Développement d'un instrument de comptage de particules dans un écoulement laminaire par encodage spatial
|Abstract:||Finding new fast and ultra-sensitive ways of detecting biomolecules is the target of numerous researchers and is largely present in the scientific literature. The emergence of nanotechnology and the continously growing comprehension of nanoscopic phenomena add new tools to the scientist’s toolbox. Light-matter interactions that give rise to surface plasmons and their effect on the spectroscopic signature of surrounding molecules are key factors for the current revolution of this domain. The use of these new technologies for real world analysis is limited in part because traditional analytical instruments are not adapted to the detection of nanoparticles. This explains the need for flexible detection platforms that can measure a range of nanometric biosensors. Measuring single particles in a flow usually give more information on the distribution of the sample and a higher analytical throughput than static measurements, which are undeniable advantages for usage in the field. The detection platform described in this thesis uses laminar flow and spatial encoding of the signal to ensure robustness, simplicity and sensitivity. The large probed volume offered by spatial encoding gives particles a long transit time which translates into high photon counts while enabling the differentiation of adjacent particles by cross-correlation. Moreover, the platform requires less stringent optical alignment and less optical components The particle counter uses a square capillary whose interior is coated using a unique selective gold coating methodology. This coating method allows the creation of a barcoded region that will become the probed volume. This inner coating is protected from mechanical damage and marries the fluidic system and the encoding device. The encoding performance as well as counting efficiencies will be discussed. Preliminary results of DNA detection using a silver nanoparticle-based biosensor will be exposed. The data treatment algorithm and the signal analysis tools developed will also be presented|
|Document Type:||Thèse de doctorat|
|Open Access Date:||30 November 2018|
|Collection:||Thèses et mémoires|
All documents in CorpusUL are protected by Copyright Act of Canada.