Personne : Boudreau, Denis
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Boudreau
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Denis
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Université Laval. Département de chimie
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Publication Accès libre Acting as a molecular tailor : dye structural modifications for improved sensitivity towards lysophosphatidic acids sensing(American Chemiscal Society, 2022-12-28) Fontaine, Nicolas; Harter, Lara; Marette, André; Boudreau, DenisLysophosphatidic acids (LPA) are key biomarkers for several physiological processes, the monitoring of which can provide insights into the host’s health. Common lab-based techniques for their detection are cumbersome, expensive and necessitate specialized personnel to operate. LPA-sensitive fluorescent probes have been described, albeit for non-aqueous conditions, which impedes their use in biological matrices. In this paper, we explore in detail the influence of structure on the extent of aggregation-induced fluorescence quenching using specially synthesized styrylpyridinium dyes bearing structural adaptations to bestow them enhanced affinity towards LPA in aqueous media. Spectroscopic investigations supported by time-resolved fluorimetry revealed the contribution of excimer formation to the fluorescence quenching mechanism displayed by the fluorescent probes. Experimental observations of the influence of structure on detection sensitivity were supported by DFT calculations.Publication Accès libre Pushing the limits of surface-enhanced raman spectroscopy (SERS) with deep learning : identification of multiple species with closely related molecular structures(Society for Applied Spectroscopy, 2022-01-26) Boudreau, Denis; Fillion, Daniel; Fontaine, Nicolas; Fortin, Hubert; Lebrun, Alexis; Barbier, OlivierRaman spectroscopy is a non-destructive and label-free molecular identification technique capable of producing highly specific spectra with various bands correlated to molecular structure. Moreover, the enhanced detection sensitivity offered by Surface-Enhanced Raman spectroscopy (SERS) allows analyzing mixtures of related chemical species in a relatively short measurement time. Combining SERS with deep learning algorithms allows in some cases to increase detection and classification capabilities even further. The present study evaluates the potential of applying deep learning algorithms to SERS spectroscopy to differentiate and classify different species of bile acids, a large family of molecules with low Raman cross sections and molecular structures that often differ by a single hydroxyl group. Moreover, the study of these molecules is of interest for the medical community since they have distinct pathological roles and are currently viewed as potential markers of gut microbiome imbalances. A Convolutional Neural Network (CNN) model was developed and used to classify SERS spectra from five bile acid species. The model succeeded in identifying the five analytes despite very similar molecular structures and was found to be reliable even at low analyte concentrations.Publication Accès libre A ratiometric nanoarchitecture for the simultaneous detection of pH and halide ions using UV plasmon-enhanced fluorescence(Royal Society of Chemistry, 2016-12-15) Asselin, Jérémie; Boudreau, Denis; Fontaine, Nicolas; Lambert, Marie-PierIn this work, we designed a ratiometric core–shell nanoarchitecture composed of an indium UV plasmonic core, an internal reference (rhodamine B), a pH-sensitive probe (fluorescein), and a halide ion sensor (6-methoxyquinolinium). Immobilizing the fluorophores in distinct silica layers at precise distances from the core modulates the plasmon coupling and tunes the linear concentration range of halide ion detection.Publication Accès libre Thinking outside the shell : novel sensors designed from plasmon-enhanced fluorescent concentric nanoparticles(Cambridge Royal Society of Chemistry, 2020-08-20) Asselin, Jérémie; Picard-Lafond, Audrey; Boudreau, Denis; Fontaine, NicolasThe alteration of photophysical properties of fluorophores in the vicinity of a metallic nanostructure, a phenomenon termed plasmon- or metal-enhanced fluorescence (MEF), has been investigated extensively and used in a variety of proof-of-concept demonstrations over the years. A particularly active area of development in this regard has been the design of nanostructures where fluorophore and metallic core are held in a stable geometry that imparts improved luminosity and photostability to a plethora of organic fluorophores. This minireview presents an overview of MEF-based concentric core–shell sensors developed in the past few years. These architectures expand the range of applications of nanoparticles (NPs) beyond the uses possible with fluorescent molecules. Design aspects that are being described include the influence of the nanocomposite structure on MEF, notably the dependence of fluorescence intensity and lifetime on the distance to the plasmonic core. The chemical composition of nanocomposites as a design feature is also discussed, taking as an example the use of non-noble plasmonic metals such as indium as core materials to enhance multiple fluorophores throughout the UV-Vis range and tune the sensitivity of halide-sensing fluorophores operating on the principle of collisional quenching. Finally, the paper describes how various solid substrates can be functionalized with MEF-based nanosensors to bestow them with intense and photostable pH-sensitive properties for use in fields such as medical therapy and diagnostics, dentistry, biochemistry and microfluidics.