Transport and deposition of quantum dots and model polystryene nanoparticles in granular aquatic environments
Notice bibliographique
Résumé
Quantum dots (QDs) are luminescent semiconductor nanoparticles with relevant applications in different fields, including medical imaging, solar cells, and sensors. However, toxic effects in living organisms have been reported, and upon release, the potential ecotoxicological risks of QDs will be directly related to their transport and fate. The objective of this research was to evaluate the transport and deposition of different QDs in systems representative of natural subsurface environments and engineered granular filtration processes. Two experimental approaches were used: (i) laboratory scale columns packed with granular materials representative of the soil or filter matrix, and (ii) a quartz crystal microbalance with dissipation monitoring (QCM-D) using sensors coated with materials representative of grain-water interfaces. The transport and deposition of the QDs were determined over a broad range of solution chemistries (i.e., ionic strength, pH, cation type, natural organic molecules (NOM)). In all cases, the deposition experiments were complemented with an appropriate physicochemical characterization of the particles and collectors. In experiments conducted with packed columns, the transport potential of a CdSe QD, a CdTe QD and model nanosized polystyrene particles was systematically investigated in two water-saturated granular matrices: (i) clean quartz sand and (ii) loamy sand obtained from Québec farm. This study provided a good starting point for the comparison of the transport behavior of engineered nanoparticles in quartz sand versus soil matrices (loamy sand), where greater retention was observed. The results obtained suggest that differences in retention are likely related to the binding affinity of surface-modified nanoparticles for specific soil constituents.In experiments conducted with a QCM-D, the deposition kinetics of polymer-coated QDs were compared with those measured for two different polystyrene latex nanoparticles onto model environmentally relevant collector surfaces (SiO2, Al2O3, or Al2O3 coated with NOM). The results showed that QD retention is relatively low compared to that of polystyrene latex particles, and in the presence of NOM, significantly lower deposition rates of QDs were observed. Overall, the data suggested that these phenomena could be attributed to the surface coating (polymers) used to stabilize the QDs, likely due to "electrosteric repulsion". In the final series of experiments, the deposition kinetics of functionalized silicon-nanocrystals (Si-NCs) was compared by means of: columns packed with quartz sand, and a QCM-D with SiO2 coated crystals (as a model sand surface). The Si-NCs used here were functionalized with carboxylic acids of varying alkyl-chain length, and in general, experiments conducted with both techniques revealed that the mobility of Si-NCs increases with longer alkyl-chains. QCM-D provided further insight on the nanoparticle deposition behavior, whereby the output parameters (i.e., frequency and dissipation) indicated how rigidly the ENPs are bound to the surface. Yet, the interpretation of nanoparticle deposition behavior by QCM-D may be limited by the size of the particle assessed; as it was determined that in the presence of large aggregates, the acquired frequency shifts were not proportional to the deposited mass.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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) | 0,000 | 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 ».