Analyse des nanoparticules de dioxyde de cérium à l’aide de l’ICP-MS en mode particule unique
Notice bibliographique
Résumé
Due to their unique properties, engineered nanomaterials are now widely used in numerous commercial products. Cerium oxide (CeO2) nanoparticles (NPs) are among the most commonly used engineered NPs, with applications in surface coatings, catalysis, the manufacturing of semiconductors, biomedicine and agriculture. With the significant increase in the production and use of CeO2 NPs, concern is increasing over their release into the environment and their subsequent fate and toxicity. In order to evaluate their environmental risk, it is necessary to detect, quantify and characterize the NPs in all environmental compartments. Unfortunately, analyses of NPs in natural systems are challenging due to their small sizes, their low concentrations (∼ ng L-1) and the complexity of environmental matrices, which also contain natural colloids. Single particle inductively coupled plasma mass spectrometry (SP-ICP-MS) is a specific and sensitive technique that enables the detection of very low concentrations (∼ ng L-1) of NPs and it can provide information on their number concentrations, sizes, and size distributions. This technique is often limited by high size detection limits (SDL). However, it is especially important to obtain rigorous size, concentration, and fate data for the smallest NPs, since they are expected to have the greatest environmental risk. To that end, the specific objective of this thesis was to develop an improved method for the detection, quantification, and characterization of CeO2 NPs in complex natural waters using SP-ICP-MS. The project was then divided into several objectives: (1) decrease the SDL for CeO2 NPs; (2) optimize the preparation method for natural water samples; (3) apply the preparation and the analysis methods to detect, quantify, and characterize CeO2 NPs in several natural water samples and commercial products, such as a paint and a stain; (4) identify the origin (natural or engineered) of the detected CeO2 NPs; (5) quantify and characterize the release of CeO2 NPs from paint and stain under natural weathering scenarios; and (6) evaluate the effect of different physicochemical conditions (pH, ionic strength, and NOM) on the fate of CeO2 NPs after their release. A high sensitivity sector field ICP-MS (SF-ICP-MS) with microsecond dwell times (50 μs) was used to lower the SDL of CeO2 NPs to below 4.0 nm. While filtration is often used as a preparation method for SP-ICP-MS, its effect on the concentrations and sizes of NPs is unknown. For this purpose, the interactions between six different membrane filters and CeO2 NPs in aqueous samples were examined. The highest recoveries were observed for polypropylene membranes, where 60 % of the pre-filtration NPs were found in a rainwater and 75% were found in a river water. Recoveries could be increased to over 80% by pre-conditioning the filtration membranes with a multi-element solution. Similar recoveries were obtained when samples were centrifuged at low centrifugal forces (≤1000xg). SF-ICP-MS was then used to detect CeO2 NPs in Montreal rainwater, St. Lawrence River water, a paint, and a stain. A significant decrease in the concentrations of CeO2 NPs, initially contained in paint and stain, was measured over time under different conditions, which was attributed to agglomeration and/or dissolution. Finally, when painted and stained panels were placed outside, the released Ce in the precipitation was mainly in the dissolved form with no significant release of CeO2 NPs.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,002 |
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 ».