Effect of hydration repulsion on nanoparticle agglomeration evaluated via a constant number Monte–Carlo simulation

Abstract

The effect of hydration repulsion on the agglomeration of nanoparticles in aqueous suspensions was investigated via the description of agglomeration by the Smoluchowski coagulation equation using constant number Monte-Carlo simulation making use of the classical DLVO theory extended to include the hydration repulsion energy. Evaluation of experimental DLS measurements for TiO2, CeO2, SiO2, and α-Fe2O3 (hematite) at high IS (up to 900 mM) or low |ζ-potential| (≥1.35 mV) demonstrated that hydration repulsion energy can be above electrostatic repulsion energy such that the increased overall repulsion energy can significantly lower the agglomerate diameter relative to the classical DLVO prediction. While the classical DLVO theory, which is reasonably applicable for agglomeration of NPs of high |ζ-potential| (∼>35 mV) in suspensions of low IS (∼<1 mM), it can overpredict agglomerate sizes by up to a factor of 5 at high IS or low |ζ-potential|. Given the potential important role of hydration repulsion over a range of relevant conditions, there is merit in quantifying this repulsion energy over a wide range of conditions as part of overall characterization of NP suspensions. Such information would be of relevance to improved understanding of NP agglomeration in aqueous suspensions and its correlation with NP physicochemical and solution properties.

Monte Carlo Simulation Modeling of Nanoparticle–Polymer Cosuspensions

“…In the case of a polymer–nanoparticle cosuspension, a variety of interactions must be accounted for, including forces between polymer chains and between individual particles, and the confounding interactions of polymer chains and particles. Molecular dynamics and other simulations have provided great insights into how colloidal suspensions behave under a variety of conditions, but the focus is mainly on aqueous suspensions. − Nonpolar cosuspensions of nanoparticles and polymers are exceedingly difficult to study because of a lack of electrostatic interaction and added complications by agglomeration and the complex interaction of an entangling network of polymer chains …”

Mechanistic elucidation of freezing-induced surface decomposition of aluminum oxyhydroxide adjuvant

“…According to the extended-DLVO theory, the effect of hydration repulsions on nanoparticle aggregation is more important than electrostatic repulsion. As a result, nanoparticles with smaller hydration repulsions tend to form aggregations ( Liu et al., 2015 ). Therefore, the freezing-induced loss of hydroxyl groups on the surface of AlOOH NPs could also be an important contribution to the agglomeration of nanoparticles.…”

Evaluation of Toxicity Ranking for Metal Oxide Nanoparticles via an in Vitro Dosimetry Model

“…Sedimentation of NPs, for the purpose of calculating the delivered dose, was quantified via the SP2N model (Materials and Methods section). This model is premised on “particles in a box” simulation approach, , which tracks particle motion, as a result of gravitational settling and Brownian motion. , Model predictions were compared with previously reported experimental NP sedimentation data in deionized water and our own new results (based on ICP-OES measurements; Materials and Methods section) for selected NPs in BEGM and DMEM cell culture media. In addition, the relative trend of sedimentation behavior of the different NPs was also evaluated using a UV–vis measurement approach (Materials and Methods section).…”

“…In order to account for the effect of agglomerate PSD and permeability on NP sedimentation and calculation of in vitro delivered dose, an improved sedimentation model was developed based on a “particles in a box” simulation approach. , This model considers the motion of particles by Brownian diffusion , and modified Stokes settling . The model was validated based on experimental sedimentation measurements for NPs chosen from a group of 24 metal oxides, previously evaluated for in vitro hazard ranking and in vivo toxicity predictions .…”