Accurate atomically detailed models of amorphous materials have been elusive to-date due to limitations in both experimental data and computational methods. We present an approach for constructing atomistic models of amorphous silica surfaces encountered in many industrial applications (such as catalytic support materials). We have used a combination of classical molecular modeling and density functional theory calculations to develop models having predictive capabilities. Our approach provides accurate surface models for a range of temperatures as measured by the thermodynamics of surface dehydroxylation. We find that a surprisingly small model of an amorphous silica surface can accurately represent the physics and chemistry of real surfaces as demonstrated by direct experimental validation using macroscopic measurements of the silanol number and type as a function of temperature. Beyond accurately predicting the experimentally observed trends in silanol numbers and types, the model also allows new insights into the dehydroxylation of amorphous silica surfaces. Our formalism is transferrable and provides an approach to generating accurate models of other amorphous materials.
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