Adsorption of Hexavalent Chromium on Raw and Activated Cassava Rhizome: Kinetic Analysis Using Mechanistic and Empirical (Regression and ANN) Models

Heavy metals adsorption by adsorbents prepared from natural materials is a low‐cost, effective method for their removal from aqueous environments. This study aims to investigate the kinetic studies on the adsorption of hexavalent chromium from its aqueous solution on raw and activated cassava rhizome. The coarse and fine raw cassava rhizome powder was activated by thermal (drying), pyrolysis, 1% (v/v) acetic acid, and 1% (w/v) KOH solutions. The batch adsorption studies were carried out by varying time (0–60 min) with adsorption capacity (meq/g) as a dependent variable. Adsorption capacity increased with an increase in time up to 40 min and then remained constant for all adsorbents with variation in adsorption capacity from 1.5 to 2.1 meq/g in the order of fine pyrolysis > fine thermal > fine acid = coarse pyrolysis > fine alkali = coarse thermal > coarse acid > coarse alkali > raw fine > raw coarse. Then, the effect of time on adsorption capacity data was fit to mechanistic models of pseudo‐first, pseudo‐second, zeroth, and half‐order kinetics. Adsorption of hexavalent chromium on raw coarse and fine cassava rhizome powder followed pseudo‐first‐order kinetics. Also, the data were fit to empirical models based on regression and neural network, and the goodness of model fit was evaluated using the correlation coefficient ( R ). Regression analysis indicates the optimal fit with an R value of 0.9948 when the effect of time on adsorption capacity was investigated. Neural network analysis reveals the best fit at an R value of 0.9985. Hence, a higher rate constant for fine particles compared to coarse particles indicates that fine particles have a greater effective surface area and enhanced diffusional properties, facilitating more efficient adsorption, which suggests that the finer particles interact more with the adsorbate, allowing for quicker transport and adsorption processes.