Stephen Holler, Ph.D., professor and chair in the Department of Physics and Engineering Physics, will present “Characterization and Classification of Aerosol Particles.”
Light scattering is a useful tool for characterizing airborne particulate matter. For spherical particles, the characterization and classification are trivial, but this is not so for nonspherical particles. The vast majority of airborne particulate matter is irregularly shaped and/or comprised of small constituent particles. The irregularity of the shape of this particulate matter poses challenges for the inverse problem. Digital holography has emerged as a useful tool for capturing light-scattering data and shape and orientation that make the inverse problem tractable. Two-dimensional light-scattering patterns may also be used in conjunction with multivariate statistical techniques and machine learning algorithms to perform classification of unknown particulates against known morphologies.
This talk will discuss the characterization and classification of airborne particulate matter using both of these techniques.
This event is open to faculty/staff and students.