Surface area of ferrihydrite consistently related to primary surface charge, ion pair formation, and specific ion adsorption

The specific surface area (SSA) of metal oxides is pivotal for scaling of surface phenomena. For ferrihydrite (Fh), the SSA can be assessed by probing the surface with ions that specifically adsorb (e.g. protons or phosphate). In the approach, an appropriate material with a known surface chemical behavior is used as reference, accounting for differences in e.g. surface sites and structure. As Fh is a nanomaterial, the size-dependency of many of its properties requires a consistent implementation for data analysis and modeling. In the present study, the proton adsorption of Fh was measured in NaNO3, NaCl, and NaClO4 solutions using a potentiometric titration methodology that leads to an internally consistent primary data set (H/Fe). For data interpretation, we employed a size-dependent molar mass, mass density, and chemical composition (FeO1.4(OH)(0.2)center dot nH(2)O), as well as a size-dependent surface curvature since the latter increases the value of the Stern layer capacitance. Using wellcrystallized goethite as reference, state-of-the-art multisite complexation modeling discloses the underlying SSA of Fh. Similar to goethite, a significant variation in electrolyte affinity constants (logK) is found for Fh. This largely explains the differences in plip m reported in literature when using e.g. KNO3 or NaCl rather than NaNO3 as electrolyte solution. Our data collection was done for Fh materials with a known aging history. The same Fh samples were also probed with phosphate ions and the collected primary data (PO4/Fe) were interpreted with the CD model. This methodology yields SSA values that are consistent with those found by probing the surface of Fh with protons. As ion probing with phosphate is rapid and sensitive, it is recommended as a tool to determine the SSA of Fh materials. This enables the development of a consistent thermodynamic database for application of surface complexation modeling in natural systems.