A novel hybrid approach for predicting and optimizing the adsorption of methyl orange and Cr(VI) removal from aqueous solutions using fungal-cross linked chitosan integrated into graphene oxide as a cost-effective adsorbent.

The release of organic dyes and heavy metal ions in wastewater from various industries has become a significant environmental issue, prompting the need for effective solutions like remediation technology to reduce these pollutants in water. In this research, we fabricated a GO@Cs-GLA-TiO composite and assessed its performance in adsorbing methyl orange and hexavalent chromium from aqueous solutions. The composite material was thoroughly characterized using techniques such as Fourier-transform infrared spectroscopy, scanning electron microscopy, Energy-dispersive X-ray, and X-ray diffraction. Batch adsorption experiments were conducted, and key parameters such as contact time, pH, adsorbent dosage, and concentration were varied systematically. The adsorption of MO and Cr(VI) fit the pseudo-second-order kinetic model and the Langmuir and the Freundlich isotherm models. The maximum adsorption capacity for MO was 277.7 ± 1.8 mg/g, and for Cr(VI), it was 33.98.3 ± 0.48 mg/g. The artificial neural networks model demonstrated a high coefficient of determination (R = 0.9996) and a low mean squared error (0.025), indicating its robustness in simulating the MO removal process under various conditions. Furthermore, the adsorption kinetics were well-described by Haldane's model, which showed the best fit compared to other models tested. Notably, the GO@Cs-GLA-TiO composite was highly reusable, maintaining 85 ± 4.6% of its Cr(VI) adsorption capacity and 88.13 ± 3.05% of its MO adsorption capacity after four cycles of adsorption-desorption. This work highlights the significant potential of the GO@Cs-GLA-TiO composite as an efficient, sustainable material for wastewater treatment, making it a valuable contribution to environmental remediation research.