Abstract
This thesis deals with an advanced laser-based microscopy technique to detect micrometer-size objects with molecular specificity. Applications are shown from the aquatic environment and from the medical world. The final chapters describe an option to increase the penetration depth through scattering samples and simulation software to help optimize the measurement settings.
One of the most prominent materials in modern life is plastic, but this also results in the large-scale production of plastic waste. A portion of this waste reaches the environment and is fragmented into small pieces, called microplastics. Microplastics pollution affects the environment and potentially our health in ways we are only beginning to understand. To study it, we need to have a solid measurement and monitoring platform, based on reliable microplastics detection.
Detection of microplastics is difficult due to their small size and heterogeneity and they can be found in different types of matrices in the environment and even in the human body. A label-free microscopy imaging technique, called Stimulated Raman Scattering (SRS) microscopy, is able to create images of small particles, like microplastics, based on their molecular structure. SRS makes use of two synchronized pulsed lasers of different colors, of which the energy difference matches a specific vibration of the target molecule.
In this thesis, we used SRS for identifying five polymer types. First, we tested the approach on an artificial mixture of plastic particles, and we identified polyethylene terephthalate particles extracted from nail polish, demonstrating also the thousand‐fold higher speed of mapping compared with conventional Raman. Furthermore, we found 12,000 plastic particles per kilogram dry weight in a Rhine estuary sediment sample. SRS was the fastest microplastics detection method at the time of publication. We concluded that SRS can be an efficient method for monitoring microplastics in the environment and potentially many other matrices of interest.
Another application area that was studied with SRS is breast tissue from explanted breast implants. Implant failure occurs in approximately a tenth of patients within 10 years, and even without a major rupture silicone can still leak. We showed how SRS can detect silicone material in breast tissue slices, without additional sample treatment. SRS images revealed the distribution and quantity of silicone material. Twenty-two donor-matched capsules from eleven patients experiencing unilateral capsular contraction complaints were included in a clinical study after bilateral explantation surgery. This method showed the correlation between silicone presence and capsular contraction.
Depth penetration of the light into the sample is an issue with any light based technique. We showed the use of a long wavelength SRS microscope system capable of greater depth imaging compared with the more common configuration with shorter wavelengths. It showed an improved depth penetration in polyethylene plastic material, in a silicone test sample with embedded polyethylene microbeads, and into subcutaneous fat tissue.
In SRS imaging we have to consider multiple parameters that influence the imaging speed, image quality and the spatial resolution. In order to find the optimized imaging setup, we developed two simulation programs for SRS imaging systems with lock-in amplifier. One simulation program was used to find parameters optimized for either image quality or acquisition time. With the second program we evaluated SRS imaging; the simulations agreed very well with experimental SRS images. The same software was used to simulate multiplexed SRS imaging. of six channels, including the inter-channel crosstalk. These programs will be useful for operating an SRS imaging setup, as well as for designing novel setups.
Original language | English |
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Qualification | PhD |
Awarding Institution |
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Supervisors/Advisors |
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Award date | 2 Nov 2021 |
Place of Publication | Amsterdam |
Publisher | |
Print ISBNs | 9789464168396 |
Electronic ISBNs | 9789464168396 |
Publication status | Published - 2 Nov 2021 |
Keywords
- microplastics
- environment
- pollution
- implants
- imaging
- spectroscopy
- identification
- silicone
- multiplexed
- simulation