UV/Ozone-Assisted Covalent Bioconjugation on Graphene Tapes
Bibliographic record
Abstract
Compared to pristine graphene, graphene oxide (GO) has intriguing advantages for biological applications, such as high compatibility and much improved solubility in an aqueous environment. In particular, the oxygen-containing functional groups on GO enable the highly stable covalent conjugation of biomolecules, which promotes its application for developing versatile functional devices. In this work, we explored an ultraviolet/ozone (UV/O 3 ) treatment strategy to activate graphene-tape substrates (prepared by drop-casting graphene nanoplatelets on double-sided conductive carbon tapes) to achieve excellent bioconjugation capabilities. Our Fourier transform infrared spectroscopy (FTIR), wetting, and X-ray photoelectron spectroscopy (XPS) measurements confirmed the generation of high-density oxygen-containing functional groups on graphene-carbon tape, while the conductivity and electrochemical activity are merely influenced. Upon immobilizing amino-ferrocene (Fc-NH 2 ) onto the UV/O 3 -activated graphene tape via carbodiimide cross-linking, a strong pair of redox peaks (corresponding to an Fc surface density over 8.0 × 10 –9 mol/cm 2 ) was observed, indicative of its “elevated” covalent conjugation capability. More remarkably, highly efficient conjugation of glucose oxidase on UV/O 3 -treated graphene tape was achieved, which demonstrated excellent catalytic activity, as confirmed by chronoamperometry. These results augment the great potential of UV/O 3 -activated graphene tape substrates for convenient fabrication of electroactive biofunctional devices with high performance.
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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".