Bibliographic record
Abstract
A wide potential application range of graphene from super capacitors and transparent conductors to antennas, has made it a prominent competitor over traditional metallic elements and carbon nanotubes (CNTs). Ink-based printing processes are of the most favorable fabrication processes for printed electronics. Ink-based printed graphene interconnects usually contain several extra polymer-based components of the ink including solvents and surfactants. Therefore, a post heating process is usually needed to not only eliminate all unwanted components in printed patterns, but also improve the printed graphene performance as an interconnect. In this study, a 1550 nm CW fiber laser irradiation is used to heat treat graphene-based printed patterns fabricated by an aerosol-based micro-scale additive manufacturing technique. The manuscript will address the preliminary optimization of the laser power and speed, in order to degrade undesired elements and obtain pure graphene patterns after post processing. Optical microscopy and scanning electron microscopy (SEM) are employed to investigate the topography and microstructure of graphene patterns.
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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".