Pt–Au–Co Alloy Electrocatalysts Demonstrating Enhanced Activity and Durability toward the Oxygen Reduction Reaction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Here we investigate the oxygen reduction reaction electrocatalytic activity and the corrosion stability of several ternary Pt–Au–Co and Pt–Ir–Co alloys, with Pt–Au–Co having never been previously studied for ORR. The addition of Au fine tunes the lattice parameter and the surface electronic structure to enable activity and cycling stability that is unachievable in Pt–25 atom % Co (state-of-the-art binary baseline). The ternary alloys exhibit a volcano-type dependence of catalytic efficacy on the content of Au or Ir. Pt–2.5 atom % Au–25 atom % Co alloy shows a specific activity of 1.41 mA cm –2 at 0.95 V, which is 16% and 404% higher than those of identically synthesized Pt–Co and pure Pt, respectively. This enhancement is promising in comparison to a range of previously published Pt “skeleton” and Pt “skin” alloys and is in fact the most optimum reported for a skeleton-type system. The catalysts exhibit dramatically improved corrosion stability with increasing levels of Au or Ir substitution, with the specific activity of all the ternary alloys being superior to that of Pt–Co after 100,000 potential cycles of 0.6–1.0 V. For instance, postcycled Pt–10 atom % Au–25 atom % Co shows a specific activity of 0.63 mA cm –2, which is 140% higher than that of Pt–Co and 439% higher than that of Pt. HRTEM and XPS shows that Au alloying promotes the formation of an atomically thin Pt–Au-rich surface layer, which imparts kinetic stabilization against the dissolution of the less noble solute component.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it