A response surface modeling and optimization of photocatalytic degradation of 2,4-dichlorophenol in water using hierarchical nano-assemblages of CuBi2O4 particles

Photocatalytic degradation, as an advanced oxidation process (AOPs), offers a great advantage to target persistent organic pollutants (POPs) in water. RSM in the present study which is statistical means for optimizing processes like photocatalysis with minimum laboratory experimentation. RSM has a history of being a potent design experiment tool for creating new processes, modifying their designs, and optimizing their performances. Herein, a highly sought-after, easily preparable, visible-light active, copper bismuth oxide (CuBi2O4) is applied against a toxic emerging contaminant, 2,4-dichlorophenol (2,4-DCP) under an LED light source (viible light λ > 420 nm). A simple coprecipitation method was adopted to synthesize CuBi2O4 and later analyzed with FESEM, EDX, XRD, FTIR, and spectroscopy to determine its intrinsic properties. Principally, the photocatalytic degradation investigations were based on response surface methodology (RSM), which is a commanding tool in the optimization of the processes. The 2,4-DCP concentration (pollutant loading), CuBi2O4 dosage (catalyst dosge), contact time, and pH were the chosen as dependent factors, that were optimized. However, under optimal conditions, the CuBi2O4 nanoparticle showed a remarkable photocatalytic performance of 91.6