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Record W2559626953 · doi:10.1007/s40243-016-0085-x

Grafting of the carbon allotropes and polypyrrole via a Kevlar-type organic linker: the correlation of carbon structure/morphology with electrochemistry of the composite electrode

2016· article· en· W2559626953 on OpenAlexaff
Mariusz Radtke, Anna Ignaszak

Bibliographic record

VenueMaterials for Renewable and Sustainable Energy · 2016
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsPolypyrroleMaterials scienceGrapheneCarbon fibersChemical engineeringElectrochemistryCarbon nanotubeCarbide-derived carbonPolymerPolymer chemistryElectrodePolymerizationComposite materialComposite numberNanotechnologyChemistryCarbon nanofiber

Abstract

fetched live from OpenAlex

The important requirement that needs to be fulfilled for an effective capacitor is fast energy uptake and release [ 1 , 2 ]. Other important features are a long-lasting cycle life, stability and high specific capacitance. They all can be improved by proper chemical, structural and morphological modification of the electrode materials [ 3 ]. Currently, in field of energy storage/conversion electronics, one of the most important task is to replace/decrease the usage of toxic heavy metals by carbonaceous materials that operate with relatively mild electrolytes [ 4 ]. Carbon allotropes such as carbon nanotubes and graphene are the most promising, and thus became essential components that could reach characteristics similar or greater than metallic electrodes [ 5 ]. This is however very challenging since carbons have lower energy density, and consequently, smaller specific capacitance [ 6 ]. On the other hand, carbon-based supercapacitors can store energy and be charged very fast during the reversible adsorption/desorption process of ions in double-layer capacitors, or by the counter-ion doping in pseudo-capacitors [ 7 , 8 ]. Both pseudo-capacitors and electrical double-layer capacitors (EDLCs) have possibilities to improve their specific capacitance by expanding the specific surface and increasing the number of redox active centers (for pseudo-capacitors) [ 9 , 10 ]. Many studies have shown that a combination of both types results in a synergistic improvement of the total capacitance, especially when pseudo-capacitors from the group of conjugated polymers (e.g., polypyrrole or polyaniline) are used. These carbon-polymer hybrid materials or composites outperform their individual components [ 11 – 13 ]. The synergistic improvement is generated by two effects. First, is the increase in conductivity for the pseudo-capacitors resulting in faster ion diffusion that restricts the capacitance [ 14 ]. This process is particularly effective when a strong covalent bond (e.g., amide-type linker) between the polymer and carbon is created. The covalently grafted polymer benefits from improved mechanical stability provided by the carbon support. This combination also demonstrates more dynamic (flexible) structure that can accommodate volumetric changes taking place upon the ion uptake/release in the polymer pseudo-capacitor. The high surface area carbon facilitates uniform distribution of the polymer particles, which is critical during the extensive charge–discharge (shrinking–stretching). Such volumetric changes for a thick and uneven polymer electrode accelerate its degradation due to the local inhomogeneity of the charge distribution (surface with less conductive fractions). All these phenomena shorten the electrode cycle life [ 15 ]. Another important factor is the electronic interaction at the carbon-linker-polymer junction. In the reverse donor–acceptor system, the covalently bound conductive polymer acts as an electron acceptor and the carbon allotrope as the electron donor, resulting in a more electrochemically stable system [ 16 ].

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)0.000
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 score0.004
Threshold uncertainty score0.585

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.003
GPT teacher head0.173
Teacher spread0.170 · 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".

Quick stats

Citations18
Published2016
Admission routes1
Has abstractyes

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