Benchmarking Three Ruthenium Phosphide Phases for Electrocatalysis of the Hydrogen Evolution Reaction: Experimental and Theoretical Insights
Bibliographic record
Abstract
Abstract The outstanding electrocatalytic activity of ruthenium (Ru) phosphides toward the hydrogen evolution reaction (HER) has received wide attention. However, the effect of the Ru phosphide phase on the HER performance remains unclear. Herein, a two‐step method was developed to synthesize nanoparticles of three types of Ru phosphides, namely, Ru2P, RuP, and RuP2, with similar morphology, dimensions, loading density, and electrochemical surface area on graphene nanosheets by simply controlling the dosage of phytic acid as P source. Electrochemical tests revealed that Ru2P/graphene shows the highest intrinsic HER activity, followed by RuP/graphene and RuP2/graphene. Ru2P/graphene affords a current density of 10 mA cm−2 at an overpotential of 18 mV in acid media. Theoretical calculations further showed that P‐deficient Ru2P has a lower free energy of hydrogen adsorption on the surface than other two, P‐rich Ru phosphides (RuP, RuP2), which confirms the excellent intrinsic HER activity of Ru2P and is consistent with experiment results. The work reveals for the first time a clear trend of HER activity among three Ru phosphide phases.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".