Tracking Morphology Changes During Metal Oxidation Over a Broad Pressure Range Using ETEM With Simultaneous Secondary Electron and STEM Imaging
Notice bibliographique
Résumé
Directly monitoring metal oxidation at the atomic scale in oxidative gas environments is crucial for applications in the semiconductor industry, catalysis and corrosion science. Over the past decades, environmental transmission electron microscopy (ETEM) has shown its great capabilities in uncovering the atomistic mechanisms governing metal and alloy oxidation [1-3]. When equipped with a secondary electron (SE) detector, ETEM also enables the simultaneous acquisition of surface topological information during gas reactions alongside the more standard STEM signals [4-5]. Despite extensive conventional ETEM studies of metal and alloy oxidation, the use of SE-STEM in oxidation experiments remains limited [5]. Furthermore, a key challenge in SE-STEM imaging in a gaseous environment is the limitation imposed by the maximum gas pressure allowed in the ETEM, typically up to tens of mbar. Extending SE-STEM imaging to higher pressure regimes within ETEM remains unexplored. In this study, we investigate metal oxidation at different pressures in an ETEM with an SE detector. Specifically, we evaluate the feasibility for extending SE-STEM imaging to higher pressures by employing a semi-open cell design. This customized semi-open cell configuration operates similarly to environmental SEM [6] and is achieved by introducing an opening at the top chip window of a closed gas cell (Figure 1). This design enables SE-STEM imaging at pressures significantly higher than the maximum gas pressure permitted in the ETEM column. We further discuss the importance of the opening size and its effect on the pressure gradient within the cell. Zinc (Zn) oxidation is selected as a model system for SE-STEM imaging under varying pressures due to its pressure-dependent oxidation kinetics and associated morphological changes, and its strong relevance to industrial catalysis and fuel cells. SE-STEM imaging of Zn oxidation was carried out in a probe corrected Hitachi HF5000-IS ETEM operating at 200 kV. Open-cell experiments were conducted using a single tilt heating holder, and closed cell and semi-closed cell experiments were performed in a MEMS heating and gas holder (both manufactured by Hitachi High-Tech Inc., Canada). We demonstrate the oxidation behavior of Zn across a range of pressures, from vacuum to ambient pressure, at elevated temperatures in different gas environments. The experiments yield movies of Zn sublimation (Figure 2A-B), surface reconstruction, and early-stage oxidation (Figure 2C-F) that allow us to discuss the mechanisms at work. Importantly, simultaneous SE-STEM imaging in both open-cell and semi-open cell configurations enables direct observation of surface morphology evolution during Zn sublimation and oxidation, offering new insights into the anisotropy of evaporation and oxidation in Zn metals. The semi-open cell design in this work offers a promising approach for investigating metal surface evolution during metal-gas reactions using SE signals, but we also anticipate broader application of SE-STEM in ETEM research for studying dynamic material processes [7]. Simultaneous secondary electron (SE) imaging of materials in a transmission electron microscope (TEM) under varying pressures. (A) Schematics of three different setups for imaging samples in a gaseous environment: open-cell environmental TEM (left), closed gas cell system (middle) and semi-open gas cell system (right). (B) Annular dark field (ADF)-STEM image and the corresponding SE-STEM image of Zn/ZnO core-shell nanoplates. The combination of ADF-STEM and SE-STEM imaging clearly reveals the selective removal of Zn at the two corners of a triangular nanoplate, while the ZnO surface shell remains intact. Early-stage Zn oxidation observed using ETEM with a SE detector. (A) Schematic showing the sublimation of a Zn/ZnO core-shell nanoplate during ETEM imaging. (B) Atomic-resolution SE-STEM imaging of the Zn sublimation process in vacuum at 200 °C. Zn vapor forms a new layer of ZnO due to residual O2 present in the TEM vacuum. (C) Schematic representation of Zn oxidation in O2. (D) Atomic-resolution BF-STEM imaging of the early-stage Zn oxidation in O2 (2.6×10-1 Pa) at 200 °C, revealing the formation of a new ZnO layer. (E) SE-STEM images exhibiting the growth of ZnO after 60 min of exposure to O2 at 200 °C. (F) BF-STEM image showing new ZnO layers formed on {001} facets, observed from the [010] viewing direction.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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 tête enseignante, 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 ».