Speckle size, intensity and contrast measurement application in micron-size particle concentration assessment

Chicea, Dan

doi:10.1051/epjap:2007163

Cited by 22 publications

(22 citation statements)

References 17 publications

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“…(3) and the two-parameters Gegenbauer kernel phase function are the most commonly used [23][24][25].…”

Section: Static Light Scattering Particle Sizingmentioning

confidence: 99%

“…The work reported in [21,22] uses a transmission optical set-up to measure the far field parameters like contrast and speckle size revealing that they are related to the average particle diameter. Reference [23] revealed a strong variation of the average speckle size and contrast with the concentration of the scattering centers. In a diluted aqueous suspension as aggregates are formed, both the concentration and the size of the scattering centers change in time, therefore these far field parameters are not suited for monitoring the nanoparticle aggregation process.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Revealing Magnetite Nanoparticles Aggregation Dynamics – A SLS and DLS Study

Chicea

2010

Engineering Materials

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Fe 3 O 4 nanoparticles in aqueous suspensions are not stable but aggregate, tremendously changing the rheological properties of the nanofluid. Modified version of both the Static Light Scattering (SLS) setup and of Dynamic Light Scattering (DLS) setup experiment were used to monitor Fe 3 O 4 nanoparticle aggregation in aqueous diluted suspension. The experiments are described in detail and the variation of the average aggregate diameter in time is presented in this work.

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“…(3) and the two-parameters Gegenbauer kernel phase function are the most commonly used [23][24][25].…”

Section: Static Light Scattering Particle Sizingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Revealing Magnetite Nanoparticles Aggregation Dynamics – A SLS and DLS Study

Chicea

2010

Engineering Materials

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“…The size of the scattering centers influence parameters like average intensity, speckle size or speckle contrast in the interference image. The same parameters are affected by the concentration of the scattering centers [14], [15], [16], [17], [18]. As a consequence, a process where both the concentration and the size of the particles change with time, such as particles aggregation, cannot be monitored using the basic, first order, speckle statistics.…”

Section: Introductionmentioning

confidence: 99%

“…The theoretical foundation for this method is explained in many papers, such as [13], [16], and [17]. This paper presents an innovative alternative approach for extracting the size information from the time series recorded in a Dynamic Light Scattering experiment, using a specialized Neural Network.…”

Section: Introductionmentioning

confidence: 99%

Using Dynamic Light Scattering Experimental Setup and Neural Networks For Particle Sizing

Rei

Chicea

2017

ACTA Universitatis Cibiniensis

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Using a Lorentzian function fit as reference, a basic experiment was designed for processing IntroductionThe study of nanoparticles is a topic of major interest in the last decades due to the wide array of applications, especially in the area of biology and medicine. As a consequence of their small size, one order of magnitude smaller than the living cells, they can be used to deliver various substances to living cells, producing, in general, only minor perturbations. The applications of these nanomaterials were presented in several papers, such as [1]. During development of these applications, there were concerns about the toxicity of these methods. As a result, techniques for monitoring the nanoparticles concentration were also developed [2].The properties of the systems of nanoparticles are in direct relation to the size distribution of the particles in the fluid. For this reason, the size characterization of these systems is one relevant aspect for further development of the nanotechnology applications. There are various techniques used for this. One modern technique is the Transmission Electron Microscopy (TEM) which evaluates particles in the range from nanometers to micrometers. This method has a good resolution but is in general expensive, time consuming and does not work in-situ. Another method is the X-Ray powder diffraction which can offer the size distribution of the particles [3]. For metal oxides, for which the assumption used is that the crystallite size is the same as the particle size, the Scherrer equation [4] can offer the mean particle size. For colloidal particles, the Guinier formula [5] can be used in a similar way. However, also these two methods are slow and do not work in-situ. The particle size for nano-systems can also be assessed by the method called "Atomic Force Microscopy" (AFM) [6], [7]. Paper [7] shows a comparison of AFM with TEM. Results show that AFM sizing requires very thin samples over several layers. The samples are scanned line by line and this takes a lot of time. Comparisons and reviews of other techniques used for nanoparticle size characterization are presented in many papers, such as [8]. As in [9], the properties of the nanofluid change very fast during nanoparticle aggregation, and as a consequence, a fast procedure for monitoring the size is needed. A valid option for this are the optical procedures, which use coherent light scattering.The optical methods make use of an incident coherent beam of light which illuminates an active sample volume containing the nanoparticles. Each particle represents a scattering center and becomes a secondary light source. The intensity of the scattered light is anisotropic and depends on the size and shape of the scattering centers. This is described by the phase function, for which there are several models used to represent it [10], [11], [12].If the incident beam is coherent, so are the secondary waves emitted by each scattering center. If a screen or a detector is present, all the wavelets emitted by all the scattering...

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“…The most common nanoparticles for nanofluids are generally metallic and nonmetallic materials such as Al 2 O 3 , Ag, CuO, Cu, SiO 2 and TiO 2 [36][37][38]. The movement of nanoparticles plays a significant role in the anomalously increased heat transfer properties of the nanofluids [39,40]. So, it is of great importance to find out a robust method to measure the movements of nanoparticles in nanofluids, in order to understanding the heat transfer enhancement mechanism.…”

Section: Introductionmentioning

confidence: 99%

Crossing statistics of laser light scattered through a nanofluid

Pirlar¹,

Movahed

Razzaghi

et al. 2017

J. Opt. Soc. Am. A

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In this paper, we investigate the crossing statistics of speckle patterns formed in the Fresnel diffraction region by a laser beam scattering through a nanofluid. We extend zero-crossing statistics to assess the dynamical properties of the nanofluid. According to the joint probability density function of laser beam fluctuation and its time derivative, the theoretical frameworks for Gaussian and non-Gaussian regimes are revisited. We count the number of crossings not only at zero level but also for all available thresholds to determine the average speed of moving particles. Using a probabilistic framework in determining crossing statistics, a priori Gaussianity is not essentially considered; therefore, even in the presence of deviation from Gaussian fluctuation, this modified approach is capable of computing relevant quantities, such as mean value of speed, more precisely. Generalized total crossing, which represents the weighted summation of crossings for all thresholds to quantify small deviation from Gaussian statistics, is introduced. This criterion can also manipulate the contribution of noises and trends to infer reliable physical quantities. The characteristic time scale for having successive crossings at a given threshold is defined. In our experimental setup, we find that increasing sample temperature leads to more consistency between Gaussian and perturbative non-Gaussian predictions. The maximum number of crossings does not necessarily occur at mean level, indicating that we should take into account other levels in addition to zero level to achieve more accurate assessments.

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Speckle size, intensity and contrast measurement application in micron-size particle concentration assessment

Cited by 22 publications

References 17 publications

Revealing Magnetite Nanoparticles Aggregation Dynamics – A SLS and DLS Study

Revealing Magnetite Nanoparticles Aggregation Dynamics – A SLS and DLS Study

Using Dynamic Light Scattering Experimental Setup and Neural Networks For Particle Sizing

Crossing statistics of laser light scattered through a nanofluid

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