(General Student Poster Session Award Winner - 1st Place) Effect of Surface Chemistry and Morphology on Polyluminol-Carbon Redox Active Composites
Bibliographic record
Abstract
The rising demand for clean energy and environmental sustainability has led to the growing interest in redox-active organic-carbon composite electrodes for high power and long-lasting energy storage, especially for electrochemical capacitors (EC)[1]. Nitrogen containing organic redox active materials such as the conducting polymer polyluminol chemically polymerized (CpLum) on multiwalled carbon nanotubes (CNT) showed increased capacitive charge storage properties in the composite (CpLum-CNT)[2]. With merely a few nm CpLum, the composite electrodes exhibited reversible faradaic redox reactions and stored c.a. 3x higher volumetric charge than that of bare CNT. Predictions using DFT showed π interactions between the polymers and the CNT substrate. These interactions are thought to have stabilized the composite and contributed to the strong electrochemical performance. In addition to CNT substrates, activated carbons (ACs) offer high specific surface areas, diverse pore size distributions and native surface functionalities owing to their sources. Biomass-derived ACs can serve as low cost, sustainable alternative substrates from feedstocks as pinecone and waste tea [3]–[6]. In this work, we investigate the effects of different surface chemistry, porosity and graphitization on CNT and porous activated carbon surfaces towards the redox activity of the CpLum-carbon composite. The surface functionalities of interest include hydroxyl and carboxyl groups owing to their known contributions toward surface wettability and pseudocapacitance while being present on naturally derived ACs. Varying porosity and graphitization also offer insight into the effects of differing specific surface areas, pore sizes, wettability, and conductivity on the CpLum-carbon composites. Figure 1 a. shows a schematic of the groups of interest and graphitization to investigate the surface interaction of luminol on CNT and Figure 1 b. shows the redox active behavior of CpLum-CNT. The insights from these studies will be used to engineer the surface of carbons such as CNTs and ACs to improve the interfacial properties for redox active materials. References [1] J. N’Diaye, R. Bagchi, J. Y. Howe, and K. Lian, “Redox Active Organic-Carbon Composites for Capacitive Electrodes: A Review,” Sustainable Chemistry , vol. 2, no. 3, pp. 407–440, 2021, doi: 10.3390/suschem2030024. [2] J. N’Diaye, J. Hyun Chang, and K. Lian, “The Capacitive Behavior of Polyluminol on Carbon Nanotubes Electrodes,” ChemElectroChem , vol. 6, no. 21, pp. 5454–5461, Oct. 2019, doi: 10.1002/celc.201901473. [3] M. Genovese and K. Lian, “Polyoxometalate modified pine cone biochar carbon for supercapacitor electrodes,” Journal of Materials Chemistry A , vol. 5, no. 8, pp. 3939–3947, 2017, doi: 10.1039/c6ta10382k. [4] M. Y. Bhat, N. Yadav, and S. A. Hashmi, “Pinecone-derived porous activated carbon for high performance all-solid-state electrical double layer capacitors fabricated with flexible gel polymer electrolytes,” Electrochimica Acta , vol. 304, pp. 94–108, 2019, doi: 10.1016/j.electacta.2019.02.092. [5] H. Eom, J. Kim, I. Nam, and S. Bae, “Recycling Black Tea Waste Biomass as Activated Porous Carbon for Long Life Cycle Supercapacitor Electrodes,” Materials , vol. 14, no. 21, p. 6592, Nov. 2021, doi: 10.3390/ma14216592. [6] Z. Zhu and Z. Xu, “The rational design of biomass-derived carbon materials towards next-generation energy storage: A review,” Renewable and Sustainable Energy Reviews , vol. 134, no. September, p. 110308, 2020, doi: 10.1016/j.rser.2020.110308. 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 | 0.001 | 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".