Comparison of a new mass-concentration, chain-reaction model with the population-balance model for early- and late-stage aggregation of shattered graphene oxide nanoparticles

Babakhani, Peyman; Bridge, Jonathan; Phenrat, Tanapon; Fagerlund, Fritjof; Doong, Ruey‐an; Whittle, Karl R.

doi:10.1016/j.colsurfa.2019.123862

Cited by 10 publications

(4 citation statements)

References 88 publications

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“…Also, the available mathematical models that try to couple the transport equation with an expression for aggregation (Babakhani et al., 2018; Chatterjee & Gupta, 2009; Quik et al., 2015; Raychoudhury et al., 2012; Taghavy et al., 2015) may provide improved results, but either they do not take into account for appropriate particle dispersion or they fail to account for the existence of repulsive forces between charged particles. Other models use simplifying or empirical reaction rates (Babakhani et al., 2019), and general attachment equations (Wang et al., 2018) to account for transport and aggregation of particles. The mathematical model developed by Babakhani (2019) takes into account transport and aggregation of nanoparticles and evaluates their size exclusion.…”

Section: Introductionmentioning

confidence: 99%

Modeling the Transport of Aggregating Nanoparticles in Porous Media

Katzourakis

Chrysikopoulos

2021

Water Resources Research

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Nanoparticle aggregation is an important process for particle attachment during transport in porous media. However, the available mathematical models for particle transport, which are based on colloid filtration theory (CFT), depth-dependent retention and blocking, despite their success in fitting relatively Abstract A novel mathematical model was developed to describe the transport of nanoparticles in water saturated, homogeneous porous media with uniform flow. The model accounts for the simultaneous migration and aggregation of nanoparticles. The nanoparticles are assumed to be found suspended in the aqueous phase or attached reversibly or irreversibly onto the solid matrix. The Derjaguin-Landau-Verwey-Overbeek theory was used to account for possible repulsive interactions between aggregates. Nanoparticle aggregation was represented by the Smoluchowski population balance equation (PBE). Both reaction-limited aggregation and diffusion-limited aggregation were considered. Particle-size dependent dispersivity was accounted for. In order to overcome the substantial difficulties introduced by the PBE, the governing coupled partial differential equations were solved by employing adaptive operator splitting methods, which decoupled the reactive transport and aggregation into distinct physical processes. The results from various model simulations showed that the transport of nanoparticles in porous media is substantially different than the transport of conventional biocolloids. In particular, aggregation was shown to either decrease or increase nanoparticle attachment onto the solid matrix, depending on particle size, and to yield early or late breakthrough, respectively. Finally, useful conclusions were drawn regarding possible erroneous results generated when aggregation, particle-size dependent dispersivity or nanoparticle surface charges are neglected.

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Section: Introductionmentioning

confidence: 99%

Modeling the Transport of Aggregating Nanoparticles in Porous Media

Katzourakis

Chrysikopoulos

2021

Water Resources Research

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“…This finding lies in line with our previous statement [2], and experimental results obtained in previous studies [29], that reversible platelet aggregation is the process of destabilization of large aggregates formed in the first phase. Although in this study the dependence of the model parameters on ADP concentration was not observed, we expect the parameters k 1 and k 2 to be linearly proportional to the logarithm of reagent concentration as was described earlier by Babakhani et al [30].…”

Section: Discussionmentioning

confidence: 57%

Study of Reversible Platelet Aggregation Model by Nonlinear Dynamics

2021

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Blood cell platelets form aggregates upon vessel wall injury. Under certain conditions, a disintegration of the platelet aggregates, called “reversible aggregation”, is observed in vitro. Previously, we have proposed an extremely simple (two equations, five parameters) ordinary differential equation-based mathematical model of the reversible platelet aggregation. That model was based on mass-action law, and the parameters represented probabilities of platelet aggregate formations. Here, we aimed to perform a nonlinear dynamics analysis of this mathematical model to derive the biomedical meaning of the model’s parameters. The model’s parameters were estimated automatically from experimental data in COPASI software. Further analysis was performed in Python 2.7. Contrary to our expectations, for a broad range of parameter values, the model had only one steady state of the stable type node, thus eliminating the initial assumption that the reversibility of the aggregation curve could be explained by the system’s being near a stable focus. Therefore, we conclude that during platelet aggregation, the system is outside of the influence area of the steady state. Further analysis of the model’s parameters demonstrated that the rate constants for the reaction of aggregate formation from existing aggregates determine the reversibility of the aggregation curve. The other parameters of the model influenced either the initial aggregation rate or the quasi-steady state aggregation values.

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“…Derived count rates (DCR), determined by dynamic light scattering (DLS), have been used as an indicator for the mass concentration of dispersed particles in suspensions. [30][31][32] Here we used the product of a DCR value (kcps) and the corresponding volume (mL) of suspension as the indicator of accumulative nanoprecipitation. The DCR of pure DMF-PBS mixture with no drug was regarded as the blank for subtraction.…”

Section: Effect Of Salt Concentration On Drug and Polymer Precipitationmentioning

confidence: 99%

Phase separation‐induced nanoprecipitation for making polymer nanoparticles with high drug loading

et al. 2023

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Increasing drug loading remains a critical challenge in the development and translation of nanomedicine. High drug‐loading nanoparticles have demonstrated unique advantages such as less carrier material used, better‐controlled drug release, and improved efficacy and safety. Herein, we report a simple and efficient salt concentration screening method for making polymer nanoparticles with exceptionally high drug loading (up to 66.5 wt%) based on phase separation‐induced nanoprecipitation. Upon addition of salt, phase separation occurs in a miscible solvent‐water solution delaying the precipitation time of drugs and polymers to different extents, facilitating their co‐precipitation thus the formation of high drug‐loading nanoparticles with high encapsulation efficiency (>90%) and excellent stability (>1 month). This technology is versatile and easy to be adapted to various hydrophobic drugs, different polymers, and solvents. This salt‐induced nanoprecipitation strategy offers a novel approach to fabricating polymer nanoparticles with tunable drug loading, and opens great potentials for future nanomedicines.

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Comparison of a new mass-concentration, chain-reaction model with the population-balance model for early- and late-stage aggregation of shattered graphene oxide nanoparticles

Abstract: Comparison of a new massconcentration, chain-reaction model with the population-balance model for early-and late-stage aggregation of shattered graphene oxide nanoparticles. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 582, p. 123862.

Cited by 10 publications

References 88 publications

Modeling the Transport of Aggregating Nanoparticles in Porous Media

Modeling the Transport of Aggregating Nanoparticles in Porous Media

Study of Reversible Platelet Aggregation Model by Nonlinear Dynamics

Phase separation‐induced nanoprecipitation for making polymer nanoparticles with high drug loading

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