Polyluminol Modified Carbon Nanotube Electrodes for Electrochemical Capacitors
Bibliographic record
Abstract
Luminol exhibits electrochemical redox activity when electropolymerized on various substrates, and has been used for electrocatalysis and biosensors [1, 2]. This electrochemical behavior is due to the presence of different amine functional groups within the polymer structure. Recent studies have shown that introducing amine groups on a carbon surface improves the charge storage capacity and the conductivity of the obtained material [3]. Our work aims to leverage the electrochemical properties of polyluminol (Plum) for electrochemical capacitors (ECs). Firstly, the Plum was synthesized using a chemical approach and characterized using spectroscopic methods and electrochemical analyses. Secondly, the polymer was deposited on carbon nanotubes (CNT) to enhance the charge storage capacity for ECs. The chemical composition of the polymer was found to be a mixture of benzoid and quinoid segments, bonded via secondary (NH) or tertiary amine (=N-) groups, respectively. Such functionalities facilitated chemical, thermal, and electrochemical stability of the polymer. The composite electrode material was obtained by in-situ chemical polymerization of Plum on CNT. Morphological analyses of CNT confirmed the increase of the Plum thickness on CNT with polymerization time, reaching a saturation point of 6.5 nm. In addition, a 4x increase of charge storage capacity with good electrode stability was observed compared to bare CNT over a potential window of 1.2 V as seen in figure 1. Study of the redox reaction kinetics revealed a mostly capacitive contribution of the polymer on CNT. This work showed the successful surface modification and engineering of CNT using a simple and effective fabrication method, which is suitable for large-scale fabrication of composite electrode materials for ECs. G.-F. Zhang and H.-Y. Chen, Analytica Chimica Acta , 419 , 25 (2000). A. Sassolas, L. J. Blum and B. D. Leca-Bouvier, Sensors and Actuators B: Chemical , 139 , 214 (2009). N. Phattharasupakun, J. Wutthiprom, P. Suktha, N. Ma and M. Sawangphruk, Journal of The Electrochemical Society , 165 , A609 (2018). Figure 1
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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".