In Situ Scanning Electron Microscopy Observation of Metal Nanoparticles during Heating
Notice bibliographique
Résumé
Metal nanoparticles offer promising applications in facet-selective catalysis and surface plasmon resonance (SPR) [1-3]. Among these nanoparticles, silver nanoparticles have shown great potential due to their excellent optoelectronic properties and the ability to control their shape. However, the chemical stability of silver nanoparticles raises concerns. One approach to improve their chemical stability is to coat the nanoparticles with gold [1, 4]. However, the stability of these gold-coated nanoparticles and their microstructural behavior including facet preservation during heating still needs to be studied for high temperature applications. To monitor the effects of increasing temperature, in situ scanning electron microscopy (SEM) is an effective technique. In situ SEM allows for the observation of morphological change in the nanoparticles during heating, which provides insights into how their synthesis can be altered to enhance their properties. In this work, a Hitachi SU7000 SEM was used to investigate the microstructural evolution of nanoparticles during heating. The SEM heating holder was developed by Hitachi, and the heating chip was manufactured and optimized by Norcada Inc. (Edmonton Canada). For the initial experiments, gold-plated pentagonal silver nanorods were used. These nanoparticles were dropcast onto the heating chip, and images of various particles were captured at elevated temperatures during the heating process. Figure 1 presents the heating profile of the nanoparticles including the specific temperatures at which images were captured. Figure 2 shows SEM images of a cluster of four particles obtained with the upper detector (UD). Images were recorded at an accelerating voltage of 8 kV to minimize the effect of beam damage, prevent charging, and capture the surface structures. At room temperature (Figures 2A and 3A), the facets of the nano particles are clearly visible. As the temperature reaches 200 °C (Figure 2B), these facets begin to fade, and with further heating, the particles start to consolidate. At around 600 °C (Figures 2C and 3B), new lines appear on the particles, possibly cracks in the gold shell, which could lead to the sublimation of the silver inside. This behavior is observed around 600-700 °C, which coincides with the volatilization temperature of silver under low pressure, which is 680 °C [5]. Videos obtained during the heating process further illustrate the evolution of these nanoparticles. Figure 3 shows the behavior of two nanoparticles adjacent to each other during heating. At room temperature (Figure 3A), the facets are clearly visible. As the temperature increases, the facets gradually disappear and by 600 °C (Figure 3B), the nanoparticles begin to consolidate and merge together. At higher temperatures (Figure 3C), when only a shell of the nanoparticles remains, the merging of the particles becomes more apparent. The in situ SEM heating set-up used in this study proves to be an excellent method for investigating these nanoparticles. Further research will focus on gold-plated silver nanoparticles with silicate shells and nanoparticles of different geometries to determine the optimal strategies for further stabilizing silver nanoparticles at high temperature. Additionally, the study will monitor the morphological changes at different heating rates and profiles [6]. Heating profile of the nanoparticles from room temperature (RT) until 1000 °C. The red dots show the temperatures at which the SEM images in Figure 2 were captured at. SEM images of a cluster of nanoparticles at temperatures marked with red dots in Figure 1. Scale bar 100 nm. SEM images of two nanoparticles (A) coalesced and merged (B), and sublimed (C) during heating. Scale bar 100 nm.
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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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».