Effect of different good solvents in flash nano-precipitation via multi-scale population balance modeling-CFD coupling approach. (14th December 2021)

• Record Type: Journal Article
• Authors: Lavino, Alessio D.; Ferrari, Marco; Barresi, Antonello A.; Marchisio, Daniele
• Is Part Of: Chemical engineering science. Volume 245(2021)
• Publication Date: 2021-12-14
• Subjects: ACT acetone -- ACN acetonitrile -- CMD cluster mass distribution -- CFD computational fluid dynamics -- CIJM confined impinging jets mixer -- DQMOM-IEM direct quadrature method of moments coupled with the interaction and exchange with the mean -- FNP flash nano-precipitation -- HSP Hansen solubility parameters -- NP Nanoparticles -- PCL poly-ε-caprolactone -- PBM population balance model -- PDF probability density function -- QMOM quadrature method of moments -- TBA tert-butanol -- THF tetrahydrofuran; Flash Nano-Precipitation -- Hansen Solubility Parameters -- Flory–Huggins Theory -- Population Balance Model -- CFD; Chemical engineering -- Periodicals; Génie chimique -- Périodiques; Chemical engineering; Periodicals; Electronic journals; 660
• DOI: 10.1016/j.ces.2021.116833
• Languages: English
• ISSNs: 0009-2509

Abstract

Highlights: Good solvents effect in FNP are studied via a multi-scale modeling approach. Acetone, acetonitrile, tetrahydrofuran and tert-butanol as good solvents. Kinetics and thermodynamics are intertwined via a PBM-CFD coupling. Modeling methods are used to decouple aggregation from mixing dynamics. Mean particle size and key mechanisms are identified and validated with experiments. Abstract: A computational and modeling approach is used to highlight the key factors that affect polymer nanoparticles (NP) formation in flash nano-precipitation (FNP), when the good solvent, e.g., acetone, is replaced by acetonitrile, tetrahydrofuran and tert-butanol. A population balance model is coupled with computational fluid dynamics to study the kinetics effects on FNP. The mean NP size is predicted in terms of mean radius of gyration via the Flory law of real polymers. The effect of different good solvents is modeled in terms of solute–solvent interactions, using the Flory–Huggins theory and Hansen solubility parameters. Promising results show how the proposed methodology is able to investigate the role played by different good solvents, analyzing single factors at the time. A deep insight into both the dynamics of mixing and the dynamics of aggregation is therefore reached and the main mechanisms involved are pointed out, showing a good agreement with experimental data.