Abstract
The present study was aimed at synthesizing algae-derived biochar to examine its effectiveness and adsorption capacity to remove Congo red dye. The independent variables such as dye concentration, adsorbent dose, and adsorption time were optimized by using a central composite design (CCD). An adsorption experiment was conducted to evaluate equilibrium using a detailed experimental design and characterized through XRD, TGA, SEM, EDX, and FTIR analysis. This paper also focuses on evaluating non-linear adsorption isotherm and kinetics to describe the adsorption mechanism along with applying an Artificial neural network to validate the removal efficiency. The maximum Congo red removal efficiency (96.14 %) and maximum adsorption capacity of algal biochar (186.94 mg/g) were achieved with the optimized parameters of 1 mg/L of dye concentration, 0.1 g of adsorbent dose, and 240 min of contact time. Adsorption behavior was well described by Langmuir isotherm and Pseudo-nth order. A multilayer perceptron (MLP) MLP 2–5–1 structure best validates the response. Overall, the study sheds light that Algal-derived biochar is a potential material for the elimination of Congo red dye and contributes to achieving sustainable development goals.
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