Platinum Nanocatalysts Supported on Defective Hollow Carbon Spheres: Oxygen Reduction Reaction Durability Studies
Bibliographic record
Abstract
The durability and long-term applicability of catalysts are critical parameters for the commercialization and adoption of fuel cells. Even though a few studies have been conducted on hollow carbon spheres (HCSs) as supports for Pt in oxygen reduction reactions (ORR) catalysis, in-depth durability studies have not been conducted thus far. In this study, Pt/HCSs and Pt/nitrogen-doped HCSs (Pt/NHCSs) were prepared using a reflux deposition technique. Small Pt particles were formed with deposition on the outside of the shell and inside the pores of the shell. The new catalysts demonstrated high activity (>380 μA cm −2 and 240 mA g −1 ) surpassing the commercial Pt/C by more than 10%. The catalysts demonstrated excellent durability compared to a commercial Pt/C in load cycling, experiencing less than 50% changes in the mass-specific activity (MA) and surface area-specific activity (SA). In stop-start durability cycling, the new materials demonstrated high stability with more than 50% retention of electrochemical active surface areas (ECSAs). The results can be rationalised by the high BET surface areas coupled with an array of meso and micropores that led to Pt confinement. Further, pair distribution function (PDF) analysis of the catalysts confirmed that the nitrogen and oxygen functional groups, as well as the shell curvature/roughness provided defects and nucleation sites for the deposition of the small Pt nanoparticles. The balance between graphitic and diamond-like carbon was critical for the electronic conductivity and to provide strong Pt-support anchoring.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".