Authors: Brendon Lalchawimawia, Abhishek Mandal
Abstract: The study aimed in enhancing the efficiency of MIL-53(Al) in the remediation of tricyclazole from aqueous matrices through the application of RSM, ANN and GA. In order to enhance the remediation efficiency of tricyclazole by MIL-53(Al) process parameter- pH (2-11), adsorbate concentration (0.01-3 ppm), equilibration time (5 min, 10, 20, 30 and 1, 2, 3, 6h), adsorbent dosage (0.01-0.7 mg) were optimized by statistical modelling. An investigation of the batch methods of adsorption was carried out. The finding reports indicated that the RSM-ANN model's projection values exhibited greater agreement with experimental results as compared to RSM alone. The RSM-ANN model showed greater coefficients of determination than the RSM. As compared to RSM, which showed R2Adj = 0.980 for tricyclazole removal optimization, the RSM-ANN reported R2Adj and RMSE values of 0.998 and 0.0725. When genetic algorithm was introduced as a hybrid coupling to the RSM model it was found that amongst all the three optimization models RSM-GA model showed the best optimization, with an R2, R2Adj and Cross-validated R2Adj value of 0.9985, 0.9981, and 0.9963, respectively.
