Optimization of the indole photodegradation on supported TiO2: influences of temperature, concentration, TiO2 amount and flow rate

Merabet, Smail; Schneider, M.; Robert, Didier; Benkhanouche, Smail; Bouhelassa, Mohammed; Weber, J.V.

doi:10.2166/wst.2008.430

Cited by 6 publications

(4 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The datasets employed for BPANN modelling were generated using a central composite design (CCD) and Box-Behnken experimental design (BBD), as represented in Eqn (1). 24,27,28 The CCD-generated datasets consisted of 20 treatment combinations of UV light intensity, stirring speed and indole concentration, and were used in the photocatalytic degradation of indole. Also based on the CCD dataset, 31 treatment combinations of initial dye concentration, light intensity, flow rate and reaction time were employed in the photodegradation of anthraquinone dye.…”

Section: Data Descriptionmentioning

confidence: 99%

“…In both CDD and BBD experiments, each of the treatment combinations was set to obtain colour removal of the indole, anthraquinone dye and methyl blue, which measure the extent of their degradation in the wastewater. The detailed experimentation describing the photodegradation of the indole, anthraquinone dye and methyl blue using pure TiO 2 and Ag + - doped TiO 2 has been reported in Merabet et al, 24 Khataee et al 28 and Sahoo and Gupta, 27 respectively.…”

Section: Data Descriptionmentioning

confidence: 99%

“…Moreover, factors such as pH of the medium, reaction time, initial concentration of the organic pollutant, light intensity, catalyst dosage, pH and flow rate have been reported to influence the photodegradation of organic pollutants. [24][25][26][27][28] Hence the effects of these parameters on the degradation of the various organic pollutants have been investigated using response surface methodology (RSM). 27,28 RSM is time consuming, costly and cannot be used to determine the nonlinear relationship between the process parameters and degradation of the organic pollutants.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Backpropagation neural networks modelling of photocatalytic degradation of organic pollutants using TiO₂‐based photocatalysts

Ayodele

Alsaffar

Mustapa

et al. 2020

J of Chemical Tech & Biotech

View full text Add to dashboard Cite

BACKGROUND The advanced oxidation process using photocatalysts has been proven to be an efficient technique used for the degradation of organic pollutants in wastewater. However, there exists a nonlinear relationship between the process parameters of the photodegradation reaction, which needs to be well understood for the design of an efficient photoreactor. This study employed a backpropagation artificial neural network (BPANN) for the modelling of photocatalytic degradation of indole, anthraquinone dye and methyl blue using undoped and Ag+‐doped TiO2 catalysts. RESULTS A Levenberg–Marquardt algorithm was employed to train the BPANN by varying the hidden neurons to obtained an optimized architecture. Optimized architectures with 3‐14‐1, 4‐12‐1 and 3‐16‐1 consist of the input layers, hidden layer and the output layer, were obtained using the datasets from photodegradation of indole, anthraquinone dye and methyl blue, respectively. The optimized BPANN accurately predicts the indole, anthraquinone dye and methyl blue degradation as a function of colour removal from the wastewater. High coefficients of determination (R2) of 0.999, 0.961 and 0.993 were obtained for the prediction of the photodegradation of indole, anthraquinone dye and methyl blue, respectively, with over 95% confidence level. The study revealed that dye concentration, catalyst dosage and reaction time have the highest level of importance for the photodegradation of indole, anthraquinone dye and methyl blue, respectively. CONCLUSION This study has demonstrated the robustness of BPANN for predictive modelling of photodegradation of organic pollutants such as indole, anthraquinone dye and methyl blue. © 2020 Society of Chemical Industry

show abstract

Section: Data Descriptionmentioning

confidence: 99%

Section: Data Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Backpropagation neural networks modelling of photocatalytic degradation of organic pollutants using TiO₂‐based photocatalysts

Ayodele

Alsaffar

Mustapa

et al. 2020

J of Chemical Tech & Biotech

View full text Add to dashboard Cite

show abstract

“…These toxicity reports have moved some laboratories to devise approaches to degrade Indole by TiO 2 dispersions under UV-light [15][16]. K. Ranjit and J. Moser et al, have reported Indole degradation and the degradation of other benzenic type compounds under UV-light mediated by doped-TiO 2 through Ti-complexes [17][18].…”

Section: Introductionmentioning

confidence: 99%

A New Perspective in the Use of FeOx-TiO2 Photocatalytic Films: Indole Degradation in the Absence of Fe-Leaching

Rtimi

Robyr

Pulgarín

et al. 2016

Journal of Catalysis

View full text Add to dashboard Cite

The first evidence is reported for the degradation of Indole at the solid air interface under low intensity solar simulated light in a stable repetitive fashion. The cosputtering of FeOx-TiO 2 on polyethylene (PE) lead to an accelerated Indole degradation kinetics compared to TiO 2-PE and FeOx-PE films. Indole degradation on TiO 2-PE, FeOx-PE and polyethylene (PE) supported photocatalysts is shown to proceed without Fe-or Ti-release as detected by inductively coupled plasma mass-spectrometry (ICP-MS). This opens a new perspective for the use of Fecontaining films in the degradation of pollutants. The mechanism of charge generation by TiO 2-FeOx-PE film under light irradiation as a function of the applied light intensity provides insight and is discussed in relation to Indole degradation. The photo-generated charges in the film give rise to highly oxidative radicals which were unambiguously identified by appropriate scavenging experiments. The most oxidative species was O-singlet presenting an estimated lifetime of 20 microseconds and a mean-free path of 140 nm. The probability of the Indole triplet deactivation was 0.01 and was much smaller compared to the probability of 0.99 for the Indole*-triplet reaction with O 2 dissolved in the aqueous solution. By attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR), the systematic shift of  s (NH) and the  s (C=C) vibration-rotational peaks were followed during Indole degradation presenting the evidence for the increase in the inter-bond distance and molecular fluidity. The increase of the film hydrophilicity during the irradiation was evaluated and seems to be necessary for the Indole degradation. An average size of ~16.7 nm of the TiO 2-FeOx nanoparticles sputtered for 2 min on the PE was determined by atomic force microscopy (AFM) and remained invariable during the degradation of Indole. The topmost layers of the FeOx-TiO 2-PE film were characterized for their optical, crystallographic features and roughness (Rg) by adequate surface science methods. This study provides the evidence for a FeOx-TiO 2 heterojunction with a random distribution of TiO 2 and FeOx nanoparticles on PE leading to interfacial charge transfer (IFCT) from FeOx to lower-lying TiO 2 rapping states.

show abstract

Photocatalytic degradation in annular reactor: Modelization and optimization using computational fluid dynamics (CFD) and response surface methodology (RSM)

Kumar

Bansal

2013

Journal of Environmental Chemical Engineering

View full text Add to dashboard Cite

Optimization of the indole photodegradation on supported TiO2: influences of temperature, concentration, TiO2 amount and flow rate

Cited by 6 publications

References 11 publications

Backpropagation neural networks modelling of photocatalytic degradation of organic pollutants using TiO₂‐based photocatalysts

Backpropagation neural networks modelling of photocatalytic degradation of organic pollutants using TiO₂‐based photocatalysts

A New Perspective in the Use of FeOx-TiO2 Photocatalytic Films: Indole Degradation in the Absence of Fe-Leaching

Photocatalytic degradation in annular reactor: Modelization and optimization using computational fluid dynamics (CFD) and response surface methodology (RSM)

Contact Info

Product

Resources

About

Optimization of the indole photodegradation on supported TiO2: influences of temperature, concentration, TiO2 amount and flow rate

Cited by 6 publications

References 11 publications

Backpropagation neural networks modelling of photocatalytic degradation of organic pollutants using TiO2‐based photocatalysts

Backpropagation neural networks modelling of photocatalytic degradation of organic pollutants using TiO2‐based photocatalysts

A New Perspective in the Use of FeOx-TiO2 Photocatalytic Films: Indole Degradation in the Absence of Fe-Leaching

Photocatalytic degradation in annular reactor: Modelization and optimization using computational fluid dynamics (CFD) and response surface methodology (RSM)

Contact Info

Product

Resources

About

Backpropagation neural networks modelling of photocatalytic degradation of organic pollutants using TiO₂‐based photocatalysts

Backpropagation neural networks modelling of photocatalytic degradation of organic pollutants using TiO₂‐based photocatalysts