Preparation of Nanoemulsion from Sacha Inchi Oil/Water by Emulsion Phase Inversion Methods

The aim of this study was to develop a nanoemulsion of Sacha inchi oil for cosmetic application by the emulsion phase inversion (EPI) method. The influence of surfactant type and surfactant-to-oil ratio (SOR) on the particle size distributions of the nanoemulsion was studied. The results obtained showed that nanoemulsion droplet size, and stability of nanoemulsions were varied considerably. At optimal condition, the smallest size (41.43 ± 0.12 nm.) and high zeta potential values were obtained

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Oil-water emulsions: Particle size distributions from elastic light scattering data

Journal of Colloid and Interface Science ◽

10.1016/0021-9797(89)90015-5 ◽

1989 ◽

Vol 127 (1) ◽

pp. 147-155 ◽

Cited By ~ 20

Author(s):

Michael Hofer ◽

Josef Schurz ◽

Otto Glatter

Keyword(s):

Particle Size ◽

Light Scattering ◽

Scattering Data ◽

Size Distributions ◽

Particle Size Distributions ◽

Elastic Light Scattering ◽

Oil Water

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On the evolution of particle size distributions during the bulk synthesis of High-Impact Polystyrene using PBM: towards morphology and phase inversion prediction

Chemical Engineering Science ◽

10.1016/j.ces.2021.117027 ◽

2021 ◽

pp. 117027

Author(s):

J.M. Maffi ◽

D.A. Estenoz

Keyword(s):

Particle Size ◽

Phase Inversion ◽

High Impact ◽

Size Distributions ◽

Particle Size Distributions ◽

High Impact Polystyrene

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Electrophoretic Deposition of Nanocrystalline SiC Ceramics

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.314.33 ◽

2006 ◽

Vol 314 ◽

pp. 33-38 ◽

Cited By ~ 3

Author(s):

S. Wildhack ◽

Fritz Aldinger

Keyword(s):

Particle Size ◽

Zeta Potential ◽

Electrophoretic Deposition ◽

Deposition Time ◽

Auxiliary Information ◽

Size Distributions ◽

Particle Size Distributions ◽

Present Contribution ◽

Surface Conditions ◽

Sic Ceramics

In the present contribution, the electrophoretic deposition (EPD) of nanocrystalline SiC powders will be discussed. In order to avoid the electrolysis of water during deposition as well as oxygen uptake of the nanocrystalline SiC by hydrolysis reactions, nonaqueous solvents were tested including ethanol and diethyl formamide. The solvents were compared regarding their effect on particle size distributions and sedimentation tests. Auxiliary information on the surface conditions as a function of the acidity of the suspension was drawn from aqueous zeta-potential measurements. The influence of dispersants, binders and the type of powder on the suspension properties was studied, and EPD was performed. For promising solvent-dispersant systems, the film thickness, current and deposition time at a given voltage were monitored during EPD.

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Data inversion methods to determine sub-3 nm aerosol size distributions using the particle size magnifier

Atmospheric Measurement Techniques ◽

10.5194/amt-11-4477-2018 ◽

2018 ◽

Vol 11 (7) ◽

pp. 4477-4491 ◽

Cited By ~ 6

Author(s):

Runlong Cai ◽

Dongsen Yang ◽

Lauri R. Ahonen ◽

Linlin Shi ◽

Frans Korhonen ◽

...

Keyword(s):

Particle Size ◽

Particle Size Distribution ◽

Em Algorithm ◽

Kernel Function ◽

Function Method ◽

Size Distributions ◽

Particle Size Distributions ◽

Inversion Methods ◽

The Em Algorithm ◽

Stepwise Method

Abstract. Measuring particle size distribution accurately down to approximately 1 nm is needed for studying atmospheric new particle formation. The scanning particle size magnifier (PSM) using diethylene glycol as a working fluid has been used for measuring sub-3 nm atmospheric aerosol. A proper inversion method is required to recover the particle size distribution from PSM raw data. Similarly to other aerosol spectrometers and classifiers, PSM inversion can be deduced from a problem described by the Fredholm integral equation of the first kind. We tested the performance of the stepwise method, the kernel function method (Lehtipalo et al., 2014), the H&A linear inversion method (Hagen and Alofs, 1983), and the expectation–maximization (EM) algorithm. The stepwise method and the kernel function method were used in previous studies on PSM. The H&A method and the expectation–maximization algorithm were used in data inversion for the electrical mobility spectrometers and the diffusion batteries, respectively (Maher and Laird, 1985). In addition, Monte Carlo simulation and laboratory experiments were used to test the accuracy and precision of the particle size distributions recovered using four inversion methods. When all of the detected particles are larger than 3 nm, the stepwise method may report false sub-3 nm particle concentrations because an infinite resolution is assumed while the kernel function method and the H&A method occasionally report false sub-3 nm particles because of the unstable least squares method. The accuracy and precision of the recovered particle size distribution using the EM algorithm are the best among the tested four inversion methods. Compared to the kernel function method, the H&A method reduces the uncertainty while keeping a similar computational expense. The measuring uncertainties in the present scanning mode may contribute to the uncertainties of the recovered particle size distributions. We suggest using the EM algorithm to retrieve the particle size distributions using the particle number concentrations recorded by the PSM. Considering the relatively high computation expenses of the EM algorithm, the H&A method is recommended for preliminary data analysis. We also gave practical suggestions on PSM operation based on the inversion analysis.

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Data inversion methods to determine sub-3 nm aerosol size distributions using the Particle Size Magnifier

10.5194/amt-2018-35 ◽

2018 ◽

Author(s):

Runlong Cai ◽

Dongsen Yang ◽

Lauri R. Ahonen ◽

Linlin Shi ◽

Frans Korhonen ◽

...

Keyword(s):

Particle Size ◽

Particle Size Distribution ◽

Em Algorithm ◽

Size Distribution ◽

Kernel Function ◽

Function Method ◽

Size Distributions ◽

Particle Size Distributions ◽

Inversion Methods ◽

The Em Algorithm

Abstract. Measuring particle size distribution accurately down to approximately 1 nm is needed for studying atmospheric new particle formation. The scanning particle size magnifier (PSM) using diethylene glycol as the working fluid has been used for measuring sub-3 nm atmospheric aerosol. A proper inversion method is required to recover the particle size distribution from PSM raw data. Similar to other aerosol spectrometers and classifiers, PSM inversion can be deduced to a problem described by the Fredholm integral equation of the first kind. We tested the performance of the step-wising method, the kernel function method (Lehtipalo et al., 2014), the H&A linear inversion method (Hagen and Alofs, 1983), and the expectation-maximization (EM) algorithm. The step-wising method and the kernel function method were used in previous studies on PSM. The H&A method and the expectation-maximization algorithm were used in data inversion for the electrical mobility spectrometers and the diffusion batteries (Maher and Laird., 1985), respectively. In addition, Monte Carlo simulation and laboratory experiments were used to test the accuracy and precision of the particle size distributions recovered using four inversion methods. When all of the detected particles are larger than 3 nm, the step-wising method may report false sub-3 nm particle concentrations because of assuming an infinite resolution, while the kernel function method and the H&A method occasionally reports false sub-3 nm particles because of using the unstable least square method. The accuracy and precision of the recovered particle size distribution using the EM algorithm are the best among the tested four inversion methods. Compared to the kernel function method, the H&A method reduces the uncertainty while keeping a similar computational expense. The measuring uncertainties in the present scanning mode may contribute to the uncertainties of the recovered particle size distributions. We suggest using the EM algorithm to retrieve the particle size distributions using the particle number concentrations recorded by the PSM. Considering the relatively high computation expenses of the EM algorithm, the H&A method is recommended to be used for preliminary data analysis. We also gave practical suggestions on PSM operation based on the inversion analysis.

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