Intermetallic Platinum Alloy Nanoparticles and Single Atoms Hybrid Electrocatalysts for Proton Exchange Membrane Fuel Cells
Bibliographic record
Abstract
Abstract Proton exchange membrane fuel cell converts hydrogen and oxygen into electricity with zero emission1. The high cost and low durability of Pt-based electrocatalysts for oxygen reduction reaction hinder its wide applications2,3. The development of non-precious metal electrocatalysts also reaches the bottleneck because of the low activity and durability4,5. Here we rationally design a hybrid electrocatalyst consisting of atomically dispersed Pt and Fe single atoms and intermetallic PtFe alloy nanoparticles. The Pt mass activity of the hybrid catalyst is 3.5 times higher than that of commercial Pt/C in a fuel cell. More importantly, the fuel cell with an ultra-low Pt loading in the cathode (0.015 mgPt cm-2) shows unprecedented durability, with 93.6% activity retention after 100,000 cycles and no noticeable current drop at 0.6 V for at least 206 h. These results highlight the importance of the synergistic effects among active sites in hybrid electrocatalysts and provide an alternative way to design more active and durable low-Pt electrocatalysts for electrochemical devices.
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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".