One of the popular cationic dyes that is environmentally persistent, toxic, carcinogenic and mutagenic is methylene blue (MB) dye. It is commonly applied as synthetic dye for dyeing fabrics in clothing and textile industries and also for dyeing papers and leathers. Sequel to the magnitude of industrial usage, a large volume of methylene blue dye containing wastewater is discharged into groundwater and surface water. At doses more than 5 mk/kg, the monoamine oxidate inhibitory characteristics of MB dye can induce fatal serotonin toxicity in human, apart from being a threat to fauna in aquatic ecosystem. Thus, it is highly imperative to eliminate MB dye from wastewaters. A number of different removal strategies have been reported in literature for treating methylene blue dye wastewater. In this state-of-the-art review, about 240 review and/or research published articles on methods for methylene blue dye wastewater decontamination or decontamination strategies were chosen for evaluation. This synthesis also discussed the various toxicities linked to MB dye. The assessment of elimination methods revealed that chemical removal methods (photochemical and non-photochemical) could generate secondary pollutants while biological methods are characterized with sensitivity of enzyme to pH. These drawbacks limit their industrial full-scale applications while adsorption technology was found to offer merits over others. The review comprehensively discussed each of these techniques while gaps and/or areas for future research are highlighted. 

Methylene blue dye: Toxicity and potential technologies for elimination from (waste)water

In the present study, we have successfully fabricated ZnO/Ag2O nanoparticles embedded in nitrogen doped carbon based nanocomposites (ZnO/Ag2O-NDC). The fabricated nanocomposites were characterized by several analytical techniques. The photocatalytic performance was inspected by the degradation of tetracycline (TC) under visible light. The fabricated nanocomposites show excellent photocatalytic degradation performance, which can degrade approximately 90.7% of TC within 60 min at nearly neutral pH 7, and the degradation rate constant was found to be 0.0083 min−1. Moreover, the optimal composite exhibited excellent stability, indicating its suitability for reuse. Reasonable pathways of antibiotic degradation were proposed based on the detected intermediates during the degradation, where the •OH and O2•- played a dominant role. It was also noticed that the N-doped graphitic carbon acts as the framework and promotes the electron transfer, and the ZnO acts as an effective photocatalyst while Ag2O as an electron trapping agent to enhance the visible light activity. 

Fabrication of highly porous ZnO/Ag2O nanoparticles embedded in N-doped graphitic carbon for photocatalytic degradation of tetracycline

Fe3O4-multiwalled carbon nanotubes-bentonite as adsorbent for removal of methylene blue from aqueous solutions.

Substantial improvement is needed in efficient and affordable decolorization and disinfection methods to solve the issues caused by dyes and harmful bacteria in water and wastewater. This work involves the photocatalytic degradation of methylene blue (MB) as well as gram-negative and gram-positive bacteria by cobalt-doped tin oxide (Co-SnO2) nanoparticles (NPs) and Co-SnO2/SGCN (sulfur-doped graphitic carbon nitride) nanocomposites (NCs) under sunlight. The coprecipitation approach was used to synthesize the photocatalysts. Maximum methylene blue (MB) photocatalytic degradation was seen with the 7% Co-SnO2 NPs compared to other (1, 3, 5, and 9 wt.%) Co-SnO2 NPs. The 7% Co-SnO2 NPs were then homogenized with different amounts (10, 30, 50, and 70 weight %) of sulfur-doped graphitic carbon nitride (SGCN) to develop Co-SnO2/SGCN heterostructures with the most significant degree of MB degradation. The synthesized samples were identified by modern characterization methods such as FT-IR, SEM, EDX, UV-visible, and XRD spectroscopies. The Co-SnO2/50% SGCN composites showed a significant increase in MB degradation and degraded 96% of MB after 150 min of sunlight irradiation. Both gram-negative (E. coli) and gram-positive (B. subtiles) bacterial strains were subjected to antibacterial activity. All samples were shown to have vigorous antibacterial activity against gram-positive and gram-negative bacteria, but the Co-SnO2/50% SGCNcomposites exhibited the maximum bactericidal action. Thus, the proposed NC is an efficient organic/inorganic photocatalyst that is recyclable and stable without lowering efficiency. Hence, Co-SnO2/50% SGCNNC has the potential to be employed in water treatment as a dual-functional material that simultaneously removes organic pollutants and eradicates bacteria.

/pdf/fabrication-of-effective-co-sno2-sgcn-photocatalysts-for-the-2t2vxr5j.pdf

Fabrication of Effective Co-SnO2/SGCN Photocatalysts for the Removal of Organic Pollutants and Pathogen Inactivation

Insights into oxygen defect enriched and non-metal dopant co modulated Fe3O4 nanospheres embedded WO3 nanorods for ameliorated photodegradation of doxycycline, Cr(VI) reduction and its genotoxicity

A facile low-cost scheme for highly photoactive Fe3O4-MWCNTs nanocomposite material for degradation of methylene blue

This study presents a novel method using an artificial neural network (ANN) to detect Pyrocatechol and hydroquinone in an aqueous solution. The technique utilizes a nanocomposite Poly 3,4-ethylenedioxythiophene-Graphene Oxide Nanosheets (PEDOT-GONs) Laccase biosensor, which demonstrates excellent electrocatalytic activity and electrochemical performance for the redox reactions of the target compounds. The study successfully develops a radical cation electropolymerization process involving poly EDOT with GONs and Lac as dopants to ensure the effective entrapment of the enzymes. Experimental techniques such as electrochemical characterization and SEM confirm the successful entrapment of the enzymes. Further, the ANN was trained using the backpropagation algorithm by applying the experimental results, with current and Pyrocatechol as inputs and hydroquinone concentrations as output. The application of ANN modeling to biosensor technology is validated, demonstrating its utility. The biosensor's linear response detection limit is 0.041 μM within the 0.040–0.41 μM and 0.41–3.0 μM ranges. Finally, the model's performances were evaluated by testing it within the test samples. The performances were measured using precision, recall, accuracy, F1-score, sensitivity, etc., and validated with existing mechanisms. 

An ANN Based Biosensor for the Detection of Pyrocatechol and Hydroquinone in Aqueous Solutions

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A facile low-cost scheme for highly photoactive Fe3O4-MWCNTs nanocomposite material for degradation of methylene blue

An ANN Based Biosensor for the Detection of Pyrocatechol and Hydroquinone in Aqueous Solutions