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Record W2327850992 · doi:10.1021/cm302823f

Hydrothermal Synthesis and Electrochemical Properties of Li<sub>2</sub>CoSiO<sub>4</sub>/C Nanospheres

2013· article· en· W2327850992 on OpenAlexafffund
Guang He, Guerman Popov, Linda F. Nazar

Bibliographic record

VenueChemistry of Materials · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHydrothermal circulationMaterials scienceElectrochemistryCarbon fibersChemical engineeringNanocompositeHydrothermal synthesisSilicateElectrolyteFumed silicaMesoporous materialParticle sizeNanotechnologyComposite materialElectrodeChemistryComposite numberCatalysisOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

A highly ordered mesoporous carbon/silica (MCS) framework was used as both a silicate precursor and carbon source to prepare Li 2 CoSiO 4 /carbon nanocomposites via hydrothermal synthesis. TEM-EDX and TGA measurements showed that ∼2 wt % carbon was incorporated within Li 2 CoSiO 4 crystal aggregates on the nanoscale. We find that both the morphology and particle size of the Li 2 CoSiO 4 /C composites are significantly influenced by the LiOH concentration in the precursors. By controlling the molar ratio of LiOH:Si:Co = 8:1:1, very uniform Li 2 CoSiO 4 /C spheres were obtained with an average diameter of 300–400 nm. Many exhibit hollow or core–shell structures. A mechanism is proposed to account for both the unusual morphology and carbon incorporation. Despite some electrolyte oxidation at high potential, the electrochemical properties of the Li 2 CoSiO 4 /C composites showed that the nanocarbon played an important role in enhancing the electrochemical performance, when compared with Li 2 CoSiO 4 prepared using fumed silica as the silicate source under similar conditions.

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 score0.002
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 head0.007
GPT teacher head0.178
Teacher spread0.171 · 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

Citations48
Published2013
Admission routes2
Has abstractyes

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