Effect of post-annealing on the plasma etching of graphene-coated-copper
Bibliographic record
Abstract
High temperature deposition of graphene on Cu by chemical vapor deposition can be used to produce high quality films. However, these films tend to have a non-equilibrium structure, with relatively low graphene adhesion. In this study, samples of graphene grown on copper foils by high temperature CVD were post-deposition annealed at temperatures well below the critical temperature of Cu. Resistance to etching under plasma was examined to assess the mechanical robustness of the graphene on the Cu surface, analyzed using optical and Raman microscopies. We found a correlation between the post-annealing time and etching time for the complete removal of graphene from Cu. Etching rates, minimum etch times, and surface appearance were observed to vary depending on the etching plasma (air, oxygen or nitrogen). Oxygen plasmas were found to be the least aggressive, emphasizing the improved adhesion with post-annealing treatments. Our results imply that the etching of graphene on Cu, and hence the adhesion of graphene, can be controlled by proper annealing and choice of plasma gas.
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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 | 0.001 |
| 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) | 0.000 | 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".