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Record W2339459167 · doi:10.1149/ma2014-02/3/166

Electrochemical and Thermal Characterization of a Graphene-Based Electrochemical Double-Layer Capacitor (EDLC)

2014· article· en· W2339459167 on OpenAlexaff
Jin Hee Kang

Bibliographic record

VenueECS Meeting Abstracts · 2014
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaterials scienceGrapheneDielectric spectroscopyElectrodeCyclic voltammetryElectrolyteElectrochemistryElectrochemical kineticsCapacitanceChemical engineeringCapacitorContact resistanceAnalytical Chemistry (journal)NanotechnologyLayer (electronics)ChemistryVoltageElectrical engineering

Abstract

fetched live from OpenAlex

Graphene-based electrodes are of great interest for developing high performance electrochemical double-layer capacitors (EDLCs) due to their excellent electrochemical properties, low electric resistance and unique structures. Meanwhile, EDLCs have become more attractive not only to offer high power and energy densities but also to withstand a harsh temperature ranges [1]. Since temperature effects can be crucial to estimate the rational evaluation of degradation, energy efficiency and lifetime, it requires better understanding of temperature-dependent electrochemical properties especially at electrode/electrolyte interfaces. In this study, the performance of an EDLC, assembled with two identical graphene electrodes and the 1M Et 4 NBF 4 /PC electrolyte in a coin cell, is systemically characterized under various operating temperature conditions, ranged from -30 °C to 60 °C. Graphene deposition is carried out by using the vacuum filtration method. This method yields an electrically strong conductive and thermally stable nano-structured graphene paper [2]. Electrochemical characterization techniques including cyclic voltammetry (CV), constant charging/discharging (CCD) and electrochemical impedance spectroscopy (EIS) are performed to evaluate capacitance retention, energy and power densities, internal resistance variation and interfacial processes at the double-layer region. In addition, EIS data is simulated with the proposed electric equivalent circuit in order to investigate the temperature dependency on interfacial reactions with respects to mass transfer (diffusion) and electrode kinetics (charge transfer) [3]. Each reaction is represented by electrical resistive elements in the equivalent circuit, and its values are correlated with the activation energy to quantitatively rationalize the observed behaviour of diffusion and the charge transfer kinetics with temperature. References: [1] R. Kotz, M. Hahn, R. Gallay, Journal of Power Sources, 154 (2006) 550-555. [2] H. Chen, M.B. Mueller, K.J. Gilmore, G.G. Wallace, D. Li, Advanced Materials, 20 (2008) 3557. [3] J.W. Jinhee Kang, Shesha H. Jayaram, Aiping Yu, Xiaohui Wang, Electrochimica Acta, 115 (2014) 587-598.

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 score0.009
Threshold uncertainty score0.731

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 head0.013
GPT teacher head0.219
Teacher spread0.206 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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