Discrete bivariate population balance modelling of heteroaggregation processes

Rollié, Sascha; Briesen, Heiko; Sundmacher, Kai

doi:10.1016/j.jcis.2009.04.031

Cited by 23 publications

(25 citation statements)

References 40 publications

(91 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The former, or molecular approach, avoids assumptions and approximations that are typical of the macroscopic approach but has the disadvantage of the complexity associated with the extrapolation of results to the macroscopic scale (Taboada-Serrano et al 2005). Progressively, models have been extended in order to include magnetic interaction (Tsouris and Scott 1995), floc structural variation (Selomulya et al 2003), breakup of agglomerates (Chin et al 1998), magnetic chain agglomerates (Mendelev and Ivanov 2005) and hetero-aggregation (Rolliè et al 2009). …”

mentioning

confidence: 99%

A predictive model of iron oxide nanoparticles flocculation tuning Z-potential in aqueous environment for biological application

2015

View full text Add to dashboard Cite

Iron oxide nanoparticles are the most used magnetic nanoparticles in biomedical and biotechnological field because of their nontoxicity respect to the other metals. The investigation of iron oxide nanoparticles behaviour in aqueous environment is important for the biological applications in terms of polydispersity, mobility, cellular uptake and response to the external magnetic field. Iron oxide nanoparticles tend to agglomerate in aqueous solutions; thus, the stabilisation and aggregation could be modified tuning the colloids physical proprieties. Surfactants or polymers are often used to avoid agglomeration and increase nanoparticles stability. We have modelled and synthesised iron oxide nanoparticles through a co-precipitation method, in order to study the influence of surfactants and coatings on the aggregation state. Thus, we compared experimental results to simulation model data. The change of Z-potential and the clusters size were determined by Dynamic Light Scattering. We developed a suitable numerical model to predict the flocculation. The effects of Volume Mean Diameter and fractal dimension were explored in the model. We obtained the trend of these parameters tuning the Z-potential. These curves matched with the experimental results and confirmed the goodness of the model. Subsequently, we exploited the model to study the influence of nanoparticles aggregation and stability by Z-potential and external magnetic field. The highest Z-potential is reached up with a small external magnetic influence, a small aggregation and then a high suspension stability. Thus, we obtained a predictive model of Iron oxide nanoparticles flocculation that will be exploited for the nanoparticles engineering and experimental setup of bioassays.

show abstract

mentioning

confidence: 99%

A predictive model of iron oxide nanoparticles flocculation tuning Z-potential in aqueous environment for biological application

2015

View full text Add to dashboard Cite

show abstract

“…On the other hand, it is interesting to note that the mathematical form for the aggregation frequency proposed here ሺߚ = ߮ߚሻ is analogous to expressions used in other widely studied phenomena [30]- [32], where ߚ is usually expressed as the product of the collision frequency and the collision efficiency. The collision frequency represents the probability of collision between two particles, and the collision efficiency describes what happens when these particles collide.…”

Section: Aggregation Frequencymentioning

confidence: 88%

Effect of sintering on the reactivity of copper-based oxygen carriers synthesized by impregnation

Maya

Bhatia

2017

Chemical Engineering Science

View full text Add to dashboard Cite

“…Die Simulationen in diesem Beitrag basieren auf 200 Rezeptorstellen bei KARPAS-299-Zellen und einem Rezeptoroberflächenan-teil von 1 À f UÀ937 0; 03 für U-937-Zellen, was ungefähr 6900 Rezeptoren entspricht. Dieser zweistufige Aggregationsprozess wurde nur bei intermediären Mischungsverhältnissen gefunden [24]. Bei sehr geringen Mischungsverhältnissen wie 1:1 Mischungen, verbleibt im Gegensatz die Brückenbildungs-wahrscheinlichkeit durch Knappheit an positiven Patches so gering, dass sich kaum PS-Oligomere bilden.…”

Section: Modellübertagung Auf Biologische Systemeunclassified

Analyse interagierender Partikel‐Zell‐Systeme mittels Durchflusszytometrie und mehrdimensionalen Populationsbilanzen

Rollié

Sundmacher

2010

Chemie Ingenieur Technik

View full text Add to dashboard Cite

Discrete bivariate population balance modelling of heteroaggregation processes

Cited by 23 publications

References 40 publications

A predictive model of iron oxide nanoparticles flocculation tuning Z-potential in aqueous environment for biological application

A predictive model of iron oxide nanoparticles flocculation tuning Z-potential in aqueous environment for biological application

Effect of sintering on the reactivity of copper-based oxygen carriers synthesized by impregnation

Analyse interagierender Partikel‐Zell‐Systeme mittels Durchflusszytometrie und mehrdimensionalen Populationsbilanzen

Contact Info

Product

Resources

About