Influence of Physical Properties on Drop Size Distribution of Stirred Liquid‐Liquid Dispersions

Kraume, Matthias; Gäbler, A.; Schulze, K.

doi:10.1002/ceat.200402006

Cited by 82 publications

(70 citation statements)

References 15 publications

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“…With addition of sodium chloride and therefore rising ionic strength, the coalescence inhibition was reduced and the drop sizes in the system increased, which agrees with the DLVO theory. The decrease of the drop size distribution at high pH values in a stirred tank is also described by Gäbler et al (2006) and Kraume et al (2004). The authors explain this effect by an increasing coalescence inhibition with higher pH values.…”

Section: Introductionmentioning

confidence: 64%

“…The authors explain this effect by an increasing coalescence inhibition with higher pH values. Kraume et al (2004) also showed the dependency of the coalescence inhibi-tion from the NaCl concentration in shaken flask experiments. The settling time, meaning the time after which a dispersed system is settled into two separate phases, increases with higher pH value and decreases with higher salt concentration.…”

Section: Introductionmentioning

confidence: 92%

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Coalescence efficiency model including electrostatic interactions in liquid/liquid dispersions

Kamp¹,

Kraume²

2015

Chemical Engineering Science

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The drop size distribution is an essential process variable in liquid/liquid systems and relevant in many technical applications. It can be described by population balance equations. A coalescence efficiency model was developed to be able to describe the well-known coalescence inhibition due to changing pH value or salt concentration. The model includes the attractive van der Waals and repulsive electrostatic force according to the DLVO theory into the population balance equation framework. This DLVO model can extend existing simulations in a straightforward manner due to a conceptual implementation. Moreover, zeta potential measurements were performed and the model was applied to simulate experiments in a stirred tank. Hence, the drop size distribution could be predicted well with changing pH value. The results are discussed in comparison to simulations with existing models in literature.

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Section: Introductionmentioning

confidence: 64%

Section: Introductionmentioning

confidence: 92%

Coalescence efficiency model including electrostatic interactions in liquid/liquid dispersions

Kamp¹,

Kraume²

2015

Chemical Engineering Science

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“…Kraume et al [15] showed that for a small dispersed-phase volume fraction f and thereby the relatively small probability of coalescence the breakage process is dominant so that the preconditions applied for the derivation of d 32 D CWe À0:6 are fulfilled. With increasing f, the probability of coalescence becomes more and more important and the power on W e becomes larger than -0.6.…”

Section: Introductionmentioning

confidence: 99%

Drop Size Distribution in a Standard Twin‐Impeller Batch Mixer at High Dispersed‐Phase Volume Fraction

El‐Hamouz

2009

Chem Eng & Technol

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The preparation of concentrated aqueous silicone oil emulsions has been investigated with particular attention to the effect of the dispersed‐phase volume fraction ϕ from 0.01 to 0.5 for a wide range of oil viscosities (50 to 1000 cSt). Oil was added on the top surface of a 6‐L vessel. Drop size distribution and Sauter mean diameter, d32, measurements were carried out over 24 h mixing time. Emulsification was found to be relatively sensitive to the oil phase viscosity, μd, for the same ϕ yielding a narrower drop size distribution for low oil viscosity (50 cSt) and a wider drop size distribution for the highly viscous oil (1000 cSt). For the same ϕ, increasing μd resulted in increasing d32. The equilibrium d32 was found to be well correlated to the viscosity number by $ {d_{32} \over D} = 0.026\, \ast \;{V_{\rm i}^{0.204}} $ for ϕ = 0.5. For the same oil viscosity, d32 was found to increase with increasing ϕ. A multiregression of d32 with both ϕ and Vi for various silicone oil viscosity grades was successfully correlated by $ d_{32} = 9.6\, \phi^{0.069} V_{\rm i}^{0.216} $ with a regression coefficient (R2) of 0.975. This shows a very weak dependence of the equilibrium d32 on ϕ.

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“…Two acrylic columns having internal diameters of 25 and 140 mm are used. A rigid borescope [22][23][24][25][26][27][28][29][30][31] (Olympus) with a 60 o field of view and 0 o direction of view is used to obtain particle images in a dynamic system. The borescope has a diameter of 6 mm and length of 250 mm.…”

Section: Methodsmentioning

confidence: 99%

Determination of Actual Object Size Distribution from Direct Imaging

Hossain¹,

Chen²,

Yang³

et al. 2009

Ind. Eng. Chem. Res.

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Direct imaging is a technique commonly used in the study of particle, bubble, and droplet size distribution in a dynamic system. Objects such as particles, bubbles, and droplets can be present at various distances from the imaging device when images are captured. Hence, the location of the object will need to be known in order to determine the actual size of an individual object. However, the location of the object cannot be determined from a single image. A single calibration scale defined at the focusing plane is normally used for the determination of all the object sizes from images. When the focus is close to the imaging device, the change in magnification with location is large. The size distribution obtained from the use of a single calibration scale would thus give a considerable deviation from the actual size distribution. In this study, a statistical method is proposed to reconstruct the actual object size distribution from the experimental object size distribution obtained from images using a single calibration scale defined at the focusing plane. Experiments are performed to validate the accuracy of the proposed method on the particle size distribution determination in a settling system. The stability of the proposed method is also analyzed theoretically for imaging devices with different depth-of-field (DOF), focusing location, and change in magnification with distance.

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Influence of Physical Properties on Drop Size Distribution of Stirred Liquid‐Liquid Dispersions

Cited by 82 publications

References 15 publications

Coalescence efficiency model including electrostatic interactions in liquid/liquid dispersions

Coalescence efficiency model including electrostatic interactions in liquid/liquid dispersions

Drop Size Distribution in a Standard Twin‐Impeller Batch Mixer at High Dispersed‐Phase Volume Fraction

Determination of Actual Object Size Distribution from Direct Imaging

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