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Record W2513035007 · doi:10.1021/acsami.6b08298

Highly Oriented Graphene Sponge Electrode for Ultra High Energy Density Lithium Ion Hybrid Capacitors

2016· article· en· W2513035007 on OpenAlexafffund
Wook Ahn, Dong Un Lee, Ge Li, Kun Feng, Xiaolei Wang, Aiping Yu, Gregory Lui, Zhongwei Chen

Bibliographic record

VenueACS Applied Materials & Interfaces · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversity of Waterloo
FundersUniversity of WaterlooNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsMaterials scienceGrapheneCapacitorElectrodeLithium (medication)Energy densityNanotechnologyIonSpongeSupercapacitorOptoelectronicsEngineering physicsElectrochemistryVoltageElectrical engineering

Abstract

fetched live from OpenAlex

Highly oriented rGO sponge (HOG) can be easily synthesized as an effective anode for application in high-capacity lithium ion hybrid capacitors. X-ray diffraction and morphological analyses show that successfully exfoliated rGO sponge on average consists of 4.2 graphene sheets, maintaining its three-dimensional structure with highly oriented morphology even after the thermal reduction procedure. Lithium-ion hybrid capacitors (LIC) are fabricated in this study based on a unique cell configuration which completely eliminates the predoping process of lithium ions. The full-cell LIC consisting of AC/HOG-Li configuration has resulted in remarkably high energy densities of 231.7 and 131.9 Wh kg(-1) obtained at 57 W kg(-1) and 2.8 kW kg(-1). This excellent performance is attributed to the lithium ion diffusivity related to the intercalation reaction of AC/HOG-Li which is 3.6 times higher that of AC/CG-Li. This unique cell design and configuration of LIC presented in this study using HOG as an effective anode is an unprecedented example of performance enhancement and improved energy density of LIC through successful increase in cell operation voltage window.

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 categoriesMeta-epidemiology (narrow)
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 score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
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 head0.007
GPT teacher head0.203
Teacher spread0.196 · 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.

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

Citations68
Published2016
Admission routes2
Has abstractyes

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