Prickly Nickel Nanowires Grown on Cu-Ni Substrate Surface as High Performance Cathodes for Hydrogen Evolution Reaction
Bibliographic record
Abstract
A new and highly rough nickel electrode is fabricated based on in-situ assembling of prickly nickel nanowires, synthesized by electroless deposition method on a layer of nickel freshly preelectrodeposited on copper, constructing Cu-Ni-PNNWs. Then, the fabricated electrode is studied for Hydrogen Evolution Reaction (HER). Surface morphology of the electrodes is characterized by Field Emission Scanning Electron Microscopy (FESEM) and X-ray diffraction (XRD) microanalysis. Kinetics of the HER is studied in 0.5 M H2SO4 on Cu-Ni-PNNWs electrode in comparison with Ni and Cu-Ni electrodes. Evaluation of the electrode activities is carried out by steady-state polarization curves (Tafel plots) and electrochemical impedance spectroscopy (EIS). The results obtained by electrochemical characterizations have shown that the Cu-Ni-PNNWs electrode benefits of high electrocatalytic activity for the HER. The EIS data are approximated using appropriate equivalent circuit model, and values of the model parameters are extracted. Analysis of the EIS results has revealed that the double layer capacitance (Cdl) and exchange current density (j0) of the Cu-Ni-PNNWs electrode are increased by factors of ~ 47 and ~ 19 times, respectively, compared with Cu-Ni. Up to our knowledge, this is the first finding of this type, reporting synthesis and activity of the Cu-Ni-PNNWs electrode for the HER.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".