Classifying Sphere, Sphere-Like, and Non-Spherical Particles Using Two-Dimensional Angular Optical Scattering (TAOS) Patterns
Abstract
In our work, we report on an image autocorrelation method devised to discern particle morphology from two-dimensional angular optical scattering (TAOS) patterns. TAOS patterns change as particle morphology evolves from spherical to highly non-spherical. By extracting features from the autocorrelation functions of the forward and backward scattering hemispheres, we are able to capture this evolution of particle morphology. In particular, using the autocorrelation functions, we roughly categorize over 30,000 TAOS patterns of airborne aerosol particles collected into three groups: sphere, sphere-like, and non-spherical particles. Supporting previous work, backscattering is more sensitive to small changes in particle morphology away from the homogeneous sphere. In addition, we explore the evolution of the scattering phase function using these defined morphology groups.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFM.A23A0173L
- Keywords:
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- 0305 Aerosols and particles;
- ATMOSPHERIC COMPOSITION AND STRUCTUREDE: 0319 Cloud optics;
- ATMOSPHERIC COMPOSITION AND STRUCTUREDE: 0321 Cloud/radiation interaction;
- ATMOSPHERIC COMPOSITION AND STRUCTUREDE: 0360 Radiation: transmission and scattering;
- ATMOSPHERIC COMPOSITION AND STRUCTURE