Epoxide Speciation and Functional Group Distribution in Graphene Oxide Paper‐Like Materials
Bibliographic record
Abstract
Abstract The electronic structure and chemical bonding of three differently prepared samples of graphene oxide paper‐like sheets are studied. Two are created by water filtration of fully oxidized graphene sheets, although one is later intercalated with dodecylamine. The third is created by reducing graphene oxide with hydrazine hydrate. The spectroscopic fingerprints of the aligned epoxide functional groups that unzip the carbon basal plane are found. This unzipping appears to be a result of aging, and the extent to which the basal plane is unzipped can be controlled via the preparation method. In particular, reduction with hydrazine enhances line defect formation, whereas intercalation inhibits the process.The hydroxyl functional group also has a tendency to gather in zones of dense oxidation on the carbon basal plane, a predilection that is not shared by the other prominent functional group species. Finally, the non‐functionalized carbon sites exhibit very similar bonding despite the increase in the sp 2 /sp 3 ratio, confirming that reduction alone is insufficient for producing pristine graphene from graphene oxide. These results are obtained by directly probing the electronic structure of the graphene oxide samples via X‐ray absorption near‐edge structure spectroscopy (XANES) and resonant X‐ray emission spectroscopy (RXES). This work has important significance for the development of graphene oxide as a band gap‐engineered electronic material, as preparation methodology strongly affects not only the initial condition of the sample, but how the electronic structure evolves over time.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".