Unveiling hydrogen evolution dependence on KOH concentration for polycrystalline and nanostructured nickel-based catalysts
Bibliographic record
Abstract
Abstract Nickel-based hydrogen evolution reaction (HER) electrodes have been widely used in alkaline and anion exchange membrane water electrolysis. Therefore, understanding the activity dependence on the KOH concentration (pH) of alkaline electrolytes is essential for designing durable and active HER catalysts. In this work, the HER activity and kinetics of polycrystalline and nanostructured nickel-based catalysts are evaluated in various pH and KOH concentrations. The results for nanostructured NiMo catalyst indicate that both electrochemical active surface area and reaction order have a promoting region under various pH’s and KOH concentrations (0.01–1.0 M, pH 12–14) accompanied by better HER activity (a lower overpotential for achieving − 10 mA cm −2 ) and Tafel slope decreases from around 180 mV dec −1 to 60 mV dec −1 in the same pH and KOH concentration range. The change in the Tafel slope indicates that the HER rate-determining step for HER at NiMo/C changes with pH and KOH concentration. The polycrystalline Ni displays different behaviours where a promoting (0.01–0.10 M, pH 12–13), stabilizing (0.1–1.0 M, pH 13–14), and an inhibiting region (2 M, pH > 14) are present. However, Tafel slopes of around 120 mV/dec are obtained for polycrystalline Ni at all KOH concentrations. The HER characteristics are inhibited at 2.0 M KOH for both catalysts due to slower OH* transport kinetics. The results confirmed the importance of tuning catalyst-pH/KOH concentration for better HER activity and kinetics. Graphical abstract
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.
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 | 0.001 |
| 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".