A Machine Learning Approach to Predict Dye Degradation Efficiency Using ANN in Photocatalytic Systems
نویسندگان
1 School of Materials Science and Nanotechnology, Jadavpur University, Kolkata-700032
2 School of Materials Science and Nanotechnology, Jadavpur University, Kolkata-700032
3 Mechanical Engineering, Jadavpur University, Kolkata-700032
4 Mechanical Engineering, Jadavpur University, Kolkata-700032
doi
10.22090/jwent.2026.2082125.2042چکیده
This paper describes a low-cost, environmentally benign, one-step green production of TiO2 nanoparticles using leaf extract of Cinnamomum Tamala, along with photocatalytic activity under UV light that is studied kinetically and reusable. Titanium isopropoxide was used as a precursor of TiO2 and leaf extract was used as a reducing and capping agent. XRD spectra show the crystallinity and anatase phase of TiO2 nanoparticles. FTIR spectra depict the presence of the Ti-O bond. Spherical TiO2 nanoparticles were observed from the FESEM image with an average size of 38.34 nanometers. UV-Vis spectra also confirm the presence of TiO2 nanoparticles with no other impurity with bandgap 3.32 ev. Kinetic study and reusability study were also performed under UV light to photocatalytic degradation (86.50%, time 90 minutes) of MB dye. Photocatalytic performance was almost the same up to 10 times of washing cycles. pH 7 is the ideal condition for photocatalytic degradation of MB from wastewater under UV light. ANN model of the degradation has been carried out for degradation procedure.
