Sustainable Photodegradation of Amoxicillin in Wastewater with a Nickel Aluminate and ZnO Heterosystem Oxides: Experimental and Gaussian Process Regression Modeling Studies DOI Open Access
Mohammed Kebir,

Rachida Bouallouche,

Noureddine Nasrallah

et al.

Catalysts, Journal Year: 2024, Volume and Issue: 14(12), P. 875 - 875

Published: Nov. 29, 2024

The wastewater generated by the pharmaceutical industry poses a risk to environment due undesirable characteristics such as low biodegradability, high levels of contaminants, and presence suspended solids, in addition load organic matter drugs other emerging products effluent. This study aims reduce impact pollution removing amoxicillin (AMO) antibiotics an pollutant. In this concept, two synthesized catalysts, NiAl2O4 ZnO, are sensitive oxides light energy. prepared materials were then characterized using X-ray diffraction, UV–vis solid reflectance diffuse, Raman spectroscopy, scanning electron microscopy, BET, ATR-FTIR spectroscopy. effects principal operating parameters under sunlight, namely, percentage mixture pH medium, initial concentration antibiotic studied experimentally determine optimal conditions for achieving degradation rate. results showed that photodegradation is higher at 6, with weight 50% both catalysts 1 g/L total catalyst dose. Then, effect AMO on reaction important influence process; rate decreases, increases. A 92% was obtained 10 mg/L 6. kinetic established first-order model Langmuir–Hinshelwood (LH) mechanism fit experimental data perfectly. success heterosystem photocatalysts sustainable energy effective removal, which can be extended treat pollutants. On hand, modeling introduced Gaussian process regression (GPR) predict sunlight heterogeneous ZnO systems. evaluation criteria GPR terms statistical coefficients errors show very interesting performance used. Where close one (R = 0.9981), small (RMSE 0.1943 MAE 0.0518). suggest has strong predictive power used optimize removal from wastewater.

Language: Английский

Performance evaluation of aminated multi-walled carbon nanotubes incorporated with green synthesized nanoparticles for toxic dyes sequestration from textile wastewater DOI Creative Commons
Titus Chinedu Egbosiuba,

Cynthia Chukwuemeka,

Jonah Chukwudi Umeuzuegbu

et al.

Water Resources and Industry, Journal Year: 2025, Volume and Issue: unknown, P. 100291 - 100291

Published: April 1, 2025

Language: Английский

Citations

0
Sustainable Photodegradation of Amoxicillin in Wastewater with a Nickel Aluminate and ZnO Heterosystem Oxides: Experimental and Gaussian Process Regression Modeling Studies DOI Open Access
Mohammed Kebir,

Rachida Bouallouche,

Noureddine Nasrallah

et al.

Catalysts, Journal Year: 2024, Volume and Issue: 14(12), P. 875 - 875

Published: Nov. 29, 2024

The wastewater generated by the pharmaceutical industry poses a risk to environment due undesirable characteristics such as low biodegradability, high levels of contaminants, and presence suspended solids, in addition load organic matter drugs other emerging products effluent. This study aims reduce impact pollution removing amoxicillin (AMO) antibiotics an pollutant. In this concept, two synthesized catalysts, NiAl2O4 ZnO, are sensitive oxides light energy. prepared materials were then characterized using X-ray diffraction, UV–vis solid reflectance diffuse, Raman spectroscopy, scanning electron microscopy, BET, ATR-FTIR spectroscopy. effects principal operating parameters under sunlight, namely, percentage mixture pH medium, initial concentration antibiotic studied experimentally determine optimal conditions for achieving degradation rate. results showed that photodegradation is higher at 6, with weight 50% both catalysts 1 g/L total catalyst dose. Then, effect AMO on reaction important influence process; rate decreases, increases. A 92% was obtained 10 mg/L 6. kinetic established first-order model Langmuir–Hinshelwood (LH) mechanism fit experimental data perfectly. success heterosystem photocatalysts sustainable energy effective removal, which can be extended treat pollutants. On hand, modeling introduced Gaussian process regression (GPR) predict sunlight heterogeneous ZnO systems. evaluation criteria GPR terms statistical coefficients errors show very interesting performance used. Where close one (R = 0.9981), small (RMSE 0.1943 MAE 0.0518). suggest has strong predictive power used optimize removal from wastewater.

Language: Английский

Citations

2