Recent trends in particle size analysis techniques

Recent advances and developments in the particle-sizing technologies are briefly reviewed in accordance with three operating principles including particle size and shape descriptions. Significant trends of the particle size analysing equipment recently developed show that compact electronic circuitry and rapid data processing systems were mainly adopted in the instrument design. Some newly developed techniques characterizing the particulate system were also introduced

Pair distribution function and structure factor of spherical particles

The availability of neutron spallation-source instruments that provide total scattering powder diffraction has led to an increased application of real-space structure analysis using the pair distribution function. Currently, the analytical treatment of finite size effects within pair distribution refinement procedures is limited. To that end, an envelope function is derived which transforms the pair distribution function of an infinite solid into that of a spherical particle with the same crystal structure. Distributions of particle sizes are then considered, and the associated envelope function is used to predict the particle size distribution of an experimental sample of gold nanoparticles from its pair distribution function alone. Finally, complementing the wealth of existing diffraction analysis, the peak broadening for the structure factor of spherical particles, expressed as a convolution derived from the envelope functions, is calculated exactly for all particle size distributions considered, and peak maxima, offsets, and asymmetries are discussed.Comment: 7 pages, 6 figure

Validity of particle size analysis techniques for measurement of the attrition that occurs during vacuum agitated powder drying of needle-shaped particles

Analysis of needle-shaped particles of cellobiose octaacetate (COA) obtained from vacuum agitated drying experiments was performed using three particle size analysis techniques: laser diffraction (LD), focused beam reflectance measurements (FBRM) and dynamic image analysis. Comparative measurements were also made for various size fractions of granular particles of microcrystalline cellulose. The study demonstrated that the light scattering particle size methods (LD and FBRM) can be used qualitatively to study the attrition that occurs during drying of needle-shaped particles, however, for full quantitative analysis, image analysis is required. The algorithm used in analysis of LD data assumes the scattering particles are spherical regardless of the actual shape of the particles under evaluation. FBRM measures a chord length distribution (CLD) rather than the particle size distribution (PSD), which in the case of needles is weighted towards the needle width rather than their length. Dynamic image analysis allowed evaluation of the particles based on attributes of the needles such as length (e.g. the maximum Feret diameter) or width (e.g. the minimum Feret diameter) and as such, was the most informative of the techniques for the analysis of attrition that occurred during drying

Automated Particle Identification through Regression Analysis of Size, Shape and Colour

Rapid point of care diagnostic tests and tests to provide therapeutic information are now available for a range of specific conditions from the measurement of blood glucose levels for diabetes to card agglutination tests for parasitic infections. Due to a lack of specificity these test are often then backed up by more conventional lab based diagnostic methods for example a card agglutination test may be carried out for a suspected parasitic infection in the field and if positive a blood sample can then be sent to a lab for confirmation. The eventual diagnosis is often achieved by microscopic examination of the sample. In this paper we propose a computerized vision system for aiding in the diagnostic process; this system used a novel particle recognition algorithm to improve specificity and speed during the diagnostic process. We will show the detection and classification of different types of cells in a diluted blood sample using regression analysis of their size, shape and colour. The first step is to define the objects to be tracked by a Gaussian Mixture Model for background subtraction and binary opening and closing for noise suppression. After subtracting the objects of interest from the background the next challenge is to predict if a given object belongs to a certain category or not. This is a classification problem, and the output of the algorithm is a Boolean value (true/false). As such the computer program should be able to ”predict” with reasonable level of confidence if a given particle belongs to the kind we are looking for or not. We show the use of a binary logistic regression analysis with three continuous predictors: size, shape and color histogram. The results suggest this variables could be very useful in a logistic regression equation as they proved to have a relatively high predictive value on their own

Droplet activation, separation, and compositional analysis: laboratory studies and atmospheric measurements [Discussion paper]

Droplets produced in a cloud condensation nucleus chamber as a function of supersaturation have been separated from unactivated aerosol particles using counterflow virtual impaction. Residual material after droplets were evaporated was chemically analyzed with an Aerodyne Aerosol Mass Spectrometer and the Particle Analysis by Laser Mass Spectrometry instrument. Experiments were initially conducted to verify activation conditions for monodisperse ammonium sulfate particles and to determine the resulting droplet size distribution as a function of supersaturation. Based on the observed droplet size, the counterflow virtual impactor cut-size was set to differentiate droplets from unactivated interstitial particles. Validation experiments were then performed to verify that only droplets with sufficient size passed through the counterflow virtual impactor for subsequent analysis. A two-component external mixture of monodisperse particles was also exposed to a supersaturation which would activate one of the types (ammonium sulfate) but not the other (polystyrene latex spheres). The mass spectrum observed after separation indicated only the former, validating separation of droplets from unactivated particles. Results from atmospheric measurements using this technique indicate that aerosol particles often activate predominantly as a function of particle size. Chemical composition is not irrelevant, however, and we observed enhancement of sulfate in droplet residuals using single particle analysis

Towards a complete inventory of stratospheric dust particles, with implications for their classification

Several investigators have recently proposed classification schemes for stratospheric dust particles [1-3]. In addition, extraterrestrial materials within stratospheric dust collections may be used as a measure of micrometeorite flux [4]. However, little attention has been given to the problems of the stratospheric collection as a whole. Some of these problems include: (a) determination of accurate particle abundances at a given point in time; (b) the extent of bias in the particle selection process; (c) the variation of particle shape and chemistry with size; (d) the efficacy of proposed classification schemes and (e) an accurate determination of physical parameters associated with the particle collection process (e.g. minimum particle size collected, collection efficiency, variation of particle density with time). We present here preliminary results from SEM, EDS and, where appropriate, XRD analysis of all of the particles from a collection surface which sampled the stratosphere between 18 and 20km in altitude. Determinations of particle densities from this study may then be used to refine models of the behavior of particles in the stratosphere [5]

Coalescence of Pickering emulsion droplets induced by an electric field

Combining high-speed photography with electric current measurement, we investigate the electrocoalescence of Pickering emulsion droplets. Under high enough electric field, the originally-stable droplets coalesce via two distinct approaches: normal coalescence and abnormal coalescence. In the normal coalescence, a liquid bridge grows continuously and merges two droplets together, similar to the classical picture. In the abnormal coalescence, however, the bridge fails to grow indefinitely; instead it breaks up spontaneously due to the geometric constraint from particle shells. Such connecting-then-breaking cycles repeat multiple times, until a stable connection is established. In depth analysis indicates that the defect size in particle shells determines the exact merging behaviors: when the defect size is larger than a critical size around the particle diameter, normal coalescence will show up; while abnormal coalescence will appear for coatings with smaller defects.Comment: 5 pages, 5 figure

Spin glass like transition in a highly concentrated Fe-C nanoparticle system

A highly concentrated (17 vol.%) Fe-C nano-particle system, with a narrow size distribution $d = 5.4\pm 0.4$ nm, has been investigated using magnetic ac susceptibility measurements covering a wide range of frequencies (17 mHz - 170 Hz). A dynamic scaling analysis gives evidence for a phase transition to a low temperature spin-glass-like phase. The critical exponents associated with the transition are $z\nu = 10.5 \pm 2$ and $\beta = 1.1 \pm 0.2$. The reason why the scaling analysis works for this sample, while it may not work for other samples exhibiting collective behavior as evidenced by aging phenomena, is that the single particle contribution to $\chi''$ is vanishingly small for $T>T_g$ and hence all slow dynamics is due to collective behavior. This criterion can only be fulfilled for a highly concentrated nano-particle sample with a narrow size distribution.Comment: 2 pages, 3 figures, Proceeding for ICM200