Production of High-Quality Graphene Using a Novel Electrochemical Intercalation-Exfoliation Approach
Bibliographic record
Abstract
Large scale production of graphene has recently received a great deal of attention because of its interesting properties and wide range of potential applications. Conventional chemical exfoliation approaches, such as Hummer’s method,provides cost-effective pathway for large scale production, however, the method suffers from several key challenges such as the usage of corrosive and toxic solution, high processing temperature, long duration, and the poor quality of graphene produced which severely affects its potential applications. Recently, electrochemical exfoliation of graphene has been proposed for a high production yield with better quality. The electrochemical method involves two steps: 1) intercalation of ionic species between the graphene layers, followed by 2) oxidation of these ionic species under an anodic voltage into gas molecule enabling exfoliation of graphene flakes from the graphite electrode.1 In this study we examine a new approach to the intercalation, using an intercalating ion that has received very little attention and has not been evaluated for electrochemical exfoliation. The intercalation was followed by exfoliation in (NH4)2SO4 solution leading to the production of graphene flakes. The resultant graphene was found to have less disrupted sp2 lattice structure, with a high yield of about 95 % of graphene, along with high electrical conductivity and a low oxidation level (with a C:O ratio of about 15, determined by XPS). In addition, the presence of nitrogen and sulfur moieties in the resulting graphene structure can act as an electrocatalyst2 for applications such as the oxygen reduction reaction. Thus, the as-prepared graphene could be used for a range of electrochemical applications. References: (1) Sharif, F.; Zeraati, A. S.; Ganjeh-Anzabi, P.; Yasri, N.; Perez-Page, M.; Holmes, S. M.; Sundararaj, U.; Trifkovic, M.; Roberts, E. P. L. Synthesis of a High-Temperature Stable Electrochemically Exfoliated Graphene. Carbon 2019. (2) Singh, A.; Yasri, N.; Karan, K.; Roberts, E. P. L. Electrocatalytic Activity of Functionalized Carbon Paper Electrodes and Their Correlation to the Fermi Level Derived from Raman Spectra. ACS Appl. Energy Mater. 2019, acsaem.9b00180.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".