AI Summary & Key Takeaways
AI InsightThe results indicated that the Langmuir model provided a better fit to the experimental data compared to the Freundlich model, as evidenced by higher determination coefficients (0.9684) and lower error values.
📌 3 Key Takeaways
Abstract
Removal of Cd(II) ions from aqueous solutions was investigated using a nickel hydroxide/reduced graphene oxide composite as the adsorbent material. Influential parameters of the batch adsorption process were optimized using the Box-Behnken design, which enabled a systematic evaluation of the effects of various factors. An analysis of variance was performed to develop a quadratic regression model for predicting the percentage of Cd(II) removal. The optimal conditions for achieving maximum removal efficiency were identified as an adsorbent dosage of 60 mg, a pH of 8.0, and a mixing period of 40 minutes. Isotherm analysis was conducted using nonlinear regression, with the sum of squared errors serving as the error function. The results indicated that the Langmuir model provided a better fit to the experimental data compared to the Freundlich model, as evidenced by higher determination coefficients (0.9684) and lower error values. This suggested that the adsorption process is characterized by a monolayer adsorption mechanism on a homogeneous surface. The maximum adsorption capacity was found to be 218 mg/g, indicating the effectiveness of the nickel hydroxide/reduced graphene oxide composite in removing Cd(II) ions from solution.