Surface chemical heterogeneity modulates silica surface hydration

Abstract

An in-depth knowledge of the interaction of water with amorphous silica is critical to fundamental studies of interfacial hydration water, as well as to industrial processes such as catalysis, nanofabrication, and chromatography. Silica has a tunable surface comprising hydrophilic silanol groups and moderately hydrophobic siloxane groups that can be interchanged through thermal and chemical treatments. Despite extensive studies of silica surfaces, the influence of surface hydrophilicity and chemical topology on the molecular properties of interfacial water is not well understood. In this work, we controllably altered the surface silanol density, and measured surface water diffusivity using Overhauser dynamic nuclear polarization (ODNP) and complementary silica-silica interaction forces across water using a surface forces apparatus (SFA). The results show that increased silanol density generally leads to slower water diffusivity and stronger silica-silica repulsion at short aqueous separations (less than ∼4 nm). Both techniques show sharp changes in hydration properties at intermediate silanol densities (2.0-2.9 nm^-2). Molecular dynamics simulations of model silica-water interfaces corroborate the increase in water diffusivity with silanol density, and furthermore show that even on a smooth and crystalline surface at a fixed silanol density, adjusting the spatial distribution of silanols results in a range of surface water diffusivities spanning ∼10%. We speculate that a critical silanol cluster size or connectivity parameter could explain the sharp transition in our results, and can modulate wettability, colloidal interactions, and surface reactions, and thus is a phenomenon worth further investigation on silica and chemically heterogeneous surfaces.

Keywords: hydration dynamics; hydrophobicity; silica; surface forces; water.

Fig. 1.

Values of water diffusivity measured at the silica surface D_surface in 15 mM NaCl, pH 5.0, and 22 °C, as measured by ODNP. Errors in D_surface are the SD of at least three measurements at each value of α_OH. The surface silanol density α_OH was quantified by deuterium exchange and pH measurements following heat treatments at 1,000, 950, 900, 800, 700, 600, or 22 °C. There is a steep transition in D_surface between α_OH = 2.2 and 2.7 nm⁻² (corresponding to pretreatment temperatures of 800 and 700 °C, respectively). The upper x axis shows the average silanol spacing if one were to assume isotropically distributed silanols on the surface. The dashed gray line represents a linear trend of D_surface with α_OH, which connects the extrema of the end points in the plot, but does not pass through all of the data points. The solid gray line shows the more likely trend.

Fig. 2.

Representative SFA measurements of interaction forces as a function of distance (0.1-nm distance resolution) between silica surfaces across a 15 mM NaCl solution at 22 °C. The two surfaces used in each force run displayed the same water contact angles––either θ_o = 26° or 33° (i.e., a symmetric experiment). Values of α_OH were calculated from the Israelachvili–Gee equation (44). The solid lines correspond to DLVO fits for each data series. A Hamaker constant A of 6.1 × 10⁻²¹ J was used (45), and fitted values for the surface potential ψ_o were −60 ± 4 mV for the 26° surface, and −55 ± 3 mV for the 33° surface. Force profiles for surfaces displaying θ_o = 0° (α_OH = 4.6 nm⁻²) essentially lie on top of those for the 26° surface, and force profiles for surfaces displaying θ_o = 38° (α_OH = 1.2 nm⁻²) similarly match with those for the 33° surface, so these additional profiles are omitted here for clarity, but are shown in SI Appendix, Fig. S7. The force measurements were conducted ∼1 h after injecting the aqueous solution between the surfaces, but measurements after 48 h showed no change for the θ_o = 0° surface.

Fig. 3.

MD simulations of the cristobalite–water interface. (A) Surface water diffusivities calculated from experiment and simulation vs. α_OH. The error bars for simulation are the 99% confidence interval assuming a Student’s t distribution. The solid black lines trace out the minimum and maximum diffusivity surfaces for simulation after optimization using a genetic algorithm. (B) Images of the α_OH = 1.0, 1.5, and 2.0 nm⁻² surfaces associated with the max and min data points in A. The silanol coordination number N_c associated with each surface is displayed in blue below each image.