Electrodeposition of <scp>Ni‐P</scp> alloy from deep eutectic solvent and its electrocatalytic activity toward hydrogen evolution reaction
Bibliographic record
Abstract
Abstract Ni‐P alloys have been successfully electrodeposited in the choline chloride and ethylene glycol with a molar proportion of 1:2(CE) electrolyte and their activities toward hydrogen evolution reaction (HER) have been also evaluated. The electrodeposition of Ni‐P alloy follows a co‐deposition process, and the bulk growth of which depends on an instantaneous nucleation under diffusion control. The morphologies of Ni‐P alloys are significantly influenced by the P content, and low P content can lead to a smooth surface. As expected, Ni‐9.0 wt.% P alloy shows an impressive HER catalytic performance with a Tafel slope (b) of 72.9 mV dec−1 and an overpotential of 105 mV at 50 mA, in agreement with its large ECSA (Cdl = 3.25 mF cm−2) and small interface charge‐transfer resistance. More interestingly, Ni‐9.0 wt.% P alloy exhibits a sustainable catalytic activity toward HER after 1000 cycling test with a tiny potential decline of ~10 mV at 100 mA cm−2. Such a striking HER activity of Ni‐9.0 wt.% P alloy can be attributed to the synergistic effect among the induced active sites from lattice contraction, negatively charged P incorporation, and a mixed nanometre crystal and amorphous structure. Thus, Ni‐P alloy electrodeposited in a CE‐based electrolyte can be used as a promising electrode material with high HER activity in alkaline solutions for hydrogen production.
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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".