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Record W2086003433 · doi:10.1039/c3cp44172e

Hierarchical nanostructured core–shell Sn@C nanoparticles embedded in graphene nanosheets: spectroscopic view and their application in lithium ion batteries

2013· article· en· W2086003433 on OpenAlexaff
Dongniu Wang, Xifei Li, Jinli Yang, Jiajun Wang, Dongsheng Geng, Ruying Li, Mei Cai, Tsun‐Kong Sham, Xueliang Sun

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsWestern University
Fundersnot available
KeywordsTinMaterials scienceGrapheneChemical vapor depositionNanosheetNanoparticleNanotechnologyChemical engineeringCarbon fibersLithium (medication)AnodeTin oxideElectrodeComposite numberComposite materialOxideChemistryMetallurgyPhysical chemistry

Abstract

fetched live from OpenAlex

Hierarchical carbon encapsulated tin (Sn@C) embedded graphene nanosheet (GN) composites (Sn@C-GNs) have been successfully fabricated via a simple and scalable one-step chemical vapor deposition (CVD) procedure. The GN supported Sn@C core-shell structures consist of a crystalline tin core, which is thoroughly covered by a carbon shell and more interestingly, extra voids are present between the carbon shell and the tin core. Synchrotron spectroscopy confirms that the metallic tin core is free of oxidation and the existence of charge redistribution transfer from tin to the carbonaceous materials of the shell, facilitating their intimate contact by chemical bonding and resultant lattice variation. The hybrid electrodes of this material exhibit a highly stable and reversible capacity together with an excellent rate capability, which benefits from the improved electrochemical properties of tin provided by the protective carbon matrix, voids and the flexible GN matrices.

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 score0.060
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.008
GPT teacher head0.225
Teacher spread0.217 · 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

Citations119
Published2013
Admission routes1
Has abstractyes

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