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The influence of process variables (adsorbent mass, sonication time, MG, DB and MB concentration dyes on adsorption was investigated by central composite rotatable design (CCRD) of RSM.
The operational parameters such as metal ions concentration, CSG-BiPO4/FePO4 mass, sonication time and temperature were investigated and optimized using central composite design (CCD).
Optimum conditions and values correspond to pH, HKUST-1-MOF-Fe3O4-NPs-GA-MIP mass, sonication time and the eluent volume were set as follow 3.0, 1.6 mg, 4.0 min and 180 μL, respectively.
Initial dyes concentrations, adsorbent mass, sonication time and pH contribution on QY and EB removal percentage were investigated by CCD and replication of experiments at conditions suggested by model has results which statistically are close to experimented data.
The effects of important variables such as the initial concentration of MB, adsorbent mass, sonication time and pH on the removal percentage of MB were investigated and optimized by central composite design (CCD).
Optimum values of 4, 0.02 g, 4 min, 10 mg L−1 were obtained for pH, AC HKUST-1 MOF mAC HKUST-1ation tiMOFand the concentration of each dye, respectively.
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Four significant variables affecting SLC recovery like; pH, eluent volume, sonication time and adsorbent mass were selected by the Plackett-Burman design (PBD) experiments.
Contribution of volume of eluent, pH, sorbent mass and sonication time on response following conduction of 28 experiments were optimized and investigated while their significantly justified according to p-value.
The influence of process variables (initial dyes concentration, adsorbent mass and sonication time) on the removal of both dyes was investigated by central composite rotatable design (CCRD) of RSM, Multi-Layer Perceptron (MLP) neural network and Doolittle Factorization Algorithm (DFA).
To achieve maximum removal, the optimum condition was determined and were set as:19.34 and 18.20 mg L−1,0.018 g and 9.35 min for initial ECR and Pb2+ ion concentrations, adsorbent mass and sonication time, respectively.
The magnitude of variables like initial dyes concentration, adsorbent mass and sonication time influence on dyes removal was optimized using small central composite design (CCD) combined with desirability function (DF) approach, while pH was studied by one-a-time approach.
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