The real origin of lognormal size distributions of nanoparticles in vapor growth processes

Kiss, L.B.; Söderlund, J.; Niklasson, Gunnar A.; Granqvist, Claes G.

doi:10.1016/s0965-9773(99)00128-2

Cited by 58 publications

(31 citation statements)

References 18 publications

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“…which is a good approximation for the gas-phase synthesis of nanoparticles (Medalia, 1982;Köylü & Faeth, 1992;Kiss, Sönderlund, Niklasson, & Granqvist, 1999) may be assumed, and the count median diameter d med and geometric standard deviation g as characteristic parameters of this distribution are then to be determined. These parameters may be obtained by a direct multi-dimensional non-linear regression (Lehre et al, 2003), i.e., finding an optimum with a variation of test distributions, which of course requires additional computing time and thus complicates in situ application to transient processes.…”

Section: Data Evaluationmentioning

confidence: 99%

On heat conduction between laser-heated nanoparticles and a surrounding gas

Kuhlmann

Reimann

Will

2006

Journal of Aerosol Science

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Section: Data Evaluationmentioning

confidence: 99%

On heat conduction between laser-heated nanoparticles and a surrounding gas

Kuhlmann

Reimann

Will

2006

Journal of Aerosol Science

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“…Many studies (14,15) have explained this polydispersity by the Brownian coagulation model. Another model (16), based on a random residence time approach, proposes that particles are moving by diffusion and drift through a finite growth zone. The particle size is assumed to be a power function of growth time, and the final size distribution is determined by the first passage time.…”

Section: Introductionmentioning

confidence: 99%

Development of magnetic chromatography to sort polydisperse nanoparticles in ferrofluids

Forge

Gossuin

Roch

et al. 2010

Contrast Media & Molecular

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Whatever the strategy of synthesis, nanoparticles in magnetic fluids commonly feature a broad size distribution. However, the presence of several size populations in ferrofluids is often problematic because of the close relationship between the efficiency of the nanoparticles and their physicochemical properties. In this work, a magnetic size sorting procedure is developed in order to reduce this polydispersity, using the magnetic properties of the iron oxide nanoparticles. This magnetic sorting with an adjustable magnetic field allows isolation of the small superparamagnetic particles as well as the larger particles. Magnetometry, nuclear magnetic relaxation dispersion profiles and transmission electron microscopy were successfully used to check the efficiency of the magnetic sorting procedure, which was shown to work as a 'magnetic' chromatography.

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“…2, we present a statistical analysis of the size distribution of Ge nanocrystals. We obtained a very good modified log normal fit to the data [22]. We note the absence of nanocrystals near the interface for a narrow band of oxide layer.…”

Section: Resultsmentioning

confidence: 63%