Substrate Bias Effect on Amorphous Hydrogenated Carbon Films Deposited by Filtered Cathodic Arc Deposition
Bibliographic record
Abstract
In the present study, we briefly describe the 45° angle magnetic filtered arc deposition (FAD) process and investigate the effect of substrate bias on the hardness of amorphous carbon (a-C) films. An attempt is made to correlate the microstructure, chemical composition and chemical bonding states with the hardness of the corresponding films. After deposition, the film properties were analyzed by Raman spectroscopy and nanoindentation system (NIS). It was found that amorphous carbon films possess highest hardness when deposited at substrate biases ranging from -50 V to -100 V. The hardness values do not show good correlation with Raman I(D)/I(G) ratio. Hydrogen additions to the system help prevent the nucleation of the graphite phase, and stabilize the sp3 bonding of amorphous hydrogenated carbon films. Hydrogen affected on the small graphitic crystalline growth. Films have higher hardness when they have higher fraction of sp3 content.
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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".