Laser micro/nano structuring of three-dimensional porous gradient graphene: Advanced heater for antibacterial surfaces and ion-selective electrode for sweat sensing
Bibliographic record
Abstract
The development of three-dimensional (3D) gradient porous graphene (GPG) patterns, leveraging the remarkable properties and unique structure of graphene, has garnered considerable attention owing to their excellent electrochemical and electrothermal performances. Among the numerous graphene synthesis methods, laser-induced graphene (LIG) stands out as an eco-friendly and practical approach for creating patterned graphene structures on commercial films, with synthetic details varying depending on the application. Unlike conventional LIG with uniform geometric characteristics, we developed an innovative approach for circular line-scribed ultraviolet (UV)-LIG patterning; these approaches utilize a high overlapping factor and low power to achieve uneven graphitization. A comprehensive analysis of the 3D GPG was conducted via specific surface area measurements, contact angle analyses, sheet resistance measurements, X-ray photoelectron spectroscopy, and Raman spectroscopy. These 3D GPG structures exhibit large surface areas, low sheet resistance, and superior ion transport, thus improving heater and ion-selective electrode (ISE) performances. The fabricated 3D GPG heaters were successfully applied to antibacterial surfaces, and the ISEs were applied in a sweat sensor was demonstrated owing to the remarkable combination of high surface area, low electrical resistance, and unique 3D porous structure.
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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 | 0.000 | 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) | 0.000 | 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".