Advances in photocatalytic degradation of crystal violet using ZnO-based nanomaterials and optimization possibilities: a review

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dc.citation.issue6
dc.citation.rankM22
dc.citation.spage120
dc.citation.volume9
dc.contributor.authorNedelkovski, Vladan
dc.contributor.authorRadovanović, Milan
dc.contributor.authorAntonijević, Milan
dc.date.accessioned2025-12-10T12:18:08Z
dc.date.available2025-12-10T12:18:08Z
dc.date.issued2025
dc.description.abstractThe photocatalytic degradation of Crystal Violet (CV) using ZnO-based nanomaterials presents a promising solution for addressing water pollution caused by synthetic dyes. This review highlights the exceptional efficiency of ZnO and its modified forms—such as doped, composite, and heterostructured variants—in degrading CV under both ultraviolet (UV) and solar irradiation. Key advancements include strategic bandgap engineering through doping (e.g., Cd, Mn, Co), innovative heterojunction designs (e.g., n-ZnO/p-Cu2O, g-C3N4/ZnO), and composite formations with graphene oxide, which collectively enhance visible-light absorption and minimize charge recombination. The degradation mechanism, primarily driven by hydroxyl and superoxide radicals, leads to the complete mineralization of CV into non-toxic byproducts. Furthermore, this review emphasizes the emerging role of Artificial Neural Networks (ANNs) as superior tools for optimizing degradation parameters, demonstrating higher predictive accuracy and scalability compared to traditional methods like Response Surface Methodology (RSM). Potential operational challenges and future directions—including machine learning-driven optimization, real-effluent testing potential, and the development of solar-active catalysts—are further discussed. This work not only consolidates recent breakthroughs in ZnO-based photocatalysis but also provides a forward-looking perspective on sustainable wastewater treatment strategies.
dc.identifier.doi10.3390/chemengineering9060120
dc.identifier.issn2305-7084
dc.identifier.urihttps://repozitorijum.tfbor.bg.ac.rs/handle/123456789/6049
dc.language.isoen
dc.publisherMDPI
dc.rights.licenseCC-BY
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceChemEngineering
dc.subjectZnO
dc.subjectcrystal violet
dc.subjectphotocatalytic degradation
dc.subjectadvanced oxidation processes
dc.subjectartificial neural networks
dc.subjectwastewater treatment
dc.titleAdvances in photocatalytic degradation of crystal violet using ZnO-based nanomaterials and optimization possibilities: a review
dc.typearticle
dc.type.versionpublishedVersion

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