Modelling and Statistical Interpretation of Phenol Adsorption Behaviour of 3-Dimensional Hybrid Aerogel of Waste-Derived Carbon Nanotubes and Graphene Oxide

Phenol is a well-known organic pollutant that poses a threat to environmental sustainability due to its prevalence in industrial effluents. This chemical is frequently found in industrial waste and can have detrimental effects on ecosystems. In order to address this issue, effective remediation strategies are essential. Carbon-based adsorbents have emerged as a popular solution in current research. These adsorbents have demonstrated exceptional efficiency in removing phenol from water, presenting a promising solution for phenol adsorption and promoting sustainable water management. The current study aims to evaluate the capacity of a novel hybrid aerogel synthesized from spent catalyst-generated carbon nanotubes (GO/CNTs) and graphene oxide (GO). The phenol adsorption efficiency and behavior of GO/CNTs were compared with three different carbon-based adsorbents: graphene oxide (GO), magnetic graphene oxide (MGO), and graphene oxide aerogel (GOA). The adsorption isotherm modeling of experimental data showed that GO/CNTs exhibited the highest phenol adsorption efficiency of 204 mg/g, followed by GOA (141 mg/g), according to the Langmuir isotherm model. The detailed adsorption mechanism was correlated with isotherm, kinetics, and thermodynamics datasets, and further validated by in-depth statistical analysis of models, confirming the superior phenol adsorption capacity of the wastederived hybrid aerogel. This research provides valuable insights into effective phenol removal from wastewater, emphasizing the promising performance of the novel GO/CNTs hybrid aerogel and providing optimized conditions for the adsorption process with statistical significance.