Liquid-Phase Exfoliation of Graphite in a Low-Boiling-Point Solvent Using 2,6-Azulene-Based Conjugated Copolymers as Stabilizers
Bibliographic record
Abstract
In the present study, we report a procedure of liquid-phase exfoliation (LPE) of pristine graphite in chloroform using azulene-based copolymers. The resulting dispersions were prepared using tip sonication for only 2 h and were stable over months. Sonication parameters and their impact on the graphene concentration have been studied. Atomic force microscopy, Raman spectroscopy, and transmission electron microscopy revealed that the exfoliated material consists of multiple layers of graphene with an average thickness ranging from 10 to 35 nm. The presence of the polymer not only enables the exfoliation process and stabilizes the dispersions but also improves the processability of the solution. G / PAz films were prepared, and conductivity values of up to 1.9 S·cm –1 were measured.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".