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Record W4285399653 · doi:10.1149/ma2022-01552279mtgabs

(General Student Poster Session Award Winner - 1st Place) Effect of Surface Chemistry and Morphology on Polyluminol-Carbon Redox Active Composites

2022· article· en· W4285399653 on OpenAlexaff
Raunaq Bagchi, Dian Yu, Jeanne N’Diaye, Jane Y. Howe, Keryn Lian

Bibliographic record

VenueECS Meeting Abstracts · 2022
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPseudocapacitanceWettingRedoxCarbon nanotubeSupercapacitorMaterials scienceComposite numberCarbon fibersChemical engineeringContact angleElectrochemistryNanotechnologyComposite materialChemistryElectrode

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.626

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.267
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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