Redox behaviour of boron subphthalocyanine carbon nanotube composites
Bibliographic record
Abstract
Organic redox-active carbon composites can be used as sustainable electrode materials in electrochemical energy storage systems. Among numerous redox active species, peripherally dodecafluorinated boron subphthalocyanines (F12BsubPcs) have shown electrochemical redox activities in the solution phase. Nonetheless, the electrochemical properties of solid F12BsubPcs when compositing with nano carbon warrants further investigation for potential applications in energy storage. In this work, nanometer scale axially brominated F12BsubPcs (Br-F12BsubPcs) were coated onto bare graphitized multiwalled carbon nanotubes (GCNT) and COOH-functionalized GCNT (COOH-GCNT) by a facile dip coating method to produce two composites and to compare the effects of the surface functional group interactions with Br-F12BsubPcs. While the surface chemical and morphological characterizations confirmed the presence of Br-F12BsubPc coating on both bare and COOH-GCNTs, the coverage on the latter was higher. Cyclic voltammetric studies in acidic electrolyte revealed a highly reversible redox couple on both composites with Br-F12BsubPc coated COOH-GCNT demonstrating up to c.a. 70% higher redox peak currents than with Br-F12BsubPc coated GCNT. Further analyses of the coated COOH-GCNT suggested a 2-electron transfer process. The charge transfer has fast-kinetics and a strong dependence on the proton concentration. The composites produced in this work demonstrate potential for future application in energy storage and can provide a strategy for developing BsubPc-based carbon composites.
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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".