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

## TL;DR

This paper introduces a fast and low-cost method to detect dye concentration using a Pt/TiO2 photocatalytic system and smartphone-based RGB sensing.

## Contribution

The novel integration of Pt/TiO2 photocatalysis with RGB-based smartphone colorimetry for rapid dye concentration monitoring.

## Key findings

- Pt/TiO2 removed 95.0% of methylene blue in 20 min under UV light and 90.2% in 160 min under simulated sunlight.
- The RGB-based PLS model achieved a high coefficient of determination (R2 = 0.961) for predicting dye concentration.
- The method outperformed traditional TiO2 in degradation speed and reduced reliance on expensive instrumentation.

## 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 TiO2-based photocatalysts, including a weak visible-light response, rapid charge–carrier recombination, and reliance on expensive instrumentation for dye concentration detection. Platinum-decorated TiO2 (Pt/TiO2) was prepared by photoreduction deposition, and systematic characterization confirmed the successful loading of zero-valent Pt nanoparticles onto the TiO2 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/TiO2 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 TiO2. The RGB-based PLS model achieved a coefficient of determination (R2) 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.