Laser Surface Roughening of Aluminum Foils for Supercapacitor Current Collectors
Bibliographic record
Abstract
Thin aluminum foils were surface roughened by laser ablation in high vacuum conditions. Their performance as current collectors for carbon-based supercapacitors were evaluated by impedance spectroscopy, cyclic voltammetry and galvanostatic cycling, and compared with those of gold plates, flat aluminum foils and commercially available carbon-coated aluminum foils (Z-flo). The results revealed that the laser surface treatment significantly enhances the electronic contact between the current collector and the active materials layers. The benefits in interface enhancement are comparable to those of a carbon coating. High power performances were reached thanks to a significantly decreased internal resistance. Long-term cycling performance revealed a slight but continuous capacity fading for supercapacitor cells having laser-treated current collectors, which was caused by the progressive growth of a surface aluminum oxide layer on the current collector. Cells assembled with carbon-coated collectors did not display the same fading thanks to the protection provided by the interfacial carbon layer. This work demonstrates that laser ablation in vacuum is a promising technique for the preparation supercapacitor current collectors with surface oxide-free and controllable surface microstructures toward specific active materials.
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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 | 0.001 | 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".