We analyze the effect of contaminants on the quadrupolar magnetic, dipolar electric and dipolar magnetic resonances of silicon nanoparticles (NPs) by considering the spectral evolution of the linear polarization degree at right angle scattering configuration, PL(90°). From an optical point of view, a decrease in the purity of silicon nanoparticles due to the presence of contaminants impacts the NP effective refractive index. We study this effect for a silicon nanosphere of radius 200 nm embedded in different media. The weakness of the resonances induced on the PL(90°) spectrum because of the lack of purity can be used to quantify the contamination of the material. In addition, it is shown that Kerker conditions also suffer from a spectral shift, which is quantified as a function of material purity.
In this work, the super-thin cloud detection algorithm [1], that uses the polarization angle of the backscattered solar
radiation to find the super-thin clouds, is briefly reviewed and the retrieval of the optical thickness of these clouds is
proposed. We found that at the neighborhood angles of the backscattering direction, these clouds can be reliably
detected. The polarized components of the reflected light may be used to retrieve the optical thickness of these
clouds.
Scattering patterns are made available by the TAOS (Two-dimensional Angle-resolved Optical Scattering) method, which consists of detecting micrometer-sized single airborne aerosol particles and collecting the intensity of the light they scatter from a pulsed, monochromatic laser beam. TAOS patterns have been classified by a learning machine, the training stage of which depends on many control parameters. Patterns due to single bacterial spores (Bq class) have to be discriminated from those produced by outdoor aerosol particles (Kq set) and diesel soot aggregates (sq set), where both Kq and sq are assumed not to contain patterns of bacterial origin. This work describes two directions along which classification continues to develop: the enlargement of the control parameter set and the simultaneous processing of two areas (sectors) selected from the TAOS pattern. The latter algorithm is meant to make the classifier sensitive to simmetry exhibited by some patterns. The available classification scheme is summarized, as well as the rule by which discrimination is rated off-line. Discrimination based on one pattern sector alone scores fewer than 15% false negatives (misclassified Bq patterns) and false positives from Kq and sq. Discrimination based on the symmetry of two pattern sectors fails to recognize 30% of the Bq (bacterial) patterns, whereas < 5% Kq (environmental) patterns are assigned to the Bq class; false positives from sq (diesel) patterns drop to zero. The issue of false positives is briefly discussed in relation to the fraction of airborne bacteria found in aerosols.
A plane wave is scattered by a potential of bounded support. Translation, rotation and reflection of the potential,
q0 induce transformations of the scattered wave. The latter can be represented by means of Born sequences,
where q0 appears under the integral sign: non-local formulas are thus derived, the properties of which are
discussed. Next, the symmetries induced by the 1st BORN approximation are addressed. Invariance of the
squared modulus of the scattering amplitude holds for translation and reflection. The transformation Tε :=
13 +Σ3ℓ=1εℓAℓ, with {εℓ;} real and {Aℓ} the generators of rotations in IR3, is investigated. Conditions on the
{ε ℓ} are derived, by which the scattering amplitude coming from the first BORN approximation is invariant to Tε. As an application, these “false symmetries” are compared to those induced by limited angular resolution
of a detector in light scattering experiments. Namely, scattering patterns are made available by the TAOS
(Two-dimensional Angle-resolved Optical Scattering) method, which consists of detecting single airborne aerosol
particles and collecting the intensity of the light they scatter from a pulsed, monochromatic laser beam. The
optics and the detector properties determine the resolution at which a pattern is saved. The implications on the
performance of TAOS pattern analysis are briefly discussed.
Real-time detection and identification of bio-aerosol particles are crucial for the protection against chemical and
biological agents. The strong elastic light scattering properties of airborne particles provides a natural means for rapid,
non-invasive aerosol characterization. Recent theoretical predictions suggested that variations in the polarization
dependent angular scattering cross section could provide an efficient means of classifying different airborne particles. In
particular, the polarization dependent scattering cross section of aggregate particles is expected to depend on the shape
of the primary particles. In order to experimentally validate this prediction, we built a high throughput, sampling system,
capable of measuring the polarization resolved angular scattering cross section of individual aerosol particles flowing
through an interrogating volume with a single shot of laser pulse. We calibrated the system by comparing the
polarization dependent scattering cross section of individual polystyrene spheres with that predicted by Mie theory. We
then used the system to study different particles types: Polystyrene aggregates composed 500 nm spheres and Bacillus
subtilis (BG, Anthrax simulant) spores composed of elongated 500 nm × 1000 nm cylinder-line particles. We found that
the polarization resolved scattering cross section depends on the shape of the constituent elements of the aggregates.
This work indicates that the polarization resolved scattering cross section could be used for rapid discrimination between
different bio-aerosol particles.
We present a series of long-wave-infrared (LWIR) polarimetric-based thermal images of facial profiles in which polarization-state information of the image forming radiance is retained and displayed. The resultant polarimetric images show enhanced facial features, additional texture, and details that are not present in the corresponding conventional thermal imagery. It has been generally thought that conventional thermal imagery (MidiR or LWIR) could not produce the detailed spatial information required for reliable human identification due to the so-called "ghosting" effect often seen in thermal imagery of human subjects. By using polarimetric information, we are able to extract subtle surface features of the human face, thus improving subject identification. The considered polarimetric image sets include the conventional thermal intensity image, S0 , the two Stokes images, S1 and S2, and a Stokes image product called the degree-of-linear-polarization (DoLP) image. Finally, Stokes imagery is combined with Fresnel relations to extract additional 3D surface information.
Two-dimensional angle-resolved optical scattering (TAOS) is an experimental method which collects the intensity pattern of monochromatic light scattered by a single, micron-sized airborne particle. In general, the interpretation of these patterns and the retrieval of the particle refractive index, shape or size alone, are difficult problems. The solution proposed herewith relies on a learning machine (LM): rather than identifying airborne particles from their scattering patterns, TAOS patterns themselves are classified. The LM consists of two interacting modules: a feature extraction module and a linear classifier. Feature extraction relies on spectrum enhancement, which includes the discrete cosine Fourier transform and non-linear operations. Linear classification relies on multivariate statistical analysis. Interaction enables supervised training of the LM. The application described in this article aims at discriminating the TAOS patterns of single bacterial spores (Bacillus subtilis) from patterns of atmospheric aerosol and diesel soot particles. The latter are known to interfere with the detection of bacterial spores. Classification has been applied to a data set with more than 3000 TAOS patterns from various materials. Some classification experiments are described, where the size of training sets has been varied as well as many other parameters which control the classifier. By assuming all training and recognition patterns to come from the respective reference materials only, the most satisfactory classification result corresponds to ≈ 20% false negatives from Bacillus subtilis particles and ≤ 11% false positives from environmental and diesel particles.
We examine how aggregation affects the light-scattering signatures, especially the polarization in the near-backward-scattering direction. We use the discrete dipole approximation (DDA) to study the backscatter of agglomerate particles consisting of oblong monomers. We examine the effects of monomer number and packing structure on the resulting negative polarization branch at small phase angle. We find large a dependence on the orientation of the monomers within the agglomerate and a smaller dependence on the number of monomers, suggesting that the mechanism producing the negative polarization minimum depends strongly on the interactions between the individual monomers. We also examine experimental measurements of substrates composed of biological cells. We find that the light-scattering signatures in the backward direction are not only different for different spore species, but for spores that have been prepared using different methodologies. These signatures are reproducible in different substrates composed of the spores from the same batches.
We have developed an experimental light-scattering method to obtain information about particles with low polydispersities in size on flat substrates. It is based on the analysis of the visibility factor of the lobes in the light scattering patterns obtained from flat metallic substrates seeded with the particles. The visibility factor of a pattern is obtained for different minima. The solution of the scattering problem may be provided by a theoretical model, and analytical expressions for the visibility are derived. This relation between visibility and polydispersity is experimentally tested, and it is shown how the origin of the loss of visibility may be exploited to characterize the polydispersity.
Our group has been developing a system for single-particle fluorescence detection of aerosolized agents. This paper describes the most recent steps in the evolution of this system. The effects of fluorophore concentrations, droplet size, and excitation power have also been investigated with microdroplets containing tryptophan in water to determine the effects of these parameters on our previous results. The vibrating orifice droplet generator was chosen for this study base don its ability to generate particles of well- known and reproducible size. The power levels required to reach saturation and photodegradation were determined. In addition, the collection of fluorescence emission was optimized through the use of a UV achromatic photographic lens. This arrangement permitted collection of images of the droplet stream. Finally, the use of a dual-beam, conditional firing scheme facilitated the collection of improved signal- to-noise single-shot spectra from individual biological particles.
Fluorescence or Raman emission can be used in characterizing particles inside or near a surface, e.g., a biological cell or spore on a filter, or a contaminant particle on a silicon wafer. Here we model the emission from a sphere on a surface. The internal fields in a sphere on a surface are known for plane-wave excitation. These fields induce dipole moments in molecules in the sphere. These oscillating dipoles are the sources of the incident radiation at the shifted frequency. The Green function for emission is found by using the reciprocity theorem for Green functions along with the internal fields generated by a plane wave at the shifted frequency. Reciprocity provides a simple method for obtaining the far fields for systems for which the near/internal fields are known for plane-wave excitation.
We report the operation of an aerosol analyzer capable of measuring the fluorescence spectra of single micrometer-size bioaerosol particles. Aerosol particles in an air stream initially transverse a cw 488-nm 'trigger' laser beam where their elastic scattering and total fluorescence is measured with photomultipliers. When the elastic scattering and fluorescence signals meet certain criteria, a UV (266 nm) 'probe' laser is triggered and it illuminates the selected particles. The UV laser-excited spectra of particles are measured with the instrument's image-intensified CCD detector, gaged with signals from the trigger laser. We demonstrate the ability of the instrument to capture the fluorescence of single airborne biological particles. The results suggest that it may be possible to differentiate among biological particles based on their single particle fluorescence spectra.
We discuss scattering in the context of the Stokes vectors and Mueller matrices that completely characterize the polarization state of the scattered light. A polar nephelometer is used to measure the light scattering Mueller matrix elements of various ideal systems. These systems are fundamental and solvable theoretically. The scattering systems can be perturbed and the amount of perturbation can be quantified. The light-scattering signals can then be examined as a function of the amount of perturbation. Eventually, the perturbation dominates the system so that the addition of more of the perturbation does not significantly alter the appearance of the scattering system or of the polarized light scattering signals. These saturated systems may also be thought of as fundamental systems. In this paper we examine some fundamental systems and discuss models which predict the polarization state of some highly perturbed scattering systems.
A ray-tracing model was used to derive the light scattering Mueller matrix element curves for a dipole near a perfect surface as a function of incident angle, scattering angle, and surface refractive index. This system represents a fundamental system composed of a perfect plane surface and a perfect (Rayleigh) scatterer.
We discuss scattering in the context of the Stokes vectors and Mueller matrices that characterize the interaction. In order to study surface structures using light-scattering techniques it is useful to examine the nature of light scattered from perfect and perturbed mirror surfaces.
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