Visualizing chemical states and defects induced magnetism of graphene oxide by spatially-resolved-X-ray microscopy and spectroscopy
Bibliographic record
Abstract
This investigation studies the various magnetic behaviors of graphene oxide (GO) and reduced graphene oxides (rGOs) and elucidates the relationship between the chemical states that involve defects therein and their magnetic behaviors in GO sheets. Magnetic hysteresis loop reveals that the GO is ferromagnetic whereas photo-thermal moderately reduced graphene oxide (M-rGO) and heavily reduced graphene oxide (H-rGO) gradually become paramagnetic behavior at room temperature. Scanning transmission X-ray microscopy and corresponding X-ray absorption near-edge structure spectroscopy were utilized to investigate thoroughly the variation of the C 2p(π*) states that are bound with oxygen-containing and hydroxyl groups, as well as the C 2p(σ*)-derived states in flat and wrinkle regions to clarify the relationship between the spatially-resolved chemical states and the magnetism of GO, M-rGO and H-rGO. The results of X-ray magnetic circular dichroism further support the finding that C 2p(σ*)-derived states are the main origin of the magnetism of GO. Based on experimental results and first-principles calculations, the variation in magnetic behavior from GO to M-rGO and to H-rGO is interpreted, and the origin of ferromagnetism is identified as the C 2p(σ*)-derived states that involve defects/vacancies rather than the C 2p(π*) states that are bound with oxygen-containing and hydroxyl groups on GO sheets.
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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".