Soft computing-based models and decolorization of Reactive Yellow 81 using Ulva Prolifera biochar

Area of Science:

• Environmental Chemistry
• Materials Science
• Chemical Engineering

Background:

• Reactive Yellow 81 (RY81) is a persistent textile dye pollutant.
• Effective decolorization methods are crucial for wastewater treatment.
• Biochar shows promise as an adsorbent for dye removal.

Purpose of the Study:

• To apply and compare optimization tools (RSM, ANN, ANFIS) for RY81 decolorization using biochar.
• To characterize biochar properties relevant to adsorption.
• To investigate adsorption mechanisms, thermodynamics, and biochar regeneration.

Main Methods:

• Biochar characterization (FTIR, elemental, proximate, BET, TGA).
• Optimization of five variables (pH, dose, time, concentration, temperature) using RSM, ANN, and ANFIS.
• Adsorption isotherm and kinetic modeling.
• Thermodynamic studies and regeneration cycle analysis.

Main Results:

• Maximum RY81 removal efficiency of 86.4% achieved.
• ANN and ANFIS models showed excellent correlation (R² > 0.9998), outperforming RSM (R² = 0.9665).
• Hill isotherm model predicted a maximum monolayer adsorption capacity of 225 mg g⁻¹, and 99.5% desorption efficiency was obtained with NaOH.

Conclusions:

• RSM, ANN, and ANFIS are effective tools for optimizing RY81 decolorization.
• The studied biochar is a viable adsorbent for RY81 removal.
• Biochar regeneration is feasible, indicating its potential for sustainable wastewater treatment.