitive sorption of toluene and water was superior to others. The visible-light driven catalyst was able to remove up to 58 % of the toluene, generated less formaldehyde than the commercial TiO(2), could be fully regenerated at 150°C, and had reasonable durability and stability. This evaluation of TiNbON shows the potential to remove VOCs and improve air quality for indoor applications. Further research is needed to evaluate the potential for harmful by-products, to identify optimal conditions, and to use field tests to show real-world performance.

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