Evaluating the efficiency of environmentally friendly magnetic photocatalyst for the treatment of industrial effluents containing dye pollutants
Abstract In this research, nanocomposites based on two-dimensional nanostructures such as graphene oxide were used as photocatalysts to remove methyl orange. One of the most important advantages of this type of photocatalyst is its high efficiency in the decomposition of colored organic pollutants,...
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2025-01-01
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| Series: | Applied Water Science |
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| Online Access: | https://doi.org/10.1007/s13201-025-02369-6 |
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| author | Sedigheh Abbasi |
| author_facet | Sedigheh Abbasi |
| author_sort | Sedigheh Abbasi |
| collection | DOAJ |
| description | Abstract In this research, nanocomposites based on two-dimensional nanostructures such as graphene oxide were used as photocatalysts to remove methyl orange. One of the most important advantages of this type of photocatalyst is its high efficiency in the decomposition of colored organic pollutants, as well as its ease of separation at the end of the process. For this purpose, titania semiconductor is synthesized as photocatalytic nanoparticles by hydrolysis method on the surface of graphene oxide. The dependence of photocatalytic activity of nanocomposite and hybrid without graphene oxide on operating conditions including irradiation time and photocatalyst concentration shows the positive effect of these two factors on the removal efficiency of methyl orange. By increasing the irradiation time from 5 to 40 min and also changing the photocatalyst concentration from 0.05 to 0.2%wt, the photocatalytic activity increases significantly, while with the increase in the pH of the suspension from 3 to 11, the removal efficiency initially decreases and then increases. The statistical findings indicate that independent single factors, their binary and triple interactions have a significant effect on the response at the 5% confidence level. Therefore, the statistical models proposed by nanocomposite and hybrid are able to estimate the dependence of removal efficiency on significant factors with an accuracy of 99%. Also, the Box–Cox curve confirms the adequacy of the statistical models without any transformation function. |
| format | Article |
| id | doaj-art-be832175b46c4a92a0fceeec55288d8c |
| institution | Kabale University |
| issn | 2190-5487 2190-5495 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | SpringerOpen |
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| series | Applied Water Science |
| spelling | doaj-art-be832175b46c4a92a0fceeec55288d8c2025-02-02T12:36:12ZengSpringerOpenApplied Water Science2190-54872190-54952025-01-0115211010.1007/s13201-025-02369-6Evaluating the efficiency of environmentally friendly magnetic photocatalyst for the treatment of industrial effluents containing dye pollutantsSedigheh Abbasi0Central Research Laboratory, Esfarayen University of TechnologyAbstract In this research, nanocomposites based on two-dimensional nanostructures such as graphene oxide were used as photocatalysts to remove methyl orange. One of the most important advantages of this type of photocatalyst is its high efficiency in the decomposition of colored organic pollutants, as well as its ease of separation at the end of the process. For this purpose, titania semiconductor is synthesized as photocatalytic nanoparticles by hydrolysis method on the surface of graphene oxide. The dependence of photocatalytic activity of nanocomposite and hybrid without graphene oxide on operating conditions including irradiation time and photocatalyst concentration shows the positive effect of these two factors on the removal efficiency of methyl orange. By increasing the irradiation time from 5 to 40 min and also changing the photocatalyst concentration from 0.05 to 0.2%wt, the photocatalytic activity increases significantly, while with the increase in the pH of the suspension from 3 to 11, the removal efficiency initially decreases and then increases. The statistical findings indicate that independent single factors, their binary and triple interactions have a significant effect on the response at the 5% confidence level. Therefore, the statistical models proposed by nanocomposite and hybrid are able to estimate the dependence of removal efficiency on significant factors with an accuracy of 99%. Also, the Box–Cox curve confirms the adequacy of the statistical models without any transformation function.https://doi.org/10.1007/s13201-025-02369-6Two-dimensional nanostructuresNanocompositePhotocatalytic activityStatistical modelBox–Cox |
| spellingShingle | Sedigheh Abbasi Evaluating the efficiency of environmentally friendly magnetic photocatalyst for the treatment of industrial effluents containing dye pollutants Applied Water Science Two-dimensional nanostructures Nanocomposite Photocatalytic activity Statistical model Box–Cox |
| title | Evaluating the efficiency of environmentally friendly magnetic photocatalyst for the treatment of industrial effluents containing dye pollutants |
| title_full | Evaluating the efficiency of environmentally friendly magnetic photocatalyst for the treatment of industrial effluents containing dye pollutants |
| title_fullStr | Evaluating the efficiency of environmentally friendly magnetic photocatalyst for the treatment of industrial effluents containing dye pollutants |
| title_full_unstemmed | Evaluating the efficiency of environmentally friendly magnetic photocatalyst for the treatment of industrial effluents containing dye pollutants |
| title_short | Evaluating the efficiency of environmentally friendly magnetic photocatalyst for the treatment of industrial effluents containing dye pollutants |
| title_sort | evaluating the efficiency of environmentally friendly magnetic photocatalyst for the treatment of industrial effluents containing dye pollutants |
| topic | Two-dimensional nanostructures Nanocomposite Photocatalytic activity Statistical model Box–Cox |
| url | https://doi.org/10.1007/s13201-025-02369-6 |
| work_keys_str_mv | AT sedighehabbasi evaluatingtheefficiencyofenvironmentallyfriendlymagneticphotocatalystforthetreatmentofindustrialeffluentscontainingdyepollutants |