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<p>Water contamination caused by pharmaceutical pollutants is a growing environmental concern. Caffeine, a widely consumed psychoactive substance, has been identified as an emerging contaminant due to its persistence in aquatic environments and resistance to conventional wastewater treatment methods. In this study, the photocatalytic degradation of caffeine was investigated using silver-doped titanium dioxide (A-TO) nanoparticles under UV-A irradiation. The 0.5 A-TO nanocatalyst was synthesized via an impregnation method and characterized using X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR-ATR), scanning electron microscopy (SEM–EDS), and diffuse reflectance spectroscopy (DRS). Photodegradation experiments demonstrated that 0.5% A-TO achieved a 95% degradation rate of caffeine within 120&#xa0;min, outperforming pure TiO<sub>2</sub>. The enhanced efficiency is attributed to improved charge carrier separation and reduced electron–hole recombination due to Ag doping. Kinetic modeling confirmed that the photodegradation follows a pseudo-first-order reaction. Additionally, scavenger studies identified hydroxyl radicals (OH<sup>·</sup>) and superoxide radicals (O<sub>2</sub><sup>·</sup>⁻) as the primary reactive species responsible for caffeine degradation. Total organic carbon (TOC) analysis revealed a 72% mineralization rate, indicating effective breakdown of caffeine into less harmful byproducts. A phytotoxicity test using lentil seedlings confirmed the environmental safety of the treated water, with the germination index increasing from 32.81% (high toxicity) to 91.67% (non-toxic) after photocatalysis. Finally, a decision tree coupled with bootstrap aggregation (DT_Bootstrap) was employed to optimize process parameters, with a MATLAB-based interface developed for predictive modeling. These findings highlight the potential of A-TO as an efficient photocatalyst for pharmaceutical pollutant remediation in water treatment applications.</p>

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Efficient degradation of caffeine using silver-doped TiO2 photocatalyst: kinetics, mechanism, and process optimization via decision tree modeling

  • 期刊论文

  • 发表日期：

    2026年1月8日

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  • H. Hafsa,
  • N. Nasrallah,
  • S. Zeghbib,
  • M. Kebir,
  • H. Tahraoui,
  • S. Lekmine,
  • A. Amrane,
  • A. Aymen Assadi,
  • F. Fadhillah,
  • F. Abdulraqeb Ahmed Ali

摘要

Water contamination caused by pharmaceutical pollutants is a growing environmental concern. Caffeine, a widely consumed psychoactive substance, has been identified as an emerging contaminant due to its persistence in aquatic environments and resistance to conventional wastewater treatment methods. In this study, the photocatalytic degradation of caffeine was investigated using silver-doped titanium dioxide (A-TO) nanoparticles under UV-A irradiation. The 0.5 A-TO nanocatalyst was synthesized via an impregnation method and characterized using X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR-ATR), scanning electron microscopy (SEM–EDS), and diffuse reflectance spectroscopy (DRS). Photodegradation experiments demonstrated that 0.5% A-TO achieved a 95% degradation rate of caffeine within 120 min, outperforming pure TiO2. The enhanced efficiency is attributed to improved charge carrier separation and reduced electron–hole recombination due to Ag doping. Kinetic modeling confirmed that the photodegradation follows a pseudo-first-order reaction. Additionally, scavenger studies identified hydroxyl radicals (OH·) and superoxide radicals (O2·⁻) as the primary reactive species responsible for caffeine degradation. Total organic carbon (TOC) analysis revealed a 72% mineralization rate, indicating effective breakdown of caffeine into less harmful byproducts. A phytotoxicity test using lentil seedlings confirmed the environmental safety of the treated water, with the germination index increasing from 32.81% (high toxicity) to 91.67% (non-toxic) after photocatalysis. Finally, a decision tree coupled with bootstrap aggregation (DT_Bootstrap) was employed to optimize process parameters, with a MATLAB-based interface developed for predictive modeling. These findings highlight the potential of A-TO as an efficient photocatalyst for pharmaceutical pollutant remediation in water treatment applications.