Enhancement of interaction of L-929 cells with functionalized graphene via COOH+ ion implantation vs. chemical method
Bibliographic record
Abstract
Abstract Low hydrophilicity of graphene is one of the major obstacles for biomaterials application. To create some hydrophilic groups on graphene is addressed this issue. Herein, COOH + ion implantation modified graphene (COOH + /graphene) and COOH functionalized graphene were designed by physical ion implantation and chemical methods, respectively. The structure and surface properties of COOH + /graphene and COOH functionalized graphene were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), and contact angle measurement. Compared with graphene, COOH + /graphene and COOH functionalized graphene revealed improvement of cytocompatibility, including in vitro cell viability and morphology. More importantly, COOH + /graphene exhibited better improvement effects than functionalized graphene. For instance, COOH + /graphene with 1 × 10 18 ions/cm 2 showed the best cell-viability, proliferation and stretching. This study demonstrated that ion implantation can better improve the cytocompatibility of the graphene.
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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".