Pronounced, Reversible, and in Situ Modification of the Electronic Structure of Graphene Oxide via Buckling below 160 K
Bibliographic record
Abstract
Abstract We have shown that the electronic structure of graphene oxide is strongly, but reversibly, affected by temperature. Below 160 K, graphene oxide is much more completely oxidized, removing any last remaining π-conjugated network. Through DFT simulations, we have shown that this is due to buckling-induced oxidation. As temperature is reduced, the lightly oxidized, graphene-like zones attempt to expand due to a negative thermal expansion coefficient (TEC), but the heavily oxidized zones, with a TEC that is near zero, prevent this from happening. This contributes to localized buckling. The deformed regions oxidize much more readily, and the 1,2-epoxide groups form a new type of functional group never before seen: a triply bonded oxygen, bonded at the 1,3,5 sites of the hexagonal carbon rings. We have called this group TB-epoxide. Stable only under buckling, the TB-epoxide groups revert back to 1,2-epoxides once the lattice relaxes to a flatter profile. We have shown that one can alter the electronic structure of graphene oxide to induce temporary, but more complete, oxidation via strain.
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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) | 0.004 | 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".