Photocatalytic degradation of 2,4,6-trinitrotoluene (TNT) in the presence of ZnS, NiS and ZnS/NiS supported Clinoptilolite under UV irradiation: experimental and neural network modelling

Norouzi, Mahdi; Karimian, Azam; Dehghani, H; Leylan, Seyyed Alireza Rezvan

doi:10.1080/03067319.2021.1887859

Cited by 3 publications

(2 citation statements)

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“…ML approaches have also been used to study the kinetics of photocatalytic pollutant degradation and to optimize the parameters for product synthesis and photocatalytic reactions. − Jiang et al trained a NN model to decode the factors affecting the degradation of 78 organic pollutants by a TiO 2 photocatalyst . The ultraviolet intensity, TiO 2 dosage, the concentration of organic pollutants in water, pH value and temperature, and the structure of organics (described by molecular fingerprint) were used to train the model, using 446 data points from the literature.…”

Section: Application Of Machine Learning To Electrocatalysts and Phot...mentioning

confidence: 99%

Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery

et al. 2022

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Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels, reducing the impact of global warming, and providing solutions to environmental pollution. Improved processes for catalyst design and a better understanding of electro/ photocatalytic processes are essential for improving catalyst effectiveness. Recent advances in data science and artificial intelligence have great potential to accelerate electrocatalysis and photocatalysis research, particularly the rapid exploration of large materials chemistry spaces through machine learning. Here a comprehensive introduction to, and critical review of, machine learning techniques used in electrocatalysis and photocatalysis research are provided. Sources of electro/photocatalyst data and current approaches to representing these materials by mathematical features are described, the most commonly used machine learning methods summarized, and the quality and utility of electro/photocatalyst models evaluated. Illustrations of how machine learning models are applied to novel electro/ photocatalyst discovery and used to elucidate electrocatalytic or photocatalytic reaction mechanisms are provided. The review offers a guide for materials scientists on the selection of machine learning methods for electrocatalysis and photocatalysis research. The application of machine learning to catalysis science represents a paradigm shift in the way advanced, next-generation catalysts will be designed and synthesized.

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Section: Application Of Machine Learning To Electrocatalysts and Phot...mentioning

confidence: 99%

Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery

et al. 2022

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“…A common drawback of using traditional wastewater treatment techniques, including physical, chemical and biotechnologies for the treatment of such wastewater and their resulting contamination, is the removal of low efficiency or high treatment costs and possible secondary contaminations [3,4] . Nowadays, the heterogeneous photocatalytic technology has the practical application potential [5][6][7] with the economic, efficient and environmental-friendly photo-catalysts and the developed photocatalytic processes, and will play an important role in this field.…”

Section: Introductionmentioning

confidence: 99%

A facile preparation of g-C₃N₄/a-Fe₂O₃/TiO₂ composite and its photocatalysis performance on the degradation of DNT/TNT under simulated sunlight

Xiufang,

Yuan,

Chunyao

2023

J. Phys.: Conf. Ser.

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It has been difficult to solve the environmental problems caused by trinitrotoluene(TNT)/dinitrotoluene(DNT) containing explosive wastewater for decades. The advanced oxidation method based on photocatalysis and hydrogen peroxide has gained considerable popularity in the field of pollutant degradation. In order to find a coping strategy, using a simple method involving obtaining g-C3N4/Fe2O3(CNFe) by two-step calcination and then mixing butyl titanate and CNFe through a sol-gel pathway, a type of low-cost g-C3N4/Fe2O3/TiO2(CNFeTi) ternary composite was prepared and then characterized by SEM-EDS, IR, Raman spectroscopy, XRD, XPS, UV-vis, etc. Using the prepared CNFeTi as catalyst, the effects of the amount of catalyst and H2O2 dosage on the photocatalytic degradation of DNT/TNT in aqueous solution have been investigated under simulated sunlight, with the reaction being tracked by UV-vis spectrophotometer. And from the results it was shown to have excellent photocatalytic performance. Under the conditions of 1.0 g·L−1 H2O2, 3.0 g·L−1 C3N4/Fe2O3/TiO2, 15 A current intensity of a Xenon light source and natural pH, 95% DNT and 91% TNT were removed after 30 min irradiation, indicating the proposed system has a high degradation rate. The CNFeTi catalyst could be reused at least five times and exhibited good stability.

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Determination of Optimum Conditions for the Degradation of 2,4,6-Trinitrotoluene (TNT) by Advanced Reduction Processes

Yasar,

Ince,

Ince

et al. 2023

Water Air Soil Pollut

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Photocatalytic degradation of 2,4,6-trinitrotoluene (TNT) in the presence of ZnS, NiS and ZnS/NiS supported Clinoptilolite under UV irradiation: experimental and neural network modelling

Cited by 3 publications

References 66 publications

Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery

Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery

A facile preparation of g-C₃N₄/a-Fe₂O₃/TiO₂ composite and its photocatalysis performance on the degradation of DNT/TNT under simulated sunlight

Determination of Optimum Conditions for the Degradation of 2,4,6-Trinitrotoluene (TNT) by Advanced Reduction Processes

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Photocatalytic degradation of 2,4,6-trinitrotoluene (TNT) in the presence of ZnS, NiS and ZnS/NiS supported Clinoptilolite under UV irradiation: experimental and neural network modelling

Cited by 3 publications

References 66 publications

Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery

Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery

A facile preparation of g-C3N4/a-Fe2O3/TiO2 composite and its photocatalysis performance on the degradation of DNT/TNT under simulated sunlight

Determination of Optimum Conditions for the Degradation of 2,4,6-Trinitrotoluene (TNT) by Advanced Reduction Processes

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A facile preparation of g-C₃N₄/a-Fe₂O₃/TiO₂ composite and its photocatalysis performance on the degradation of DNT/TNT under simulated sunlight