On Oxygen‐Containing Groups in Chemically Modified Graphenes
Bibliographic record
Abstract
Reduced graphenes (belonging to the class of chemically modified graphenes, CMG) are one of the most investigated and utilized materials in current research. Oxygen functionalities on the CMG surfaces have dramatic influences on material properties. Interestingly, these functionalities are rarely comprehensively characterized. Herein, the four most commonly used CMGs, mainly electrochemically reduced graphene oxide (ER-GO), thermally reduced graphene oxide (TR-GO), and the corresponding starting materials, that is, graphene oxide and graphite oxide, were comprehensively characterized by a wide variety of methods, such as high-resolution X-ray photoelectron spectroscopy, electrochemical impedance spectroscopy, UV/Vis spectroscopy, transmission electron microscopy (TEM), and voltammetry, to establish connections between the structures of these materials that carry different oxygen functionalities and their electrochemical behaviors. This was followed by the quantification of the negatively charged oxygen-containing groups (OCGs) by UV/Vis spectroscopy and of the electrochemically reducible OCGs by voltammetry. Lastly, a biofunctionalization with gold nanoparticle (AuNP)-modified DNA sequences was performed by the formation of covalent bonds with the carboxylic groups (-COOH) on the CMG surfaces. There was an evident predominance of functionalizable -COOH groups on the ER-GO surface, as confirmed by a higher amount of Au detected both with differential-pulse voltammetry and impedance spectroscopy, coupled with visualization by TEM. We exploited the DNA-Au bioconjugates as highly specific stains to localize and visualize the positions of carboxylic groups. Our findings are very important to clearly identify the presence, nature, and distribution of oxygen functionalities on different chemically modified graphenes.
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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".