Thermal modeling for anionic surfactant using Inverse gas chromatography and image processing techniques

Abstract

Anionic surfactants are one of the necessary ingredients demanded in extensive bio-and pharmaceutical industry. Their concern on human health and environmental safety get increase and is originated from its surface thermodynamic properties. Surface thermodynamic properties have severely an effect on thermodynamic and kinetic parameters in the chemical reaction. However, there is a kind of serious differences between theoretical calculation and experimental result because of lacks of understanding on complex surface thermodynamic properties. Inverse gas chromatography (IGC) is an analytic chemistry tool providing information on physicochemical and thermodynamic parameters. Herein, a thermal modeling of surface thermodynamic properties is suggested. Net retention volume, VN, of n-alkanes and polar probes upon sodium lauryl sulfate surface properties as an anionic surfactant are analyzed at diverse temperatures range from 363.15 to 433.15 K using IGC. VN of n-alkane values are employed to assess the London dispersive surface free energy, γSL by comprehensive thermodynamic models and results into the Guttmann Lewis acid-base parameters and acid-base constants. The results reveal that an excellent linear correlation coefficient value closer to 1. The current work demonstrates how to approach surface thermodynamic characteristics of anionic surfactant and suggests a new thermal model as an advanced model. Additionally, scanning electron microscopy image analysis regarding the surface morphology has been carried out using image processing techniques. Current comprehensive approach enables to analyze and apply for an effective understanding on surfactant molecules.