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  4. 2008
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  2. Topics
  3. Nanoparticle tracking analysis
  4. 2008
Showing papers on "Nanoparticle tracking analysis published in 2008"
Journal Article•10.1016/J.IDAIRYJ.2008.06.006•
Determination of heat-induced effects on the particle size distribution of casein micelles by dynamic light scattering and nanoparticle tracking analysis

[...]

Thu Tran Le1, Thu Tran Le2, Pieter Saveyn2, Hoang Dinh Hoa1, Paul Van der Meeren2 •
Hanoi University1, Ghent University2
01 Dec 2008-International Dairy Journal
TL;DR: In this article, the change in particle size distribution of casein micellar dispersions induced by heating both in the absence and presence of whey proteins was investigated by two techniques.

74 citations

Journal Article•
Nanoparticle tracking system analyzes polydispersed samples

[...]

Bob Carr
01 Jan 2008-Laser Focus World
TL;DR: The ability to see nanoparticles directly and individually allows a nanoparticle tracking analysis system to analyze samples with particles of varying sizes and shapes as mentioned in this paper, which can be used to detect and track nanoparticles.
Abstract: The ability to see nanoparticles directly and individually allows a nanoparticle tracking analysis system to analyze samples with particles of varying sizes and shapes.

4 citations

Accurate particle size distribution determination by nanoparticle tracking analysis based on 2-D Brownian dynamics simulation

[...]

Hans Saveyn, Bernard De Baets, B Hole, P Smith, Paul Van der Meeren 
1 Jan 2008
TL;DR: In this article, a physical model is presented to simulate the average step length distribution during nanoparticle tracking analysis experiments as a function of the particle size distribution and the distribution of the number of steps within the tracks.
Abstract: A physical model is presented to simulate the average step length distribution during nanoparticle tracking analysis experiments as a function of the particle size distribution and the distribution of the number of steps within the tracks. Considering only tracks of at least five steps, numerical simulation could be replaced by a normal distribution approximation. Based on this model, simulation of a step length distribution allows obtaining a much more reliable estimation of the particle size distribution, thereby reducing the artificial broadening of the distribution, as is typically observed by direct conversion of step length to particle size data. As this fitting procedure also allowed including data from particles that were followed for a relatively low number of steps, the measurement time could be reduced for particles that are known to be monodisperse. Whereas the inversion is less sensitive towards the particle size distribution width, still similar values were obtained for both the average diameter and standard deviation of a polystyrene latex sample irrespective of the track length, provided that the latter included at least five steps.

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