Three-dimensional self-assembled hybrid silicon nanostructures for high sensitivity SERS chemical and biosensing applications
Notice bibliographique
Résumé
Raman spectroscopy is a powerful tool for detection of chemical and bioanalytes but lacks enhancement required to detect these analytes at the ultrahigh sensitivity needed for many applications. Surface enhanced Raman Scattering is a technique by which an analyte signal can become greatly enhanced and, near single molecule sensitivity, is achievable. Currently, SERS-based detection platforms currently rely on noble metal nanostructures as primary enhancing sources for the detection of chemical and bioanalytes but have significant limitations in terms of reproducibility and biocompatibility. Recent research has shown that semiconductors have the ability to exhibit SERS enhancing characteristics that can potentially supplant the use of noble metals without the limitations associated with noble metal nanomaterials. This thesis presents, the generation of three-dimensional self-assembled hybrid silicon nanostructures though a laser-ion plume formation mechanism. These Si nanostructures exhibit high sensitivity SERS enhancement characteristics which can be applied for chemical and biosensing applications. In this thesis, the Raman enhancing characteristics of the hybrid Si nanostructures are examined and correlated to the unique physical morphology and material chemistry of these nanostructures. These Si nanostructures are shown to be comprised of individual Si nanospheroids that have fused to form a highly 3D nanoweb-like self-assembled nanostructures. It is also shown that these nanospheroids are composed of both amorphous and polycrystalline sub-regions, which can only be generated within an ion-plume formed by a femtosecond pulsed laser. By programming the laser, the nanostructure morphology and hybrid nature can be manipulated and optimized. These Si nanostructures are shown to be highly sensitive as SERS platforms for chemical analytes. In addition, it is shown that with the application of noble metal nanoparticles on the surface of the 3D hybrid silicon nanowebs structures, an additional enhancement boost can be optimized for the detection of chemical molecules. With this, the dual contribution to the SERS sensitivity from both the primary Si nanostructures and the secondary noble metal nanostructures can be used to detect the presence of a biomolecule analyte is shown. To delve deeper into how these hybrid Si nanostructures cause SERS enhancement of bioanalytes, the Si ion interactions within the laser-ion plume were manipulated to induce quantum-scale defects within the hybrid Si nanospheroids. By creating both an inert and oxygenated laser-ion plumes the formation of sub-nanograins within the nanospheroids and sub-nanovoids on the nanospheroid surface is shown to significantly enhance the detection of bioanalyte signal for multiple biomolecules which act as signals for various diseases. Based on the results in this thesis, it has been proven that Si-based nanostructures have the capacity to be used as sole SERS enhancing sources for chemical and biomolecule analytes.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».