Enhancing Wastewater Treatment Through Python ANN-Guided Optimization of Photocatalysis with Boron-Doped ZnO Synthesized via Mechanochemical Route

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dc.citation.issue7
dc.citation.rankM22
dc.citation.spage2240
dc.citation.volume13
dc.contributor.authorNedelkovski, Vladan
dc.contributor.authorRadovanović, Milan B.
dc.contributor.authorMedić, Dragana
dc.contributor.authorStanković, Sonja
dc.contributor.authorHulka, Iosif
dc.contributor.authorTanikić, Dejan
dc.contributor.authorAntonijević, Milan
dc.date.accessioned2025-08-26T09:06:47Z
dc.date.available2025-08-26T09:06:47Z
dc.date.issued2025
dc.description.abstractThis study explores the enhanced photocatalytic performance of boron-doped zinc oxide (ZnO) nanoparticles synthesized via a scalable mechanochemical route. Utilizing X-ray diffraction (XRD) and scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS), the structural and morphological properties of these nanoparticles were assessed. Specifically, nanoparticles with 1 wt%, 2.5 wt%, and 5 wt% boron doping were analyzed after calcination at temperatures of 500 °C, 600 °C, and 700 °C. The obtained results indicate that 1 wt% B-ZnO nanoparticles calcined at 700 °C show superior photocatalytic efficiency of 99.94% methyl orange degradation under UVA light—a significant improvement over undoped ZnO. Furthermore, the study introduces a predictive model using the artificial neural network (ANN) technique, developed in Python, which effectively forecasts photocatalytic performance based on experimental conditions with R2 = 0.9810. This could further enhance wastewater treatment processes, such as heterogeneous photocatalysis, through ANN-guided optimization.
dc.identifier.doi10.3390/pr13072240
dc.identifier.issn2227-9717
dc.identifier.urihttps://repozitorijum.tfbor.bg.ac.rs/handle/123456789/5997
dc.language.isoen
dc.publisherMDPI
dc.rights.licenseCC-BY
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceProcesses
dc.subjectoptimization
dc.subjectdoped ZnO
dc.subjectnanoparticles
dc.subjectneural networks
dc.subjectphotocatalysis
dc.titleEnhancing Wastewater Treatment Through Python ANN-Guided Optimization of Photocatalysis with Boron-Doped ZnO Synthesized via Mechanochemical Route
dc.typearticle
dc.type.versionpublishedVersion

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