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Modeling Tetracycline Adsorption onto Blast Furnace Slag Using Statistical and Machine Learning Approaches

Author

Listed:
  • Harsha S. Rangappa

    (Center for Interdisciplinary Programs, Indian Institute of Technology Hyderabad, Kandi, Sangareddy 502285, India
    Centre for Regional and Rural Futures, Faculty of Science, Engineering and Built Environment, Deakin University, Burwood, VIC 3125, Australia)

  • Phyu Phyu Mon

    (Department of Chemistry, Indian Institute of Technology Hyderabad, Kandi, Sangareddy 502285, India)

  • Indika Herath

    (Centre for Regional and Rural Futures, Faculty of Science, Engineering and Built Environment, Deakin University, Waurn Ponds, VIC 3216, Australia)

  • Giridhar Madras

    (Department of Chemical Engineering, Indian Institute of Technology Hyderabad, Kandi, Sangareddy 502285, India)

  • Chuxia Lin

    (Centre for Regional and Rural Futures, Faculty of Science, Engineering and Built Environment, Deakin University, Burwood, VIC 3125, Australia)

  • Challapalli Subrahmanyam

    (Center for Interdisciplinary Programs, Indian Institute of Technology Hyderabad, Kandi, Sangareddy 502285, India
    Department of Chemistry, Indian Institute of Technology Hyderabad, Kandi, Sangareddy 502285, India)

Abstract

Ground granulated blast furnace slag (GGBS) is a primary industrial waste product of iron production, and its improper disposal has been a serious environmental problem. This study aims to modify the GGBS using oxalic acid (GGBS-Ox) for the adsorption of tetracycline (TC) from an aqueous solution. GGBS-Ox was synthesized and characterized via FTIR, XRD SEM, XPS, BET, and DLS. The effects of process parameters, involving initial solution pH, stirring speed, and contact time, are evaluated by utilizing response surface methodology (RSM), artificial neural network (ANN), and random forest (RF) based models. The experimental results indicate that the removal efficiency of TC is significantly affected by the initial pH of the solution. The RSM, ANN, and RF models accurately simulated the experimental data, as indicated by the high coefficient of determination (R 2 ), which was 0.98, 0.95, and 0.98, respectively. Additionally, kinetics, isotherm, and thermodynamic models were evaluated for the adsorption of TC onto GGBS-Ox. The findings of this study demonstrated the utilization of GGBS-Ox as an efficient and sustainable adsorbent for the treatment of TC and can be considered as a potential adsorbent for wastewater treatment.

Suggested Citation

  • Harsha S. Rangappa & Phyu Phyu Mon & Indika Herath & Giridhar Madras & Chuxia Lin & Challapalli Subrahmanyam, 2024. "Modeling Tetracycline Adsorption onto Blast Furnace Slag Using Statistical and Machine Learning Approaches," Sustainability, MDPI, vol. 16(1), pages 1-24, January.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:1:p:464-:d:1313331
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