Cefixime removal via WO/Co-ZIF nanocomposite using machine learning methods.

Journal: Scientific reports
PMID:

Abstract

In this research, an upgraded and environmentally friendly process involving WO/Co-ZIF nanocomposite was used for the removal of Cefixime from the aqueous solutions. Intelligent decision-making was employed using various models including Support Vector Regression (SVR), Genetic Algorithm (GA), Artificial Neural Network (ANN), Simulation Optimization Language for Visualized Excel Results (SOLVER), and Response Surface Methodology (RSM). SVR, ANN, and RSM models were used for modeling and predicting results, while GA and SOLVER models were employed to achieve the optimal conditions for Cefixime degradation. The primary goal of applying different models was to achieve the best conditions with high accuracy in Cefixime degradation. Based on R analysis, the quadratic factorial model in RSM was selected as the best model, and the regression coefficients obtained from it were used to evaluate the performance of artificial intelligence models. According to the quadratic factorial model, interactions between pH and time, pH and catalyst amount, as well as reaction time and catalyst amount were identified as the most significant factors in predicting results. In a comparison between the different models based on Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Coefficient of Determination (R Score) indices, the SVR model was selected as the best model for the prediction of the results, with a higher R Score (0.98), and lower MAE (1.54) and RMSE (3.91) compared to the ANN model. Both ANN and SVR models identified pH as the most important parameter in the prediction of the results. According to the Genetic Algorithm, interactions between the initial concentration of Cefixime with reaction time, as well as between the initial concentration of Cefixime and catalyst amount, had the greatest impact on selecting the optimal values. Using the Genetic Algorithm and SOLVER models, the optimum values for the initial concentration of Cefixime, pH, time, and catalyst amount were determined to be (6.14 mg L, 3.13, 117.65 min, and 0.19 g L) and (5 mg L, 3, 120 min, and 0.19 g L), respectively. Given the presented results, this research can contribute significantly to advancements in intelligent decision-making and optimization of the pollutant removal processes from the environment.

Authors

  • Amir Sheikhmohammadi
    Department of Environmental Health Engineering, School of Health, Khoy University of Medical Sciences, Khoy, Iran.
  • Hassan Alamgholiloo
    Department of Environmental Health Engineering, School of Health, Khoy University of Medical Sciences, Khoy, Iran.
  • Mohammad Golaki
    Student Research Committee, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran.
  • Parsa Khakzad
    Department of Environmental Health Engineering, School of Health, Khoy University of Medical Sciences, Khoy, Iran.
  • Esrafil Asgari
    Department of Environmental Health Engineering, School of Public Health, Zanjan University of Medical Sciences, Zanjan, Iran. asgari.esrafil@zums.ac.ir.
  • Faezeh Rahimlu
    Department of Environmental Health Engineering, School of Health, Khoy University of Medical Sciences, Khoy, Iran.