Single-Atoms and Sub-Nanometer Clusters of Pt on Graphene Support Prepared By Atomic Layer Deposition
Notice bibliographique
Résumé
To maximize Pt utilization in polymer electrolyte membrane fuel cells (PEMFCs), platinum nanoparticles (Pt NPs) supported on high surface area carbon blacks are usually used as catalysts for both oxygen reduction and hydrogen oxidation.1 For the wide-spread commercialization of PEMFCs, key challenges to be addressed are the high electrochemical activity and high stability for low-Pt-loading catalysts. It is expected that downsizing catalyst nanoparticles to clusters or even single atoms could significantly increase their catalytic activity and is therefore highly desirable to maximize the efficiency. However, the particle-size dependent catalytic activity of Pt, determined by the interplay of surface geometric and electronic factors, is not quite straightforward in the range of a few nanometers.2,3 The interaction of Pt with support, as well as the interaction of Pt precursor with support during the supported catalyst formation, are considered to play key roles on the formation of Pt NPs, as well as their activity and stability. Recently, due to their unique electric and micro-structural characteristics, nanostructured carbon materials with graphene structures such as carbon nanotubes (CNTs) and carbon nanofibers (CNFs) have been studied extensively as alternative supports for electrocatalysts, showing much enhanced fuel cell performance.4 Graphene, a unique structure of a two-dimensional (2D) sheet composed of sp2-bonded carbon atoms with one-atomic layer thick, has inspired a flurry of interests for both fundamental science and applied research due to its extraordinary properties. One hopes to employ such 2-D sheets as conductive supports to both anchor electrocatalysts and modulate the electrochemical reactions in a controlled fashion.5 On the other hand, the large-scale synthesis of practical and stable clusters and single atoms of catalysts remains a significant challenge, because clusters and single atoms are too mobile and easy to sinter under realistic reaction conditions.6 To this end, atomic layer deposition (ALD), a promising technique for small size catalyst fabrication,5 provides the solution. Previous studies have revealed that ALD allows control of the morphology of the deposited metal, from discrete tiny nanoparticles to a continuous thin film, through the surface chemistry.7 In the presented study, we employ the ALD technique to fabricate single atoms and sub-nanometer clusters of Pt on the surfaces of graphene nanosheet support.8 The morphology, size, density and loading of Pt on graphene can be precisely controlled by simply adjusting the number of ALD cycles. High angle annular dark field scanning TEM (HAADF-STEM) and electrochemical characterizations were carried out to determine how the catalyst structure changes with adjusting the numbers of ALD cycles. Fig. 1a and b show the bright-field TEM image and HAADF-STEM image of Pt/graphene with 100 ALD cycles, respectively. On the bright-field TEM image, only Pt nanoparticles of 1–4 nm in size are observed (Fig. 1a). Interestingly, the sensitivity to atomic number Z-contrast of HAADF-STEM revealed, in addition to these Pt nanoparticles, the presence of numerous individual Pt atoms, as well as very small Pt clusters of size ≤1 nm consisting of only a few atoms (Fig. 1b). EDS, collected from different areas with Pt-clusters ranging from 1.2 to 6.7 nm size on a graphene nanosheet as well as an area containing only a few atoms, further confirmed the presence of Pt. The presence of Pt individual atoms and extremely small clusters suggests a strong interaction between graphene and Pt atoms, which may induce some modulation in the electronic structure of the Pt clusters. X-ray absorption fine structure (XAFS) spectroscopy, including both the X-ray Absorption Near Edge Structure (XANES) and the Extended X-ray Absorption Fine Structure (EXAFS), will be used to correlate the electronic structure and local environment of Pt and their electrochemical performance, and how it affects the methanol oxidation activity and CO adsorption. This work is anticipated to form the basis for the exploration of a next generation of highly efficient single-atom catalysts for various applications.
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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 | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».