A competitive aggregation model for Flash NanoPrecipitation

Cheng, Janine Chungyin; Vigil, R. Dennis; Fox, Rodney O.

doi:10.1016/j.jcis.2010.07.066

Cited by 53 publications

(54 citation statements)

References 50 publications

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“…It is important to note that the initial precipitation process, which we model as Brownian aggregation, 11 occurs on much faster time scales than the mixing process (τ agg ∼ 10 ns, while τ mix ∼ 1 ms). Hence, the initial organic nanoparticle formation kinetics will be mixing limited.…”

Section: Kinetic Modelmentioning

confidence: 99%

“…11 In solving the PBE, one difficulty is the computational expense, especially when the PBE is implemented in the CFD code (i.e., when solving a general FNP case, p usually ranges from 20 to 50 and q from 50 to 300, resulting in 50 × 300 ) 15 000 equations to solve).…”

Section: Population Balance Equationmentioning

confidence: 99%

“…9 To describe the particle formation and size distribution as functions of mixing time and physical properties of inlet streams in the FNP process, a competitive aggregation model has been developed. 11 Using this model, knowledge of particle properties can be obtained by solving a bivariate population balance equation (PBE). In this kinetic model, the PBE represents an aggregate containing the organic actives and the diblock copolymer.…”

Section: Introductionmentioning

confidence: 99%

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Kinetic Modeling of Nanoprecipitation using CFD Coupled with a Population Balance

Cheng

Fox

2010

Ind. Eng. Chem. Res.

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A model study has been conducted for Flash Nanoprecipitation (FNP)sa novel approach to produce functional nanoparticles. A population balance equation with the FNP kinetics has been integrated into a computational fluid dynamics (CFD) simulation of a custom-designed microscale multi-inlet vortex reactor (MIVR) to yield conditions comparable to the real experimental settings. In coping with the complicated aggregation model in the CFD code, a new numerical approach, the conditional quadrature method of moments (CQMOM), has been proposed, which is capable of solving the multivariate system efficiently and accurately. It is shown that the FNP process is highly influenced by mixing effects in the microreactor, and thus coupling CFD with the kinetics model is essential in obtaining valid comparisons with experiments. A model study has been conducted for Flash Nanoprecipitation (FNP)sa novel approach to produce functional nanoparticles. A population balance equation with the FNP kinetics has been integrated into a computational fluid dynamics (CFD) simulation of a custom-designed microscale multi-inlet vortex reactor (MIVR) to yield conditions comparable to the real experimental settings. In coping with the complicated aggregation model in the CFD code, a new numerical approach, the conditional quadrature method of moments (CQMOM), has been proposed, which is capable of solving the multivariate system efficiently and accurately. It is shown that the FNP process is highly influenced by mixing effects in the microreactor, and thus coupling CFD with the kinetics model is essential in obtaining valid comparisons with experiments. Disciplines Biological Engineering | Chemical Engineering

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Section: Kinetic Modelmentioning

confidence: 99%

Section: Population Balance Equationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Kinetic Modeling of Nanoprecipitation using CFD Coupled with a Population Balance

Cheng

Fox

2010

Ind. Eng. Chem. Res.

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“…To avoid relying on the PD algorithm or Wheeler algorithm (Cheng et al, 2010) to get M k , w i and A i , Gimbun et al (2009) proposed a solution of differential equations with the conditions of algebraic constraints. A differential algebraic approach is represented by Eq.…”

Section: T β a T A T T A T A T A T W T W Tmentioning

confidence: 99%

Investigation of Aggregation Kernel and Simulation of Ultrafine Particle Aggregation under Turbulence and Brownian Motion

Zheng

Wang

et al. 2018

J. Chem. Eng. Japan / JCEJ

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In the present study, the in uence of di erent particle aggregation models on the y ash particle aggregation process of a turbulence aggregation device has been studied. The in uence of an interparticle repulsive potential energy barrier, U max , on the rate of aggregation was considered, and capture e ciency, f (α), was introduced to correct the ideal turbulence aggregation kernel. The simulation results of an ideal turbulence aggregation model and a corrected turbulence aggregation model were compared to the experimental results, and showed that the error between the ideal turbulence aggregation model and experimental results was approximately 8%; whereas, the error between the corrected turbulence aggregation model and experimental results was only 3%. Brownian aggregation cannot be ignored in the turbulence aggregation of the particles less than 2 µm in diameter. The coupled corrected turbulence aggregation and Brownian aggregation model coincided well with the experimental results.

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“…The multiscale model developed in this work describes the FNP as an aggregation process, as also proposed by other authors (Cheng et al, 2010), but for the first time it calculates the rate with which polymer molecules interact (via the so-called aggregation kernel) directly from MD simulations (Di Pasquale et al, 2014). MD data are, in fact, used to fit the Flory law (Flory, 1953;Rubinstein and Colby, 2003) for the radius of gyration and the Stokes-Einstein law for the diffusion coefficient of single PCL polymer molecules, completely defining the aggregation kernel appearing in the Smoluchowski population balance equation (PBE).…”

Section: Introductionmentioning

confidence: 99%

A novel multiscale model for the simulation of polymer flash nano-precipitation

Lavino

Pasquale

Carbone

et al. 2017

Chemical Engineering Science

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Numerous models describe the flash nano-precipitation (FNP) process to form polymer nanoparticles, however most of them are based on equilibrium approaches and are not capable of predicting kinetically stable configurations. Moreover, since FNP occurs through solvent-displacement, the way in which the solvent and anti-solvent are mixed plays an important role, which is often overlooked. Here we propose a multiscale approach, which combines molecular dynamics (MD), a Smoluchowski population balance equation (PBE) and computational fluid dynamics (CFD), to model the FNP process, from the atomistic-scale up to the macro-scale. The particle formation process is not described with the usual nucleation-and-growth approach, but as Brownian aggregation of the polymer molecules into nanoparticles. Being the final nanoparticles amorphous, no energy barrier to the aggregation process is considered, whereas the effects of both turbulent mixing and turbulent aggregation on the evolution of the nanoparticles are accounted for. The main novelty of this work is that the aggregation kernel appearing in the PBE, * Corresponding author: Daniele Marchisio; e-mail: daniele.marchisio@polito.it; tel.: +390110904622; fax: +390110904699

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A competitive aggregation model for Flash NanoPrecipitation

Cited by 53 publications

References 50 publications

Kinetic Modeling of Nanoprecipitation using CFD Coupled with a Population Balance

Kinetic Modeling of Nanoprecipitation using CFD Coupled with a Population Balance

Investigation of Aggregation Kernel and Simulation of Ultrafine Particle Aggregation under Turbulence and Brownian Motion

A novel multiscale model for the simulation of polymer flash nano-precipitation

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