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Record W2327001674 · doi:10.1021/nn404439r

Tailoring Porosity in Carbon Nanospheres for Lithium–Sulfur Battery Cathodes

2013· article· en· W2327001674 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.

Bibliographic record

VenueACS Nano · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPorosityMaterials scienceSulfurCarbon fibersElectrolyteCathodeChemical engineeringMesoporous materialComposite numberComposite materialElectrodeChemistryMetallurgyCatalysisOrganic chemistry

Abstract

fetched live from OpenAlex

Porous hollow carbon spheres with different tailored pore structures have been designed as conducting frameworks for lithium-sulfur battery cathode materials that exhibit stable cycling capacity. By deliberately creating shell porosity and utilizing the interior void volume of the carbon spheres, sufficient space for sulfur storage as well as electrolyte pathways is guaranteed. The effect of different approaches to develop shell porosity is examined and compared in this study. The most highly optimized sulfur-porous carbon nanosphere composite, created using pore-formers to tailor shell porosity, exhibits excellent cycling performance and rate capability. Sulfur is primarily confined in 4-5 nm mesopores in the carbon shell and inner lining of the shells, which is beneficial for enhancing charge transfer and accommodating volume expansion of sulfur during redox cycling. Little capacity degradation (∼0.1% /cycle) is observed over 100 cycles for the optimized material.

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 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 score0.006
Threshold uncertainty score0.571

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 head0.012
GPT teacher head0.211
Teacher spread0.199 · 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