Search

ABSTRACT Polystyrene spheres ranging in diameter from 2, 5, 10, to 20 μm were embedded in five different types of thick organic films (> 50 μm) to serve as model systems to evaluate the use of time‐of‐flight secondary ion mass spectrometry for the localization and particle sizing of pharmaceuticals in orodispersible drug delivery films. It was found that certain films, such as gelatin and ethyl cellulose, are prone to developing micron‐scale topography which can affect the linearity of the sputter yield, which can ultimately affect the maximum analyzable depth. Surprisingly, the sputter yield of the film was more of a determining factor for affecting the measurement of spheres. It was possible to more accurately extract the true dimensions of the buried spheres in faster sputtering films, while slower sputtering films were associated with matrix effects and sputtering artifacts that degraded the quality of the reconstructed image. Signal attenuation was also found to be problematic and quite significant for certain film chemistries, which placed a limit on the size of the particles that could be visualized. Overall, visualization of particles embedded in thick organic films is possible, but the extraction of quantitative data such as size and the amount of material is difficult given the influence of sample dependent sputtering artifacts. [ABSTRACT FROM AUTHOR]

This paper presents the feasibility of Fraunhofer diffraction analysis as a measure of the size of fast‐moving inkjet droplets. This measurement method showed that an inkjet droplet measurement tool was possible with a good balance of real‐time measurement and accuracy. [ABSTRACT FROM AUTHOR]

Particle size distributions (PSDs) define the description of particle systems and of their separation processes in mechanical process engineering. Modern analytical methods, in particular image analysis, and their combination with material‐specific analytics record additional geometric and material parameters of particles. Many of these particle properties, like particle size, are not constant but also distributed, leading to a multi‐dimensional particle property distribution that can be used to describe particle processes. Thus, it is possible to define a partition function that quantifies separation in multidimensional space. The multidimensional approaches can be simply reduced in their dimensionality, so that the known one‐dimensional distribution functions, e.g., a PSD, can be obtained as marginal distributions. [ABSTRACT FROM AUTHOR]

Abstract: The particle size of polymer colloids is a key characteristic. It directly affects Raman measurements due to light scattering by particles. This publication exploits the extent to which these spectral changes can be correlated to the particle sizes by using a spectral hard model and data‐driven model. To this end, spectra of aqueous polystyrene nanoparticles are decomposed into pure component spectral models by means of indirect hard modeling (IHM). Each pure component model is characterized by multiple peak‐shaped Voigt profiles. By fitting the model to spectra of polymer colloids, spectral changes due to light scattering by particles are incorporated in the model parameters. The resulting parameter values are used as input for data‐driven partial least squares (PLS) regression to extract particle sizes. The method is applied to Raman spectra of polystyrene nanoparticles of 23–60 nm diameter measured repeatedly at concentrations 0.17–1 wt%. The hybrid model predicts the particle size with R2 = 0.99. In contrast, purely data‐driven PLS regression of the spectral intensities with 3 latent PLS variables results in R2 from 0.78 to 0.83. Resulting PLS scores portray a clear differentiability of Raman scattering and light scattering by particles within IHM model parameters. PLS regression coefficients further allow identification of individual peak parameters that correlate with particle size, which substantiates previous findings on correlation between Raman signal and scattering by polymer colloids. Combining IHM and data‐driven PLS regression demonstrates more accurate prediction of particle size for extended usage of Raman spectroscopy as comprehensive process analytical technology to determine sample concentrations and particle data. [ABSTRACT FROM AUTHOR]

The colonial microalga, Botryococcus braunii, produces and stores hydrocarbons in membranes and in colonies. Although hydrocarbons in B. braunii could easily be extracted for biofuel production, yields are actually poor without energy-intensive pretreatment such as thermal drying. To develop extraction methods without drying, we applied the mechanical cell disruption to wet B. braunii using either a high-pressure homogenizer, a bead mill, or a circulating particle disruptor (Jet-Paster) and examined the relationships between the extent of cell and/or colony disruption and extracted hydrocarbon yields using n-hexane. When the number of particles over 20 μm classified as colonies, decreased after each treatment, the hydrocarbon yields of samples treated (over 20%) were much larger than those without treatments (under 5%). Thus, the colony disruption may increase hydrocarbon yields by enhancing n-hexane penetration to the colony. Although the degree of disruption on the Jet-Paster treatment was the lowest (2.2-9.3%) and that of sample treated by the homogenizer was the highest (27-55%), extracted hydrocarbon yields were improved in both treatments. The facts indicate that disrupting large colonies into small colonies improves hydrocarbon recovery, and the fractionation of cells is not needed for hydrocarbon extraction from B. braunii. © 2017 Curtin University of Technology and John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY This paper describes how to numerically tackle the problem of counting and sizing particles by impedance measurement in an orifice-electrode system. The model allows to simulate the particle dynamics submitted to strong hydrodynamic stresses through a microorifice and to compute the voltage pulses generated by the modification of the inner dielectric medium. This approach gives important information about particles size distribution and allows to quantify the role of trajectory and orientation of particles on the size measurement. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Airborne inhalable particulate in the workplace can represent a significant health hazard, and one of the primary sources of particles is mist produced through the application of cutting fluids in machining operations. The atomization process is one of the principal mechanisms associated with cutting fluid mist formation and generates droplets from fifty to a few thousand micrometers in size. These particles subsequently undergo vaporization and settling effects resulting in an aerosol to which workers may be exposed. While a variety of equipment is available to characterize the fine particulate in the breathing zone, standard equipment to measure the size of the atomized droplets is not available. In this paper, an imaging system is employed to characterize the large droplets produced by atomization in turning. One of the drawbacks of such a system is the time-consuming experimental calibration procedure that is required to improve the accuracy of the droplet size measurements and extend the depth of field of the imaging system. With this in mind, an approach is introduced to predict droplet diameter based on measurement data without physical system calibration. The relationship between the actual diameter and the measured diameter is established based on an imaging system simulation model that includes a three dimensional point spread function and an image formation relationship grounded in the principles of geometric optics. These two components are combined using convolution integral theory to derive an image intensity profile. The introduction of halo width into the simulation greatly extends the image depth of field, which is a critical factor in capturing more droplets in one image and also minimizing particle size distribution bias towards larger droplets. The model predicts droplet diameter as a function of measured diameter and halo width. Model behavior of predicted diameters from the simulation compares well with those from a physical calibration of the system. The numerical calibration model is then used in the study of cutting fluid atomization in a turning process, and the measured droplet size distribution compares favorably with droplet sizes predicted by a mechanistic atomization model. [ABSTRACT FROM AUTHOR]

Characterization of dense polydisperse suspensions, with mean diameters 143 and 226 nm and volume fractions ranging from 0.03 to 0.27, was conducted using time-dependent measurements of multiply scattered light. Frequency-domain photon migration measurements of isotropic scattering coefficients at wavelengths between 488 and 828 nm were found to agree with those predicted from the Mie theory and the polydisperse hard-sphere Percus-Yevick model. The wavelength-dependent isotropic scattering data were then used to successfully recover the particle size distribution and volume fraction of the suspensions, by minimizing a nonlinear least-squares problem. The mean particle size and volume fractions were recovered within an error range of 0-15.53 and 0-24%, respectively, compared with dynamic light scattering results and experimentally measured volume fractions. [ABSTRACT FROM AUTHOR]

Dynamic light scattering (DLS) is a well-known noninvasive technique for investigating interactions of protein molecules in solution. Unfortunately, DLS is not very sensitive to small size changes because covariables, such as temperature, viscosity, and refractive index, are not precisely known, or they vary as functions of an experiment run, making it difficult to resolve subtle size changes of only a few Angström. It is usually not possible, if these covariables are not systematically measured and brought into the DLS analysis, to separate monomers from dimers when both are present in solution. We present here measurements with a variant of DLS that determines rotational diffusion as well as translation diffusion. This technique, called depolarized dynamic light scattering (DDLS) is, like DLS, also an old method, but it is rarely used due to enormous practical difficulties. However, we have found that a combination of DLS with DDLS is very promising, because it allows for a rough shape determination of the molecule under study and it is more sensitive to subtle size changes. We built an instrument that overcomes some of the difficulties, and report measurements made with this instrument. One of the samples was Photosystem-I, a membrane protein for photosynthesis. Its dimensions were determined to be 9.6nm thick and 26nm in diameter, values that are in good agreement with the dimensions obtained from X-ray diffraction analysis of single crystals. [ABSTRACT FROM AUTHOR]