Prediction of the surface chemistry of calcium aluminosilicate glasses

Miri Ramsheh, S.; Turchi, M.; Perera, S.; Schade, A.M.; Okhrimenko, D.V.; Stipp, S.L.S.; Solvang, M.; Walsh, T.R.; Andersson, M.P.

doi:10.1016/j.jnoncrysol.2023.122597

Cited by 1 publication

(1 citation statement)

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“…Predicting p K a using DFT + COSMO-RS is a general method, which (in principle) is system-independent. Our results for silica and other p K a predictions using the same method in the literature (e.g.,) suggest that the predictive power of the method is at least semiquantitative, but that it is best to benchmark against some experimental data whenever possible.…”

Section: Resultsmentioning

confidence: 99%

First-Principles Prediction of Amorphous Silica Nanoparticle Surface Charge: Effect of Size, pH, and Ionic Strength

Nazemzadeh,

Miranda,

Liang

et al. 2023

J. Phys. Chem. B

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The quantification of surface charge properties of silica nanoparticles is essential for several applications. To determine these properties, many experimental and theoretical methods have been introduced, which are time-consuming and/or challenging to use. In this study, a first-principles approach is developed to determine the surface charge properties of amorphous silica nanoparticles against the nanoparticle size, pH, and ionic strength without relying on experimental data. An amorphous silica nanoparticle of 1.34 nm diameter is simulated by using integrated molecular dynamics and Monte Carlo methods. A detailed analysis of the nanoparticle structure is provided by analyzing the types of silanol groups on the surface. Moreover, a model is developed to estimate the probability distribution of the surface silanol groups based on the nearest neighbor distances and the diameter of the nanoparticle to determine the number of surface silanols on larger nanoparticles. Thereafter, a computational chemistry approach is used to calculate the acid dissociation constants of the corresponding deprotonation reactions. The calculated constants and the point of zero charge value are in excellent agreement with experiments. The surface charge properties of the nanoparticle with various diameters are then estimated by using a mean-field model at different pH and ionic strength values. The results of the developed model are compared to the Poisson−Boltzmann equation as a reference model. The developed model predictions agree well with the reference model for low and mid-electrolyte concentrations (1 and 10 mM) and small nanoparticles (smaller than 100 nm). However, the developed model seems to qualitatively predict the surface charge properties more accurately than the Poisson− Boltzmann model for high electrolyte concentrations.

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Section: Resultsmentioning

confidence: 99%