Structurally Disordered Phosphorus-Doped Pt as a Highly Active Electrocatalyst for an Oxygen Reduction Reaction
Bibliographic record
Abstract
The application of Pt alloy catalysts for oxygen reduction reactions (ORRs) in proton-exchange membrane fuel cells is severely impeded by base metal leaching, since the produced metal ions can result in the degradation of a Nafion membrane by replacing H + and inducing a Fenton reaction. Doping Pt with nonmetal elements can significantly mitigate such problems due to the relative harmlessness of the corrosion products of anions. Herein, we developed a phosphorus-doping strategy, which can greatly boost the ORR performance of Pt. Phosphorus was introduced into the near-surface of commercial Pt/C (denoted as P NS -Pt/C) via a surfactant-free method. High-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) and X-ray photoelectron spectrum (XPS) tests indicate that the introduction of phosphorus induced distortion of the Pt lattice and the downshift of the d-band center. In situ electrochemical Fourier transform infrared (FTIR) spectroscopy with adsorbed CO as a molecule probe further revealed that the introduction of phosphorus can lower the adsorption ability. The ORR mass activity of P NS -Pt/C is as high as 1.00 mA μg Pt –1 @0.90 V, which is enhanced by 7 times in comparison with the initial Pt/C catalyst. Meanwhile, the durability is also enhanced. After 10 000 potential cycles, P NS -Pt/C only lost 14% of the ORR mass activity, while Pt/C lost 51%. More importantly, a H 2 –air fuel cell with a P NS -Pt/C cathode achieves a power density of 1.06 W cm –2 at a current density of 2.0 A cm –2 with a low Pt loading of 0.15 mg cm –2 . The current density at 0.60 V (practical working potential) is 1.54 A cm –2, 2 times higher than that of commercial Pt/C. Density functional theory (DFT) calculations indicate that near-surface phosphorus doping can induce the distortion of the Pt surface, on which some concave Pt sites have optimal binding energy of OH for the ORR. Furthermore, this phosphorus-doping strategy is also valid for a PtNi alloy catalyst to further boost the ORR performance.
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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) | 0.000 | 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".