Surface Characteristics of Microporous and Mesoporous Carbons Functionalized with Pentafluorophenyl Groups
Bibliographic record
Abstract
The in situ diazonium reduction reaction is a reliable and well-known approach for the surface modification of carbon materials for use in a range of applications, including in energy conversion, as chromatography supports, in sensors, etc. Here, this approach was used for the first time with mesoporous colloid-imprinted carbons (CICs), materials that contain ordered monodisperse pores (10–100 nm in diameter) and are inherently highly hydrophilic, using a common microporous carbon (Vulcan carbon (VC)), which is relatively more hydrophobic, for a comparison. The ultimate goal of this work was to modify the CIC wettability without altering its nanostructure and also to lower its susceptibility to oxidation, as required in fuel cell and battery electrodes, by the attachment of pentafluorophenyl (−PhF 5 ) groups onto their surfaces. This was shown to be successful for the CIC, with the −PhF 5 groups uniformly coating the inner pore walls at a surface coverage of ca. 90% and allowing full solution access to the mesopores, while the −PhF 5 groups deposited only on the outer VC surface, likely blocking its micropores. Contact angle kinetics measurements showed enhanced hydrophobicity, as anticipated, for both the −PhF 5 modified CIC and VC materials, even revealing superhydrophobicity at times for the CIC materials. In contrast, water vapor sorption and cyclic voltammetry suggested that the micropores remained hydrophilic, arising from the deposition of smaller N- and O-containing surface groups, caused by a side reaction during the in situ diazonium functionalization process.
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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".