(39e) The Effect of Surface Chemistry on the Surface Energetics of Homogenous and Heterogeneous Physical Mixtures of Mannitol

The surface energy plays an important role in guiding number of phenomenon like wettability, cohesion/adhesion, flowability etc. Inverse gas chromatography has emerged as a useful tool for surface energy determination, and more recently, the surface energy heterogeneity of the solids using finite dilution inverse gas chromatography (FD-IGC) measurements. Notionally for mixtures of solids, this technique should probe the high energy domains preferentially while ignoring lower energy domains, however practically it appears that the problems facing the relative heterogeneities of materials or mixtures are not simple. The first part of this work involves the investigations on the mixtures produced by taking the weighted fractions of the homogenous (surface modified) and heterogeneous components. In the second part, investigations on the blends of homogenous components with different chemical surface functionalities was carried out. Different surface chemistries for the mannitol samples was obtained by the process of silanisation of surfaces with alkyl- and haloalkyl- groups to contain specific end functional groups. Mixtures of homogeneous materials was found to yield similarly homogeneous distributions, however the value was found to be an average of the constituent components. Homogenous binary mixtures containing components with different chemical surface functionalities were found to restore a heterogeneous effect in surface energy. A 50:50 weighting of the mixture was found to vary in the range of 28-32 mJ/m². Increasing haloalkyl fraction yielded decreasing energetics which was in the range of 26-28 mJ/m².

Furthermore, a novel method for measurement of energetic heterogeneity via modelling finite dilution IGC measurements using a Boltzmann distribution model and simulation fitting approach was developed. The surface energy distributions was determined, using a multi-solvent system site filling. The modelling was able to predict the surface energy distribution of the homogeneous as well as heterogeneous binary mixtures.