Surface and Interface Engineering of Graphene Oxide Films by Controllable Photoreduction
Bibliographic record
Abstract
We report herein the engineering of the surface/interface properties of graphene oxide (GO) films by controllable photoreduction treatment. In our recent works, typical photoreduction processes, including femtosecond laser direct writing (FsLDW), laser holographic lithography, and controllable UV irradiation, have been employed to make conductive reduced graphene oxide (RGO) microcircuits, hierarchical RGO micro-nanostructures with both superhydrophobicity and structural color, as well as moisture-responsive GO/RGO bilayer structures. Compared with other reduction protocols, for instance, chemical reduction and thermal annealing, the photoreduction strategy shows distinct advantages, such as mask-free patterning, chemical-free modification, controllable reduction degree, and environmentally friendly processing. These works indicate that the surface and interface engineering of GO through controllable photoreduction of GO holds great promise for the development of various graphene-based microdevices.
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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 | 0.000 | 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".