Light-scattering Patterns Research Articles

Spectral approach to recognize spherical particles among non-spherical ones by angle-resolved light scattering

Most of known light-scattering technologies, which allow one to separate spherical from non-spherical single particles, utilize either analysis of 2D light-scattering pattern or depolarization of light scattered. Both approaches force one to use high-sensitive detectors to provide a suitable signal to noise ratio for two-dimensionless photo matrix or for optical system with crossed polarizers. In this study, we introduce the method for discrimination of spherical and non-spherical single particles. The approach is based on measurement of leading, most intensive, element S11 of light-scattering matrix. To provide maximal signal to noise ratio we specified the light-scattering profile (LSP) in terms of integrated over azimuthal angle S11 as a function of polar scattering angle. The shape-sensitive vector-invariant for individual spherical particles was constructed from the parameters of LSP spectrum. The vector-invariant plays a role of the numerical criterion to identify spherical particles from LSPs. It can be applied to find a sphere with characteristics ranging from 16.5 to 70 and from 0.5 to 7.0 for size and phase-shift parameters respectively (size parameter α = πdn0/λ, where d – sphere diameter, λ – wavelength of the incident light, and n0 – medium refractive index, RI, phase-shift parameter ρ = 2α(m − 1), where relative RI m = n/n0 and n is the sphere RI). These ranges cover all possible characteristics of blood cells within the visible region of wavelengths. The ability of the vector-invariant to recognize spherical cells among non-spherical ones was tested theoretically by LSP databases of optical models of platelets and mature red blood cells. Moreover, experimentally the vector-invariant demonstrated good performance in searching of near-perfect spheres among milk fat globules, isolated nuclei of mononuclear cells, and completely spherized cells in a course of red blood cell lysis.

Label-free Identification of Bacteria Species Based on Divergence Angle Distribution of Light Scattering Patterns

Label-free Identification of Bacteria Species Based on Divergence Angle Distribution of Light Scattering Patterns

Improving trapping methods for buprestid beetles to enhance monitoring of native and invasive species

AbstractMost of the current understanding of the orientation and communication of jewel beetles arose from research on the Asian emerald ash borer (EAB), Agrilus planipennis, which has become one of the most destructive invasive forest insect pests in history following its introduction to North America and European Russia. From a European perspective, a number of jewel beetles have a high invasive risk similar to that of the emerald ash borer, including the potential threat of the bronze birch borer Agrilus anxius, the goldspotted oak borer Agrilus auroguttatus, and the twolined chestnut borer Agrilus bilineatus. Native jewel beetles expanding their geographic range include the cypress jewel beetle Ovalisia festiva and the black-banded oak borer Coraebus florentinus. Other native species are increasing in their importance, including the flathead oak borer Coraebus undatus, the two-spotted oak borer Agrilus biguttatus, the flatheaded beech borer Agrilus viridis and Agrilus cuprescens. Commonly used prism and multi-funnel trap designs and other promising experimental trap designs have been tested and compared in the US and in Europe. One factor considered has been colouration, typically purple and green. Another is olfactory attraction, both to plant volatiles and extracts such as (Z)-3-hexenol, Manuka oil, Phoebe oil and Cubeb oil, and also to pheromones such as (Z)-3-lactone, for emerald ash borer. Field observations have been made of mating and host-finding behaviours of oak buprestids based upon visual stimuli in North America and Europe. By using pinned dead EAB models, visual mating approaches have been observed by males of Agrilus biguttatus, Agrilus sulcicollis and Agrilus angustulus, which is a behaviour similar to that previously observed in EAB. Green plastic-covered branch-traps significantly out-performed other trap designs and caught more Agrilus jewel beetles if an artificial visual decoy that copies a beetle body was included. A higher fidelity decoy offered the same distinctive light-scattering pattern as real resting EAB females and elicited the full sequence of stereotypical male mating flight behaviour of EAB and A. biguttatus from up to 1 m away. An optimization of visual, olfactory and other possible stimuli has likely not yet been achieved. More sophisticated trap designs could lead to more sensitive detection capabilities with increased selectivity.

Convolutional neural networks for particle shape classification using light-scattering patterns

Particle shapes can be distinguished by the properties of optical light-scattering patterns. We investigate the feasibility of convolutional neural networks for shape-based classification using light-scattering patterns by mimicking a real application scenario of shape classification of micro-sized phytoplankton. Six different particle shapes were chosen. The volume-equivalent size parameter ranged from 2.98 to 14.89. The real part of refractive index was n = 1.06 ± 0.04. The particles were random oriented with respect to the direction of propagation of the incident light. The angular range of the light-scattering pattern in the data set was limited to 89–152° for the scattering angle and 0–63° for the azimuthal angle. Using a convolutional neural network trained with a pre-simulated database as a classifier, an average of above 97% classification accuracy is achieved. The results demonstrate the potential of convolutional neural networks to distinguish particle shape using light-scattering patterns.

Particle-shape classification using light scattering: An exercise in deep learning

We apply machine-learning algorithms to the calculated light-scattering patterns from particles having seven different common and naturally occurring shapes to assess the accuracy of shape classification based on light scattering. We consider different input data sets including one- and two-dimensional scattering functions of both intensity and polarization. Our scattering data set is produced from particles of volume-equivalent size parameter 5, and refractive index m = 1.5 + 0i. As expected, classification capabilities were much greater when the two-dimensional scattering data were used than when only one-dimensional data were considered. When the two-dimensional intensity patterns are considered, classification accuracies were approximately 70% for the regularly shaped particles and above 90% for the highly irregularly shaped particles. These capabilities increased slightly when linear polarization was used as input. Although all our results are specific to our particular data set, machine-learning techniques are easily generalizable. This exercise suggests that particle discrimination can be achieved in practical experiments using light-scattering patterns through deep learning.

Generation of aerosol-particle light-scattering patterns from digital holograms.

The similarity between the light-scattering pattern of a particle in the near-forward direction and diffraction from the particle's silhouette is investigated. Images of irregularly shaped free-flowing aerosol particles are obtained from digital hologram measurements, which are then binarized to yield a silhouette. Application of Huygens's principle to the silhouette generates an approximate scattering pattern, which when compared to the true measured pattern shows good agreement for particles much larger than the wavelength of light.

Optimal angular range for the Chin–Shifrin inversion algorithm in particle sizing by laser diffraction

In laser diffraction particle sizing measurements, only light in the range of forward small scattering angles is used to recover the particle size distribution (PSD). The Chin–Shifrin (C–S) integral transform algorithm is used to recover the particle size distributions (PSDs). However, this algorithm is based on the Fraunhofer diffraction theory, which may be used to approximate the scattered light pattern at small scattering angles. By comparing the inversion results recovered using the C–S algorithm from the two series of simulated light scattering data we determine the optimal range of angular integration for which the Fraunhofer diffraction approximation and the C–S algorithm may be used to reconstruct the PSD. One series is simulated using Mie scattering to calculate the true intensity pattern and for the other series is used to approximate the intensity pattern. For both series the data is calculated over a range of scattering angles. The effect of the deviation of the Fraunhofer diffraction pattern from the Mie scattering pattern is studied and the optimal range of angles is determined based on the inversion error of recovered PSD. The results show that the intensity pattern deviation will lead to variations in the recovered PSD. Also, the larger the angular range, the poorer the results. The optimal range of integration angle of the C–S algorithm for the various PSDs with different distribution widths and particle sizes is analyzed. The results indicate that the smaller the particle size and the wider the PSD, the smaller the optimal angular range.

Increase of light transmission of a Venlo-type greenhouse during winter by 10%: a design study

During winter and at higher latitudes, natural light is the limiting factor for crop growth in greenhouses. The design of Venlo-type greenhouses in the Netherlands has not changed for many years, although recent developments of diffuse glass with anti-reflective coatings might necessitate alteration of the roof design for maximized light transmissivity during winter. Light transmissivity of a greenhouse, in general, is influenced by roof slope, gutter orientation, roof shape, dimensions, position and reflectivity of construction elements, screen installation, position and transmissivity of screen material, transmissivity and light-scattering pattern of the covering and the effect of condensation on the inner side of the covering material or screen. Using the ray-tracing model RAYPRO (Swinkels et al., 2001), the integral effect of all individual and combined measures on light transmission of the greenhouse at crop level was calculated. The results show that it is possible to increase light transmission by more than 10% with a novel greenhouse roof concept. Results of ray-tracing calculations for individual and combined measures are described in this paper. After identifying the roof concept with the theoretically highest increase in light transmissivity during winter in the Netherlands, economic feasibility and all constructional restrictions were taken into account in close cooperation with industrial partners. This has led to a novel roof design that was built as a demonstration greenhouse on a scale of 500 m2 in summer 2016 at Wageningen University & Research station in Bleiswijk. This “winterlight greenhouse” had resulted in a re-design of the traditional Venlo-type greenhouse roof, covering and screen.

Surface roughness during depositional growth and sublimation of ice crystals

Abstract. Ice surface properties can modify the scattering properties of atmospheric ice crystals and therefore affect the radiative properties of mixed-phase and cirrus clouds. The Ice Roughness Investigation System (IRIS) is a new laboratory setup designed to investigate the conditions under which roughness develops on single ice crystals, based on their size, morphology and growth conditions (relative humidity and temperature). Ice roughness is quantified through the analysis of speckle in 2-D light-scattering patterns. Characterization of the setup shows that a supersaturation of 20 % with respect to ice and a temperature at the sample position as low as −40 ∘C could be achieved within IRIS. Investigations of the influence of humidity show that higher supersaturations with respect to ice lead to enhanced roughness and irregularities of ice crystal surfaces. Moreover, relative humidity oscillations lead to gradual “ratcheting-up” of roughness and irregularities, as the crystals undergo repeated growth–sublimation cycles. This memory effect also appears to result in reduced growth rates in later cycles. Thus, growth history, as well as supersaturation and temperature, influences ice crystal growth and properties, and future atmospheric models may benefit from its inclusion in the cloud evolution process and allow more accurate representation of not just roughness but crystal size too, and possibly also electrification properties.

Spectral solution of the inverse Mie problem

We developed a fast method to determine size and refractive index of homogeneous spheres from the power Fourier spectrum of their light-scattering patterns (LSPs), measured with the scanning flow cytometer. Specifically, we used two spectral parameters: the location of the non-zero peak and zero-frequency amplitude, and numerically inverted the map from the space of particle characteristics (size and refractive index) to the space of spectral parameters. The latter parameters can be reliably resolved only for particle size parameter greater than 11, and the inversion is unique only in the limited range of refractive index with upper limit between 1.1 and 1.25 (relative to the medium) depending on the size parameter and particular definition of uniqueness. The developed method was tested on two experimental samples, milk fat globules and spherized red blood cells, and resulted in accuracy not worse than the reference method based on the least-square fit of the LSP with the Mie theory. Moreover, for particles with significant deviation from the spherical shape the spectral method was much closer to the Mie-fit result than the estimated uncertainty of the latter. The spectral method also showed adequate results for synthetic LSPs of spheroids with aspect ratios up to 1.4. Overall, we present a general framework, which can be used to construct an inverse algorithm for any other experimental signals.

Fractal analysis of the Rayleigh Photoinduced Light Scattering Pattern from LiNbO3:Zn Crystals

Fractal analysis was used to study Rayleigh photoinduced light scattering (PILS) patterns in a series of LiNbO3:Zn single crystals (0.018–0.88 mass%) that were grown from the congruent melt and were promising as nonlinear optical materials with low photorefraction and coercive-field values. Results from fractal analysis and Raman light-scattering spectroscopy were compared. Extremes found on the time dependence of the fractal dimension of various layers of the PILS pattern speckle structure indicated that the concentration of laser-induced defects in the photorefractive crystal changed. The rate of change of the concentration of laser-induced defects depended non-linearly on the crystal Zn concentration. The form of congruent Zn-doped LiNbO3 crystals with the most ordered structure was identified.

The Microphysical Properties of Small Ice Particles Measured by the Small Ice Detector-3 Probe during the MACPEX Field Campaign

Abstract A reliable understanding of the microphysical properties of ice particles in atmospheric clouds is critical for assessing cloud radiative forcing effects in climate studies. Ice particle microphysical properties such as size, shape, and surface roughness all have substantial effects on the single-scattering characteristics of the particles. A recently developed ice particle probe, the Small Ice Detector-3 (SID-3), measures the two-dimensional near-forward light-scattering patterns of sampled ice particles. These scattering patterns provide a wealth of information for understanding the microphysical and radiative characteristics of ice particles. The SID-3 was operated successfully on 12 aircraft flights during the NASA Midlatitude Airborne Cirrus Properties Experiment (MACPEX) field campaign in April 2011. In this study, SID-3 measurements are used to investigate the frequency of occurrence of a number of ice particle properties observed during MACPEX. Individual scattering patterns (7.5°–23°) are used to infer properties of the observed particles as well as to calculate partial scattering functions (PSFs) for ensembles of particles in the measured size range (~5–100 μm). PSFs are compared to ray-tracing-based phase functions to infer additional properties of the particles. Two quantitative values—halo ratio and steepness ratio—are used to characterize PSFs. The MACPEX dataset suggests that most atmospheric ice particles have rough surfaces or are complex in nature. PSFs calculated for particles that were characterized as having smooth surfaces also appeared to more closely resemble rough crystal PSFs. PSFs measured with SID-3 compare well with those calculated for droxtals with rough surfaces.

Measurement of back-scattering patterns from single laser trapped aerosol particles in air

We demonstrate a method for measuring elastic back-scattering patterns from single laser trapped micron-sized particles, spanning the scattering angle range of θ=167.7°-180° and φ=0°-360° in spherical coordinates. We calibrated the apparatus by capturing light-scattering patterns of 10 μm diameter borosilicate glass microspheres and comparing their scattered intensities with Lorenz-Mie theory. Back-scattering patterns are also presented from a single trapped Johnson grass spore, two attached Johnson grass spores, and a cluster of Johnson grass spores. The method has potential use in characterizing airborne aerosol particles, and may be used to provide back-scattering data for lidar applications.

Inversion method based on stochastic optimization for particle sizing.

A stochastic inverse method is presented based on a hybrid evolutionary optimization algorithm (HEOA) to retrieve a monomodal particle-size distribution (PSD) from the angular distribution of scattered light. By solving an optimization problem, the HEOA (with the Fraunhofer approximation) retrieves the PSD from an intensity pattern generated by Mie theory. The analyzed light-scattering pattern can be attributed to unimodal normal, gamma, or lognormal distribution of spherical particles covering the interval of modal size parameters 46≤α≤150. The HEOA ensures convergence to the near-optimal solution during the optimization of a real-valued objective function by combining the advantages of a multimember evolution strategy and locally weighted linear regression. The numerical results show that our HEOA can be satisfactorily applied to solve the inverse light-scattering problem.

Simultaneous holographic imaging and light-scattering pattern measurement of individual microparticles.

This work combines digital holography with spatial filtering at two wavelengths to record the hologram and light-scattering pattern for a single particle using a color sensor. Particles 30-100 μm in size and with various shapes are considered. The results demonstrate the ability to unambiguously associate a complicated scattering pattern with the particle size, shape, and orientation.

Relation between clinical mature and immature lymphocyte cells in human peripheral blood and their spatial label free scattering patterns.

A single living cell's light scattering pattern (LSP) in the horizontal plane, which has been denoted as the cell's "2D fingerprint," may provide a powerful label-free detection tool in clinical applications. We have recently studied the LSP in spatial scattering planes, denoted as the cell's "3D fingerprint," for mature and immature lymphocyte cells in human peripheral blood. The effects of membrane size, morphology, and the existence of the nucleus on the spatial LSP are discussed. In order to distinguish clinical label-free mature and immature lymphocytes, the special features of the spatial LSP are studied by statistical method in both the spatial and frequency domains. Spatial LSP provides rich information on the cell's morphology and contents, which can distinguish mature from immature lymphocyte cells and hence ultimately it may be a useful label-free technique for clinical leukemia diagnosis.

Visualizing Light Scattering in Silicon Waveguides with Black Phosphorus Photodetectors.

A black phosphorus photodetector is utilized to investigate the light-scattering patterns of a silicon waveguide through wavelength- and polarization-dependent scanning photocurrent measurements. The photocurrent signals exhibit similar patterns to the light-intensity distribution of the waveguide calculated by finite-difference time-domain simulations, suggesting that photoexcited electron-hole pairs in the silicon waveguide can be injected into phosphorene to induce its photoresponse.

Mature red blood cells: from optical model to inverse light-scattering problem.

We propose a method for characterization of mature red blood cells (RBCs) morphology, based on measurement of light-scattering patterns (LSPs) of individual RBCs with the scanning flow cytometer and on solution of the inverse light-scattering (ILS) problem for each LSP. We considered a RBC shape model, corresponding to the minimal bending energy of the membrane with isotropic elasticity, and constructed an analytical approximation, which allows rapid simulation of the shape, given the diameter and minimal and maximal thicknesses. The ILS problem was solved by the nearest-neighbor interpolation using a preliminary calculated database of 250,000 theoretical LSPs. For each RBC in blood sample we determined three abovementioned shape characteristics and refractive index, which also allows us to calculate volume, surface area, sphericity index, spontaneous curvature, hemoglobin concentration and content.

Fractal analysis of photoinduced light-scattering patterns in stoichiometric LiNbO3 crystals

We have analyzed the fractal dimension of photoinduced light-scattering patterns in stoichiometric lithium niobate single crystals of different genesis and, based on this analysis, we have investigated the dynamics of manifestation of laser-induced defects in different layers of the photoinduced light-scattering pattern in these crystals. Energy transfer between photoinduced light-scattering layers has been revealed. We have shown that, as distinct from the method of investigation of the photoinduced light scattering by measuring the time dynamics of the opening angle of the indicatrix of the speckle structure of the photoinduced light scattering, the investigation of the time dynamics of the fractal dimension of different layers of the photoinduced light-scattering pattern makes it possible to register particular features of time changes of the order of laser-induced defects in the crystal.

Surprises and anomalies in acoustical and optical scattering and radiation forces

Experiments on radiation torques and negative radiation forces by various researchers display how the underlying wave-field geometry influences radiation forces. Other situations strongly influenced by wave-field geometry include high-order caustics present in light-scattering patterns of objects as simple as oblate drops of water or oblate bubbles of air in water. Related theoretical and experimental investigations are considered. Acoustic scattering enhancements associated with various guided waves are also examined. These include guided waves having negative group velocities and guided wave radiating wavefronts having a vanishing Gaussian curvature.