Author
Samuel Erdogan
Mentor
Wayne H. Knox
Abstract
Microplastics are a widely studied contaminant, the negative effects of which are yet fully understood, that permeate human and non—human ecosystems alike. Given their suspected adverse effects and their prevalence as a pollutant, a quick and effective detection method for quantifying the density of pollutant and pollutant type in a sample is desirable. This work investigates material birefringence as a means to determine microplastic identity in samples. By imaging filtered samples of microplastics under the microscope and spectrally filtering the images, we can obtain a spectral profile of the birefringence of each particle in a sample and use this to reconstruct material data. A detection method as well as results, drawbacks, and improvements are discussed.
Background – Birefringence
Birefringence is an optical property of materials where the refractive index of a medium changes relative to the orientation of light interacting with said medium. By polarizing a beam of light such that its electric field oscillates purely in one linear direction, the resulting beam has a phase difference in the vertical and horizontal components of the electric field. Due to the phase difference, this beam detected by another linear polarizer has the potential to transmit into the new polarization, whereas light transmitting through crossed polarizers typically results in no transmission.
Motivation for an Optical Identifier of MPs
Microplastics (MPs) are a widely studied pollutant with potential adverse health effects and extreme environmental permeability, being found even on mountaintops as tall as Mt. Fuji. The Knox group has previously studied methods of determining material information from samples of filtered microplastics (water and air environments).
Given their prevalence and environmental impact, an optical marker for material information is desirable for MPs. It was noted visually that different MPs displayed markedly different birefringent behavior, and that it may be a window to accessing material information quantitatively.
To that end, the Michel Levy Chart (1889) was targeted as a starting point for translating color information from sample analysis to birefringence information. The chart shows a direct relationship between observed color, material thickness, and birefringence (Δn). Thus, we were motivated to pursue spectral information in the hopes of reconstructing birefringence and therefore material information.
Jones Model for MP Birefringence
The experiment performed will obtain birefringence information by placing samples between crossed polarizers. The behavior of the electric field through the system can be modeled using Jones algebra to form an expected result.
Δn = Birefringence, t = thickness, θ = Polarizer Angle (Rel. to Optic Axis)
The above model produces Intensity vs. λ info which takes the form of a sinusoid dependent on input polarization angle, birefringence, and material thickness. The more birefringent/thick a sample is, the more orders the transmission goes through resulting in the repeating colors and washing out of colors at higher orders.
This model assumes that MPs have a well-defined optic axis, as well as that their dispersion is low enough such that Δn(λ)’ = 0. If these are good assumptions, a measurement of I(λ) through a sample encodes birefringence information in the form of these sinusoids.
Current Experimental Efforts
An illumination system designed to scan through the visible range was built using a linear actuating bandpass filter and thermal source. The illumination is passed through MPs filtered onto isotropic SiN grates between crossed polarizers. Microscope images of samples are taken across the entire visible range on a monochromatic CMOS camera.
A single fiber is selected, and the average detector counts over its area is used to generate an I(λ) response. The response is fit to the model to obtain Δn information.
Results
A wide variety of fibers were tested with fitment to the Jones model:
Conclusions
We have successfully shown quantitative differences in the birefringent behavior of MPs. With a large enough data set to account for variability, it may prove possible to ID materials by their birefringence alone and create an automated MP detection device. Future work can include assumption viability analysis and integration of image segmentation for automated results.
Acknowledgements / References
Funding / Collaborators:
Knox Group, SiMPore, Parverio
Dr. Samantha Romanick
References:
– Prv. Comm. Wayne H. Knox
– Penman, Maggie. “The Latest Unlikely Place Where You Can Now Find Microplastics.” The Washington Post, 2 Nov. 2023
– Hoffman, Robert, and Michael W Davidson. “Michel-Levy Birefringence Chart.” Olympus – Life Science Solutions, Evident, Accessed 10 Dec. 2023.