The effects of anodic treatment on the surface chemistry of a Graphite Intercalation Compound
Bibliographic record
Abstract
Graphite intercalation compounds (GIC) can be used as adsorbents for the removal of dissolved organic contaminants in water, and can be rapidly regenerated by electrochemical treatment. After electrochemical regeneration, the adsorption capacity of the GIC is often observed to increase compared to fresh adsorbent. This increase has been attributed to roughening of the surface as well as changes in surface chemistry. Specific surface areas of fresh and electrochemically treated GICs have been measured, and show no significant variation. Consequently, the electrochemical anodic oxidation process used to regenerate the material has been investigated, and these changes, specifically the transformation of the oxygen containing functional groups which is believed to give the GIC its surface chemistry properties, has been measured and studied. Analytical techniques including Scanning Electron Microscopy, Attenuated Total Reflectance Fourier Transform Infra-red spectroscopy, X-ray Photoelectron spectroscopy, Energy Dispersive X-ray spectroscopy and Boehm titrations were used to detect and estimate the relative amounts of functionalities such as carboxylic, quinone and lactonic functional groups. Results showed that fresh GICs have acidic quinone and carboxyl groups on the surface. These functional groups increase upon regeneration, however sustained regeneration leads to the formation of basic lactones which offset the relative amounts of the acidic groups. Acidic functional groups have been reported to increase adsorption, and consequently, there is an initial increase in adsorption due to surface acidic functionalities. Subsequent regeneration leads to the formation of basic functional groups which limit this enhanced adsorption.
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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 | 0.000 |
| 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) | 0.000 | 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".