Using Excel Solver’s Parameter Function in Predicting and Interpretation for Kinetic Adsorption Model via Batch Sorption: Selection and Statistical Analysis for Basic Dye Removal onto a Novel Magnetic Nanosorbent

Abstract

Magnetic nanosorbents efficiently capture substances, particularly basic dyes, and can be easily recovered using a magnetic field in water treatment. Adsorption is a cost-effective and highly efficient method for basic dye removal. This study compared eight nonlinear kinetic adsorption models using Microsoft Excel 2023, which provided a detailed analysis and statistical results comparable to advanced programs like MATLAB and OriginPro. The Fractal Like-Pseudo First Order (FL-PFO) model showed the best fit for the kinetic adsorption model, closely predicting experimental data at 33.09 mg g−1. This suggests that the diffusion rate of basic dye within the magnetic nanosorbent pores is a crucial factor. The statistical parameters confirmed the suitability of these kinetic adsorption models for describing the observed behavior. Overall, Microsoft Excel emerged as a reliable tool for predicting adsorption behavior using various kinetic models for basic dye removal, offering a wide range of functions for diverse applications, including environmental monitoring and modeling. Corrected Akaike’s information criterion was used to determine the optimal model. It found the lowest AICcorrected value of about −3.8479 for the FL-PFO kinetic model, while the Elovich kinetic adsorption model had the highest AICcorrected value of 29.6605. This indicates that the FL-PFO kinetic model effectively correlated the kinetic data. It can be concluded that Microsoft Excel’s accessibility, familiarity, and broad range of capabilities make it a valuable resource for many aspects of environmental engineering.