The determination of oxide surface charging parameters for a predictive metal adsorption model

Abstract

The procurement of oxide surface charging parameters has been a widely researched topic in recent years [1–30]. In this study, a one-site, two- pK surface charging mechanism is used in combination with a diffuse double-layer description of the electric double-layer to fit pH shift data over silica and alumina. From these fits of pH data, with no further adjustment of parameters, metal adsorption can be predicted over both supports to a reasonable degree of accuracy. A multi-dimensional optimization procedure employing a Nelder–Mead simplex algorithm is used to optimize the Δ pK ( pK 2– pK 1) parameter to obtain a best fit of the pH shift data with fixed PZC and hydroxyl density ( N s ). The resulting set of parameters is then used with no adjustment in a purely electrostatic adsorption model (the Revised Physical Adsorption or RPA model) in order to predict anionic chloroplatinic acid (CPA, [PtCl 6] −2) adsorption on alumina and cationic platinum tetraammine (PTA, [Pt(NH 3) 4] +2) adsorption on alumina and silica. The optimization procedure developed in this study gives reasonable values of the Δ pK compared to other values reported in the literature, with fits to the pH shift data at various oxide loadings with relative errors below 2.8%.