Evaluation of Metal-Organic Framework/Layered Double Hydroxide-Embedded Sodium Alginate Beads for Effective Removal of Tartrazine Dye: a Comparative Analysis of Rsm and Ann
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Date
2025
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Elsevier
Abstract
NiFe-layered double hydroxide supported metal-organic framework-embedded alginate bead composite (MIL-88 A/NiFe-LDH@SA) was developed and investigated for the removal of tartrazine food dye (TTZ). Structural characterizations of MIL-88 A/NiFe-LDH@SA were determined by the measurement of FTIR, XRD, BET, SEM, and EDX. Response surface methodology (RSM) and artificial neural network (ANN) were applied to predict the removal of TTZ dye. The optimization of the relevant parameters was obtained via the central composite design (CCD) in RSM. The numerical optimization revealed that a maximum removal efficiency of 94.82 % was achieved at Co of 8.02 mg/L, pH of 3.74, adsorption duration of 4.72 h, and adsorbent amount of 1.33 mg/mL. A comparative analysis was also performed for RSM and ANN models. The findings show that both models can accurately predict TTZ removal efficiency. However, based on the statistical analysis results, ANN demonstrated a higher level of accuracy than RSM in predicting TTZ removal. The kinetic studies also revealed that the adsorption well obey the pseudo-second order (PSO). The isotherm studies indicated that the LangmuirFreundlich (L-F) model was proper for explaining the adsorption behavior of TTZ on MIL-88 A/NiFeLDH@SA. Thermodynamic studies conducted that the adsorption process is spontaneous and exothermic.
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Keywords
Adsorption, Artificial Neural Network, Metal-Organic-Framework, Response Surface Methodology, Sodium Alginate, Tartrazine
Turkish CoHE Thesis Center URL
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Q1
Scopus Q
Q1
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Volume
311