Inverse-problem approach for particle digital holography: accurate location based on local optimization

We propose a microparticle localization scheme in digital holography. Most conventional digital holography methods are based on Fresnel transform and present several problems such as twin-image noise, border effects, and other effects. To avoid these difficulties, we propose an inverse-problem approach, which yields the optimal particle set that best models the observed hologram image. We resolve this global optimization problem by conventional particle detection followed by a local refinement for each particle. Results for both simulated and real digital holograms show strong improvement in the localization of the particles, particularly along the depth dimension. In our simulations, the position precision is > or =1 microm rms. Our results also show that the localization precision does not deteriorate for particles near the edge of the field of view.     

Measurement of microchannel flow with digital holographic microscopy by integrated nearest neighbor and cross-correlation particle pairing

A micro digital in-line holographic particle tracking velocimetry (micro-DHPTV) system has been developed and applied to investigate the three-dimensional flow field in straight and Y-junction microchannels. The micro-DHPTV system comprises a cooled frame-transfer CCD camera and a double-pulsed laser. The processing algorithm introduced to evaluate the three-dimensional velocity is based on the combination of integrated cross-correlation and nearest neighbor matching algorithms, taking advantage of information from both the reconstructed particle field and the original holograms fringes patterns. Tests on simulated pairs of holograms show that the particles can be detected, located, and paired with high probability and accuracy. Results obtained in the straight and Y-junction microchannels show that the superimposed vector field is physically reasonable.     

Effect of particle spatial distribution on particle deposition in ventilation rooms

We used simulations and experimental tests to investigate indoor particle deposition during four commonly used ventilation modes, including ceiling supply, side-up supply, side-down supply and bottom supply. We used a condensation monodisperse aerosol generator to generate fine diethylhexyl sebacate (DEHS) particles of different sizes along with two optical particle counters that measured particle concentration at the exhaust opening and inside a three-dimensional ventilated test room. We then simulated particle deposition using the same ventilation modes with computational fluid dynamics (CFD) method. Our simulated results indicate that mean deposition velocity/rate for particles 0.5–10 μm (aerodynamic diameter) is not affected by different ventilation modes. However, both our experimental and simulated results indicate that the deposition loss factor, a parameter defined based on mass balance principle to reflect the influence of particle distribution on deposited particle quantity, differ significantly by ventilation mode. This indicates that ventilation plays an important role in determining particle deposition due to the apparent differences in the spatial distribution of particles. The particle loss factor during ventilation modes characterized by upward air flow in the room is smaller than that of mixing ventilation; however this trend was strongly influenced by the relative location of the inlets, outlets and aerosol source.     

Real-time shape-based particle separation and detailed in situ particle shape characterization

Particle shape is an important attribute in determining particle properties and behavior, but it is difficult to control and characterize. We present a new portable system that offers, for the first time, the ability to separate particles with different shapes and characterize their chemical and physical properties, including their dynamic shape factors (DSFs) in the transition and free-molecular regimes, with high precision, in situ, and in real-time. The system uses an aerosol particle mass analyzer (APM) to classify particles of one mass-to-charge ratio, transporting them to a differential mobility analyzer (DMA) that is tuned to select particles of one charge, mobility diameter, and for particles with one density, one shape. These uniform particles are then ready for use and/or characterization by any application or analytical tool. We combine the APM and DMA with our single-particle mass spectrometer, SPLAT II, to form the ADS and demonstrate its utility to measure individual particle compositions, vacuum aerodynamic diameters, and particle DSFs in two flow regimes for each selected shape. We applied the ADS to the characterization of aspherical ammonium sulfate and NaCl particles, demonstrating that both have a wide distribution of particle shapes with DSFs from approximately 1 to 1.5.     

A device for measuring the concentration and dispersion quality ofmagnetic particle suspensions

A technique, called rheomagnetic measurement, for studying the concentration and orientation of magnetic particles through inductance measurement is presented. The particles are oriented in a predominantly extensional flow field, and, because they are magnetic, their orientation can be detected with a weak magnetic sensing field. Because flocs of magnetic particles orient differently in a flow field than primary particles do, this method can be useful in obtaining information about the particle flocculation aspect of dispersion quality. A magnetic sensing field can also be used to detect the particle concentration in a quiescent flow. Experimental data on the effects of particle concentration and milling for rod-like γ-Fe₂O₃ and plate-like Ba-ferrite suspensions are discussed. The results for Ba-ferrite magnetic markedly contrast with those for the rod-like magnetic particles but showed similarity with those for rod-like γ-Fe₂O₃     

A hierarchical approach to simulate the packing density of particle mixtures on a computer

In many fields of materials science it is important to know how densely a particle mixture can be packed. The “packing density” is the ratio of the particle volume and the volume of the surrounding container needed for a random close packing of the particles. We present a method for estimating the packing density for spherical particles based on computer simulations only, i.e. without the need for additional experiments. Our method is particularly suited for particle mixtures with an extremely wide range of particle diameters as they occur e.g. in modern concrete mixtures. A single representative sample from such mixtures would be much larger than can be handled on present standard computers. In our hierarchical approach the diameter range is therefore divided into smaller intervals. Samples from these limited diameter intervals are drawn and their packing density is estimated from a simulated packing. The results are used to “fill” the interstices in the sample from the next larger particle interval. To account for the interaction between particles of different sizes we include larger particles into the sample of smaller ones. The larger ones act as part of the boundary during the packing. Thus we obtain more realistic estimates of how dense a fraction of particles can be packed within the whole mixture. The focus of this paper is on the divide-and-conquer approach and on how the simulation results from the fractions can be collected into an overall estimate of the packing density. We do not go into details of the simulation technique for the single packing. We compare our results to some experimental data to show that our method works at least as good as the classical analytical models like CPM without the need for any experiments.     

Theory of inversion with two-dimensional regularization: profiles of microphysical particle properties derived from multiwavelength lidar measurements

We present the theory of inversion with two-dimensional regularization. We use this novel method to retrieve profiles of microphysical properties of atmospheric particles from profiles of optical properties acquired with multiwavelength Raman lidar. This technique is the first attempt to the best of our knowledge, toward an operational inversion algorithm, which is strongly needed in view of multiwavelength Raman lidar networks. The new algorithm has several advantages over the inversion with so-called classical one-dimensional regularization. Extensive data postprocessing procedures, which are needed to obtain a sensible physical solution space with the classical approach, are reduced. Data analysis, which strongly depends on the experience of the operator, is put on a more objective basis. Thus, we strongly increase unsupervised data analysis. First results from simulation studies show that the new methodology in many cases outperforms our old methodology regarding accuracy of retrieved particle effective radius, and number, surface-area, and volume concentration. The real and the imaginary parts of the complex refractive index can be estimated with at least as equal accuracy as with our old method of inversion with one-dimensional regularization. However, our results on retrieval accuracy still have to be verified in a much larger simulation study.     

Modeling of the signals of an optical particle counter for real nonspherical particles

An optical particle counter (OPC) was exposed to atmospheric particles of diameters of 200, 300, and 400 nm. The OPC data were combined with the results of single-particle analysis with a transmission electron microscope (TEM) on samples taken in parallel with the OPC measurements. With a T-matrix-based optical model the measured OPC spectra of scattered light pulses could be approximated with good precision. With an algorithm that simulated the response of the OPC to a given population of model particles derived from the TEM results, average absorption properties of different particle types were retrieved. For mobility sizes of 400 nm, higher light absorption was retrieved with the optical model for soot aggregates than for the rest of the morphological particle types. At smaller mobility sizes no compositional information could be derived from the model particles derived from the TEM data. Despite the limited success of the new methodology applied to the present experiment the results encourage the use of OPCs in combination with electrical mobility analyzers to derive more than aerosol-size distributions. With state-of-the-art pulse-height analysis the light-scattering pulses could be resolved with much finer resolution than in the instrument used.     

Camera self-calibration method suitable for variant camera constraints

This paper presents a self-calibration algorithm that seeks the camera intrinsic parameters to minimize the sum of squared distances between the measured and reprojected image points. By exploiting the constraints provided by the fundamental matrices, the function to be minimized can be directly reduced to a function of the camera intrinsic parameters; thus variant camera constraints such as fixed or varying focal lengths can be easily imposed by controlling the parameters of the resulting function. We employed the simplex method to minimize the resulting function and tested the proposed algorithm on some simulated and real data. The experimental results demonstrate that our algorithm performs well for variant camera constraints and for two-view and multiple-view cases.     

Intrinsic speckle noise in off-axis particle holography

In holographic imaging of particle fields, the interference among coherent wave fronts associated with particle scattering gives rise to intrinsic speckle noise, which sets a fundamental limit on the amount of information that particle holography can deliver. It has been established that the intrinsic speckle noise is especially severe in in-line holography because of superposition of virtual image waves, the direct transmitted wave, and the real image. However, at sufficiently high particle number densities, such as those typical in holographic particle image velocimetry (HPIV) applications, intrinsic speckle noise also arises in off-axis particle holography from self-interference among wave fronts that form the real image of particles. To overcome the latter problem we have constructed a mathematical model that relates the first- and second-order statistical properties of the intrinsic speckle noise to relevant holographic system parameters. Consistent with our experimental data, the model provides a direct estimate of the information capacity of particle holography. We show that the noise-limited information capacity can be expressed as the product of particle number density and the extent of the particle field along the optical axis. A large angular aperture of the hologram contributes directly to achievement of high information capacity. We also show that filtering in either digital or optical form is generally ineffective in removing the intrinsic speckle noise from the particle image as a result of the similar spectral properties of the two. These findings emphasize the importance of angular aperture in designing holographic particle imaging systems.     

Vertical profiles of microphysical particle properties derived from inversion with two-dimensional regularization of multiwavelength Raman lidar data: experiment

Inversion with two-dimensional (2-D) regularization is a new methodology that can be used for the retrieval of profiles of microphysical properties, e.g., effective radius and complex refractive index of atmospheric particles from complete (or sections) of profiles of optical particle properties. The optical profiles are acquired with multiwavelength Raman lidar. Previous simulations with synthetic data have shown advantages in terms of retrieval accuracy compared to our so-called classical one-dimensional (1-D) regularization, which is a method mostly used in the European Aerosol Research Lidar Network (EARLINET). The 1-D regularization suffers from flaws such as retrieval accuracy, speed, and ability for error analysis. In this contribution, we test for the first time the performance of the new 2-D regularization algorithm on the basis of experimental data. We measured with lidar an aged biomass-burning plume over West/Central Europe. For comparison, we use particle in situ data taken in the smoke plume during research aircraft flights upwind of the lidar. We find good agreement for effective radius and volume, surface-area, and number concentrations. The retrieved complex refractive index on average is lower than what we find from the in situ observations. Accordingly, the single-scattering albedo that we obtain from the inversion is higher than what we obtain from the aircraft data. In view of the difficult measurement situation, i.e., the large spatial and temporal distances between aircraft and lidar measurements, this test of our new inversion methodology is satisfactory.     

Automatic threshold technique for holographic particle field characterization

The 3D distribution of a particle field by digital holography is obtained by 3D numerical reconstruction of a 2D hologram. The proper identification of particles from the background during numerical reconstruction influences the overall effectiveness of the technique. The selection of a suitable threshold value to segment particles from the background of reconstructed images during 3D holographic reconstruction process is a critical issue, which influences the accuracy of particle size and number density of reconstructed particles. The object particle field parameters, such as depth of sample volume and density of object particles, influence the optimal threshold value. The present study proposes a novel technique for the determination of the optimal threshold value of a reconstructed image. The effectiveness of the proposed technique is demonstrated using both simulated and experimental data. The proposed technique is robust to variation in optical properties of particle and background, depth of sample volume, and number density of object particle field. The particle diameter obtained from the proposed threshold technique is within 5% of that obtained from the particle size analyzer. There is a maximum ten times increase in reconstruction effectiveness by using the proposed automatic threshold technique in comparison with the fixed manual threshold technique.     

Improved inversion procedure for particle size distribution determination by photon correlation spectroscopy

We propose a minimum variation of solution method to determine the optimal regularization parameter for singular value decomposition for obtaining the initial distribution for a Chahine iterative algorithm used to determine the particle size distribution from photon correlation spectroscopy data. We impose a nonnegativity constraint to make the initial distribution more realistic. The minimum variation of solution is a single constraint method and we show that a better regularization parameter may be obtained by increasing the discrimination between adjacent values. We developed the S-R curve method as a means of determining the modest iterative solution from the Chahine algorithm. The S-R curve method requires a smoothing operator. We have used simulated data to verify our new method and applied it to real data. Both simulated and experimental data show that the method works well and that the first derivative smoothing operator in the S-R curve gives the best results.     

An expert system for chemical speciation of individual particles using low-Z particle electron probe X-ray microanalysis data

An electron probe X-ray microanalysis (EPMA) technique, using an energy-dispersive X-ray detector with an ultrathin window, designated a low-Z particle EPMA, has been developed. The low-Z particle EPMA allows the quantitative determination of concentrations of low-Z elements, such as C, N, and O, as well as chemical elements that can be analyzed by conventional energy-dispersive EPMA, in individual particles. Since a data set is usually composed of data for several thousands of particles in order to make environmentally meaningful observations of real atmospheric aerosol samples, the development of a method that fully extracts chemical information contained in the low-Z particle EPMA data is important. An expert system that can rapidly and reliably perform chemical speciation from the low-Z particle EPMA data is presented. This expert system tries to mimic the logic used by experts and is implemented by applying macroprogramming available in MS Excel software. Its feasibility is confirmed by applying the expert system to data for various types of standard particles and a real atmospheric aerosol sample. By applying the expert system, the time necessary for chemical speciation becomes shortened very much and detailed information on particle data can be saved and extracted later if more information is needed for further analysis.     

Three-dimensional particle tracking with subnanometer resolution using off-focus images

A three-dimensional (3D) particle tracking algorithm based on microscope off-focus images is presented in this paper. Subnanometer resolution in all three axes at 400 Hz sampling rate is achieved using a complementary metal-oxide-semiconductor (CMOS) camera. At each sampling, the lateral position of the spherical particle is first estimated by the centroid method. The axial position is then estimated by comparing the radius vector, which is converted from the off-focus two-dimensional image of the particle with no information loss, with an object-specific model, calibrated automatically prior to each experiment. Estimation bias and variance of the 3D tracking algorithm are characterized through analytical analysis. It leads to an analytical model, enabling prediction of the measurement performance based on calibration data. Finally, experimental results are presented to illustrate the performance of the measurement method in terms of precision and range. The validity of the theoretical analysis is also experimentally confirmed.     

Spatially-resolved photocapacitance measurements to study defects in a-Si:H based p–i–n particle detectors

Thick large-area particle or X-ray detectors suffer degradation during operation due to creation of defects that act as deep traps. Measuring the photocurrent under homogeneously absorbed weak light can monitor variation in detector performance. We describe how photocapacitance can be used as an alternative method to measure the creation of defects and their energy level after intense irradiation with protons or He ions at 1.5 MeV and after exposure to intense laser pulses. The possibility to detect small areas of high defect density in a large-area detector structure is discussed.     

Compact infrared cryogenic wafer-level camera: design and experimental validation

We present a compact infrared cryogenic multichannel camera with a wide field of view equal to 120°. By merging the optics with the detector, the concept is compatible with both cryogenic constraints and wafer-level fabrication. The design strategy of such a camera is described, as well as its fabrication and integration process. Its characterization has been carried out in terms of the modulation transfer function and the noise equivalent temperature difference (NETD). The optical system is limited by the diffraction. By cooling the optics, we achieve a very low NETD equal to 15 mK compared with traditional infrared cameras. A postprocessing algorithm that aims at reconstructing a well-sampled image from the set of undersampled raw subimages produced by the camera is proposed and validated on experimental images.     

Experimental and numerical modeling of particle levitation and movement behavior on traveling-wave electric curtain for particle removal

Traveling-wave electric curtain (EC) has been developed for potential application in particle removal/shield on solar panels and other surfaces. Levitation and transport of a particle in a traveling-wave electric field were simulated. Results show that levitation directions/angles and levitation trajectories differ because of the difference in starting positions and starting times. The particles in the two positive acceleration regions are levitated in opposite directions, and the particles distributed on the dielectric surface are levitated and transported successively rather than simultaneously. Movement trajectories are complex and affected by various factors. In the current paper, movement trajectories are modeled to analyze which motion modes are advantageous or disadvantageous to particle removal. This process is beneficial to elucidate the mechanism of particle removal and provide a guidance for movement control by designing appropriate operating parameters.     

The development of the measurement of particle concentration using a commercial laser diffraction particle size analyzer

A laser diffraction particle size analyzer based on the Fraunhofer diffraction theory has the advantages of real-time measurement of particle size distribution over a broad range. However, the dispersed particle number concentration is not displayed in commercially available analyzers. The method of measuring the dispersed particle number concentration was investigated for different particles having various shapes, i.e. spherical, cubical and prismoidal with a log-normal distribution, by considering the characteristics of the measured voltage of the set detector in relation to the diffracted light intensity using a commercial laser diffraction particle size analyzer. As a result, an approximate equation for the particle number concentration was proposed expressing the measured median diameter and the highest voltage measured by the detector. This equation was applicable to particles having various shapes, i.e. spherical, cubical and prismoidal. Furthermore, this technique can be used for the continuous measurement of the particle number concentration of growing crystals in the crystallizer for crystallization operation.     

Commercial spectrophotometer for particle sizing

Particle-size distribution and the concentration of polystyrene particles suspended in water were accurately recovered from the inversion of spectral extinction data measured with a commercial spectrophotometer. The instrument was modified by placing a spatial filter in the collection optics to prevent low-angle scattered light from affecting the measurement of transmitted power. The data were inverted by use of a nonlinear iterative algorithm. When the extinction coefficient is measured in the lambda range of 0.3-1.1 mum, the particle distributions can be retrieved over a diameter range of 0.6-2.8 mum for a wide interval of sample concentrations. The average diameters are recovered with a precision of better than +/-1% and with accuracies consistent with the uncertainties by which the nominal diameters are known. The relative standard deviations of distributions corresponding to monodisperse samples are +/-5-10%, whereas the accuracy on the measured concentrations is ~5%.