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Record W2224538295 · doi:10.1021/acsami.5b10267

Sulfur Nanogranular Film-Coated Three-Dimensional Graphene Sponge-Based High Power Lithium Sulfur Battery

2016· article· en· W2224538295 on OpenAlexafffund
Wook Ahn, Min Ho Seo, Yun‐Seok Jun, Dong Un Lee, Fathy M. Hassan, Xiaolei Wang, Aiping Yu, Zhongwei Chen

Bibliographic record

VenueACS Applied Materials & Interfaces · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Waterloo
KeywordsMaterials scienceGrapheneLithium–sulfur batterySulfurBattery (electricity)Lithium (medication)SpongeNanotechnologyPower (physics)Metallurgy

Abstract

fetched live from OpenAlex

To meet the requirements of both high energy and power density with cycle durability of modern EVs, we prepared a novel nanosulfur granular assembled film coated on the three-dimensional graphene sponge (3D-GS) composite as a high-performance active material for rechargeable lithium sulfur batteries. Instead of conventional graphene powder, three-dimensional rGO sponge (3D-rGO) is employed for the composite synthesis, resulting in a sulfur film directly in contact with the underlying graphene layer. This significantly improves the overall electrical conductivity, strategically addressing challenges of conventional composites of low sulfur utilization and dissolution of polysulfides. Additionally, the synthesis mechanism of 3D-GS is elucidated by XPS and DFT analyses, where replacement of hydroxyl group of 3D-rGO sponge by sulfur (S8) is found to be thermodynamically favorable. As expected, 3D-GS demonstrates outstanding discharge capacity of 1080 mAh g(-1) at a 0.1C rate, and 86.2% capacity retention even after 500 cycles at a 1.0C rate.

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), Insufficient payload (model declined to judge)
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 score0.005
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.193
Teacher spread0.185 · 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

Citations72
Published2016
Admission routes2
Has abstractyes

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