Single-Atoms and Sub-Nanometer Clusters of Pt on Graphene Support Prepared By Atomic Layer Deposition
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".