Particle monitoring and classification based on optical scattering and imaging analysis
La présentation sera en anglais / The presentation will be given in English.
Abstract: Real-time detection, classification, and identification of aerosol particles are crucial in various industries and public health areas. To overcome the limitations of existing particle analysis methods, we investigated three categories of industrial-oriented techniques for both statistical monitoring and fingerprint detection. The first technique is based on optical scattering, which correlates particle information with scattered intensity. By employing polarization characterization and multi-angle measurement, we have sufficiently classified different particle types at the single-species level. Additionally, to achieve high-throughput particle characterization, we developed imaging platforms for particle detection. Utilizing polarization imaging and deep learning algorithms, we achieved a classification accuracy of ~95%. Finally, we demonstrated a compact digital in-line holographic microscopy platform with an inertial spectrometer for simultaneous measurement of two independent fingerprint parameters at the single-species level. Specifically, by interrogating the particle location and size captured with the platform, particle mass density can be estimated. Furthermore, by employing Monte Carlo fitting to the Lorenz-Mie theory, the refractive index of each particle can be extracted from the interference patterns. The combination of mass density and optical density characterization unambiguously enhances the discriminatory power of the system, especially when dealing with particles that exhibit similar mass densities but distinctive refractive indices or vice versa.
Date and Time
Location
Hosts
Registration
- Date: 06 Aug 2024
- Time: 12:30 PM to 01:30 PM
- All times are (GMT-05:00) Canada/Eastern
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- 1100 Notre-Dame St W
- Montréal, Quebec
- Canada H3C 1K3
- Building: Building A
- Room Number: Room 1302
- Contact Event Host
- Co-sponsored by Co-sponsored by National Research Council, Canada. Optonique. ETS Optica Student Chapter.
Speakers
Jingwen Li of PhotonDelta
Particle monitoring and classification based on optical scattering and imaging analysis
Abstract: Real-time detection, classification, and identification of aerosol particles are crucial in various industries and public health areas. To overcome the limitations of existing particle analysis methods, we investigated three categories of industrial-oriented techniques for both statistical monitoring and fingerprint detection. The first technique is based on optical scattering, which correlates particle information with scattered intensity. By employing polarization characterization and multi-angle measurement, we have sufficiently classified different particle types at the single-species level. Additionally, to achieve high-throughput particle characterization, we developed imaging platforms for particle detection. Utilizing polarization imaging and deep learning algorithms, we achieved a classification accuracy of ~95%. Finally, we demonstrated a compact digital in-line holographic microscopy platform with an inertial spectrometer for simultaneous measurement of two independent fingerprint parameters at the single-species level. Specifically, by interrogating the particle location and size captured with the platform, particle mass density can be estimated. Furthermore, by employing Monte Carlo fitting to the Lorenz-Mie theory, the refractive index of each particle can be extracted from the interference patterns. The combination of mass density and optical density characterization unambiguously enhances the discriminatory power of the system, especially when dealing with particles that exhibit similar mass densities but distinctive refractive indices or vice versa.
Biography:
Dr. Jingwen Li is a senior researcher and Engineer in the field of Engineering Physics. He obtained his Ph.D. from Polytechnique Montreal in 2017. Following his doctorate, he pursued postdoctoral research at the Department of Electrical and Computer Engineering at The University of British Columbia from 2017 to 2018, where he was awarded the Micas Elevate Postdoctoral Fellowship.
Dr. Li then contributed his expertise as a research scientist at Nanozen Industries in Vancouver for three years. He is currently serving as an Associate Professor at Jiangnan University. His research interests lie in optical sensors, holography, and machine vision. He holds three US patents and has authored over 20 publications.
Agenda
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- Introduction from the host (2 to 5 minutes)
- Presentation (40 to 45 minutes)
- Questions from the audience (5 to 10 minutes)
- Lunch and networking
Food and beverages will be provided will be provided. / Des collations et des rafraîchissements seront offerts.