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Record W2771473781 · doi:10.1002/aenm.201702381

3D Porous Carbon Sheets with Multidirectional Ion Pathways for Fast and Durable Lithium–Sulfur Batteries

2017· article· en· W2771473781 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdvanced Energy Materials · 2017
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsUniversity of Waterloo
FundersChina Scholarship CouncilUniversity of WaterlooNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsPolysulfideMaterials scienceSulfurPorosityElectrochemistryCarbon fibersLithium (medication)NanotechnologyEnergy storageIonElectrodeFaraday efficiencyChemical engineeringElectrolyteComposite materialOrganic chemistryChemistry

Abstract

fetched live from OpenAlex

Abstract In this work, unique porous carbon sheets (PCSs) are developed via a facile synthesis. The obtained PCS delivers long‐range conductive framework, abundant active interfaces, rich element doping, and notably a high inner porosity that builds up an admirable 3D network for multidirectional ion transfer. Such unique architecture and surface chemistry enable ultrafast sulfur electrochemistry as well as high‐efficiency inhibition on polysulfide shuttling via the dually physical and chemical sulfur confinement. The PCS‐based sulfur electrodes achieve superb rate capability up to 10 C, outstanding cyclability over 1000 cycles, and high areal capacity of 4.8 mA h cm −2 . This work offers an appealing model of material engineering for fast and reliable lithium–sulfur batteries, as well as guidance for rational structural design in extended energy storage and conversion systems.

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.

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 score0.013
Threshold uncertainty score1.000

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 head0.009
GPT teacher head0.200
Teacher spread0.191 · 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