Laser fabricated binder-free Ni/NiO nanostructured electrodes for enhanced hydrogen evolution
Bibliographic record
Abstract
The growing demand for green hydrogen via electrochemical water splitting necessitates highly efficient electrocatalysts for the hydrogen evolution reaction (HER). Traditional electrode fabrication methods using organic binders often hinder electron transfer and limit surface area, reducing catalytic performance. Binder-less approaches, such as Ultra-Short Laser Pulses for In-Situ Nanostructure Generation (ULPING), provide an alternative by enhancing electron transfer kinetics and catalytic activity. This study explores the influence of laser fabrication parameters (i.e. laser power and scanning speed) on the growth of nano-Ni/NiO, having broccoli-type morphology, for hydrogen evolution in alkaline media (1 M KOH). SEM and EDX analyses revealed correlations between surface roughness, oxidation, and laser processing conditions, while XPS deconvolution of Ni-2p 3/2 and O-1s spectra provided insights into oxidation states and surface chemistry. Higher laser power increased oxidation and nanostructure formation, leading to enhanced surface area and improved catalytic performance, while lower scanning speeds allowed more ablation time, further improving HER efficiency. Among the four samples studied, sample S3, with highest power and lowest scanning speed, exhibited the best performance with an overpotential of 154 mV at 10 mA/cm², a Tafel slope of 93.8 mV/dec, along with a large ECSA, and stability for 12 hours. Additionally, S3 demonstrated lower charge transfer resistance (R ct ) and higher catalytic turnover frequency (TOF) compared to other samples. These findings establish ULPING as a scalable, reproducible method for fabricating high-performance Ni/NiO electrodes, emphasizing the importance of optimizing fabrication parameters to enhance catalytic activity, in line with the UN’s Sustainable Development Goals (SDGs) for clean energy technologies. • ULPING enables in-situ nanostructuring, enhancing catalytic activity without organic binders. • Higher laser power and lower scanning speeds improve oxidation, surface roughness, and HER performance. • Optimized sample shows low overpotential (154 mV) and Tafel slope (93.8 mV/dec) with 12 hours stability. • Aligns with SDGs, offering a reproducible, resource-efficient hydrogen production.
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How this classification was reachedexpand
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".