Rapid Quantitative Detection of Dye Concentration in Pt/TiO2 Photocatalytic System Based on RGB Sensing

This article presents an integrated strategy that couples high-efficiency photocatalytic degradation with low-cost, rapid detection to overcome the main drawbacks of conventional TiO<sub>2</sub>-based photocatalysts, including a weak visible-light response, rapid charge-carrier recombination, and reliance on expensive instrumentation for dye concentration detection. Platinum-decorated TiO<sub>2</sub> (Pt/TiO<sub>2</sub>) was prepared by photoreduction deposition, and systematic characterization confirmed the successful loading of zero-valent Pt nanoparticles onto the TiO<sub>2</sub> surface, significantly improving charge separation and extending absorption into the visible region. Methylene blue degradation was quantified under ultraviolet (UV) and simulated sunlight; radical-scavenging tests clarified the reaction pathway. In parallel, smartphone images of the reaction mixture were processed in ImageJto extract red-green-blue (RGB) values, which were related to dye concentration through a partial least-squares (PLS) model validated against reference UV-Vis data. Pt/TiO<sub>2</sub> removed 95.0% of methylene blue within 20 min of UV irradiation and 90.2% within 160 min of simulated sunlight-31.8% and 19.1% faster, respectively, than pristine TiO<sub>2</sub>. The RGB-based PLS model achieved a coefficient of determination (R<sup>2</sup>) of 0.961 for the prediction set. By integrating photocatalysis with smartphone-based colorimetry, the proposed method enables rapid monitoring of organic dyes concentration, providing an intelligent and economical platform for industrial wastewater treatment.

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Publication Details

Journal
Sensors
Published
2025-05-19
DOI
https://doi.org/10.3390/s25103195
Primary Topic
Biosensors and Analytical Detection
Type
article
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article

Rapid Quantitative Detection of Dye Concentration in Pt/TiO2 Photocatalytic System Based on RGB Sensing

Cuiyan Han, Baolin Zhu, Yang Liu, Cheng Guo et al.
Sensors
Biosensors and Analytical Detection
article

Rapid Quantitative Detection of Dye Concentration in Pt/TiO2 Photocatalytic System Based on RGB Sensing

Cuiyan Han, Baolin Zhu, Yang Liu, Cheng Guo, Fu Yang, Shuqi Liu, J. J. Cui, Ziao Wang
article en

Abstract

This article presents an integrated strategy that couples high-efficiency photocatalytic degradation with low-cost, rapid detection to overcome the main drawbacks of conventional TiO<sub>2</sub>-based photocatalysts, including a weak visible-light response, rapid charge-carrier recombination, and reliance on expensive instrumentation for dye concentration detection. Platinum-decorated TiO<sub>2</sub> (Pt/TiO<sub>2</sub>) was prepared by photoreduction deposition, and systematic characterization confirmed the successful loading of zero-valent Pt nanoparticles onto the TiO<sub>2</sub> surface, significantly improving charge separation and extending absorption into the visible region. Methylene blue degradation was quantified under ultraviolet (UV) and simulated sunlight; radical-scavenging tests clarified the reaction pathway. In parallel, smartphone images of the reaction mixture were processed in ImageJto extract red-green-blue (RGB) values, which were related to dye concentration through a partial least-squares (PLS) model validated against reference UV-Vis data. Pt/TiO<sub>2</sub> removed 95.0% of methylene blue within 20 min of UV irradiation and 90.2% within 160 min of simulated sunlight-31.8% and 19.1% faster, respectively, than pristine TiO<sub>2</sub>. The RGB-based PLS model achieved a coefficient of determination (R<sup>2</sup>) of 0.961 for the prediction set. By integrating photocatalysis with smartphone-based colorimetry, the proposed method enables rapid monitoring of organic dyes concentration, providing an intelligent and economical platform for industrial wastewater treatment.

SensorsVol. 25(10)
Nankai University (CN), Jiangsu Vocational College of Medicine (CN)
Clean water and sanitation
Openalex Percentile: Top 90%
Biosensors and Analytical Detection
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