Review on Moringa oleifera, a green adsorbent for contaminants removal: characterization, prediction, modelling and optimization using Response Surface Methodology (RSM) and Artificial Neural Network (ANN).

Abstract

Moringa oleifera utilization in water treatment to eliminate emerging pollutants such as heavy metal ions, pesticides, pharmaceuticals, and pigments has been extensively evaluated. The efficacy of Moringa oleifera biosorbent has been investigated in diverse research work using various techniques, including its adsorption capacity kinetic, thermodynamic evaluation, adsorbent modifications, and mechanism behind the adsorption process. The Langmuir isotherm provided the most remarkable experimental data fit for batch adsorption investigations, whereas the best fit was obtained with the pseudo-second order kinetic model. Furthermore, only a few papers that combined batch adsorption with fixed-bed column investigations were examined. In the latter articles, the scientists modified the adsorbent to increase the material's adsorption capacity as determined by analytical methods, including IR spectroscopy, scanning electronic microscope (SEM), and X-ray diffraction (XRD). However, the raw material can show appreciable adsorption capacity values, proving moringa's potency as a biosorbent. Hydrogen bonds, electrostatic interaction, and van der Waals forces were the main processes in the found and reported adsorbent-adsorbate interactions. These mechanisms could change depending on the physiochemical nature of adsorption. Although frequently employed for heavy metal ions and dye adsorption, Moringa oleifera can still be explored in pesticide and medication adsorption investigations due to the few publications in this comprehensive review. This study, therefore, examined different Adsorbents from the Moringa oleifera plant, as well as parameters and models for enhancing the adsorption process.