Electrochemical Exfoliation of Graphite to Graphene-Based Nanomaterials
Bibliographic record
Abstract
Here, we report on a new automated electrochemical process for the production of graphene oxide (GO) from graphite though electrochemical exfoliation. The effects of the electrolyte and applied voltage were investigated and optimized. The morphology, structure and composition of the electrochemically exfoliated GO (EGO) were probed by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), energy dispersive X-ray (EDX) spectroscopy, X-ray photoelectron spectroscopy (XPS), FTIR spectroscopy and Raman spectroscopy. Important metrics such as the oxygen content (25.3 at.%), defect density (ID/IG = 0.85) and number of layers of the formed EGO were determined. The EGO was also compared with the GO prepared using the traditional chemical method, demonstrating the effectiveness of the automated electrochemical process. The electrochemical properties of the EGO, CGO and other carbon-based materials were further investigated and compared. The automated electrochemical exfoliation of natural graphite powder demonstrated in the present study does not require any binders; it is facile, cost-effective and easy to scale up for a large-scale production of graphene-based nanomaterials for various applications.
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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 | 0.001 |
| 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".