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

Temperature Measurement of Trapped, Thermally Sensitive Single Particles in an Optical Trap Using Raman Spectroscopy

Single particles trapped in an optical trap may experience temperature elevation, yet direct measurement of temperature and its distribution inside the optical trap of several to hundreds of microns in size remains a big challenge. We introduce a method that can measure the temperature inside a universal optical trap (UOT) using Raman spectroscopy of single trapped particles of high thermal conductivity. We measured temperature and temperature distributions inside the UOT using Raman shifts of single-walled carbon nanotubes (SWCNTs) and micron-sized diamonds (MSDs), which are heated by trapping laser beams directly or indirectly, depending on the location of the particle in the trap. We show that the temperature at the center of the UOT is much lower than the temperature along the hollow beams that form a hollow, cage-shaped UOT. In the range of the trapping laser power of 200-2950 mW, the surface temperature of particles trapped at the center of a UOT changes from 322 K to 830 K, correspondingly. This result gives a heating rate as a high thermal-absorbing particle trapped in the center of the UOT with 18.3 ± 0.4 °C/100 mW. In addition, the temperature gradient outside the UOT was also characterized by trapping SWCNT particles outside the UOT. Results show that when a light-absorbing particle is trapped for the study of material property, phase transitions, surface equilibrium process, chemical reactions, etc., this method can be used to measure temperature distribution and its variations in the trap and its surroundings.

Shape Discrimination of Individual Aerosol Particles Using Light Scattering

We established an experimental apparatus by combining polarized light scattering and angle-resolved light scattering measurement technology to rapidly identify the shape of an individual aerosol particle. The experimental data of scattered light of Oleic acid, rod-shaped Silicon dioxide, and other particles with typical shape characteristics were analyzed statistically. To better study the relationship between the shape of particles and the properties of scattered light, the partial least squares discriminant analysis (PLS-DA) method was used to analyze the scattered light of aerosol samples based on the size screening of particles, and the shape recognition and classification method of the individual aerosol particle was established based on the analysis of the spectral data after nonlinear processing and grouping by particle size with the area under the receiver operating characteristic curve (AUC) as reference. The experimental results show that the proposed classification method has a good discrimination ability for spherical, rod-shaped, and other non-spherical particles, which can provide more information for atmospheric aerosol measurement, and has application value for traceability and exposure hazard assessment of aerosol particles.

The color of aerosol particles

Digital in-line holography (DIH) is an established method to image small particles in a manner where image reconstruction is performed computationally post-measurement. This ability renders it ideal for aerosol characterization, where particle collection or confinement is often difficult, if not impossible. Conventional DIH provides a gray-scale image akin to a particle's silhouette, and while it gives the particle size and shape, there is little information about the particle material. Based on the recognition that the spectral reflectance of a surface is partly determined by the material, we demonstrate a method to image free-flowing particles with DIH in color with the eventual aim to differentiate materials based on the observed color. Holograms formed by the weak backscattered light from individual particles illuminated by red, green, and blue lasers are recorded by a color sensor. Images are reconstructed from the holograms and then layered to form a color image, the color content of which is quantified by chromaticity analysis to establish a representative signature. A variety of mineral dust aerosols are studied where the different signatures suggest the possibility to differentiate particle material. The ability of the method to resolve the inhomogeneous composition within a single particle in some cases is shown as well.

Development and application of a method to classify airborne pollen taxa concentration using light scattering data

Although automated pollen monitoring networks using laser optics are well-established in Japan, it is thought that these methods cannot distinguish between pollen counts when evaluating various pollen taxa. However, a method for distinguishing the pollen counts of two pollen taxa was recently developed. In this study, we applied such a method to field evaluate the data of the two main allergens in Japan, Chamaecyparis obtusa and Cryptomeria japonica. We showed that the method can distinguish between the pollen counts of these two species even when they are simultaneously present in the atmosphere. This result indicates that a method for automated and simple two pollen taxa monitoring with high spatial density can be developed using the existing pollen network.

Optical-Trapping Laser Techniques for Characterizing Airborne Aerosol Particles and Its Application in Chemical Aerosol Study

We present a broad assessment on the studies of optically-trapped single airborne aerosol particles, particularly chemical aerosol particles, using laser technologies. To date, extensive works have been conducted on ensembles of aerosols as well as on their analogous bulk samples, and a decent general description of airborne particles has been drawn and accepted. However, substantial discrepancies between observed and expected aerosols behavior have been reported. To fill this gap, single-particle investigation has proved to be a unique intersection leading to a clear representation of microproperties and size-dependent comportment affecting the overall aerosol behavior, under various environmental conditions. In order to achieve this objective, optical-trapping technologies allow holding and manipulating a single aerosol particle, while offering significant advantages such as contactless handling, free from sample collection and preparation, prevention of contamination, versatility to any type of aerosol, and flexibility to accommodation of various analytical systems. We review spectroscopic methods that are based on the light-particle interaction, including elastic light scattering, light absorption (cavity ring-down and photoacoustic spectroscopies), inelastic light scattering and emission (Raman, laser-induced breakdown, and laser-induced fluorescence spectroscopies), and digital holography. Laser technologies offer several benefits such as high speed, high selectivity, high accuracy, and the ability to perform in real-time, in situ. This review, in particular, discusses each method, highlights the advantages and limitations, early breakthroughs, and recent progresses that have contributed to a better understanding of single particles and particle ensembles in general.

Study on polarization scattering applied in aerosol recognition in the air

In this work, we present an in situ online aerosol recognition scheme by synchronized parallel polarization scattering analysis. By theoretical simulations, we select the feasible scattering angles and evaluate the potential of Stokes parameters to identify aerosols. Correspondingly, we develop a measurement system based on multi-angle optical scattering and multidimensional polarization analyzing technique. We construct two index groups based on non-normalized and normalized polarization parameters respectively, and employ their frequency distribution histograms instead of the simple average values to identify and classify different types of aerosols. The experimental verification confirms a future way of a multi-dimensional polarization parameter group applied in a fast and effective air pollutants monitoring.