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Record W2460133424 · doi:10.1007/s12274-016-1160-4

Tunable filter Raman spectroscopy of purified semiconducting and metallic carbon nanotubes

2016· article· en· W2460133424 on OpenAlexaff
Paul Finnie

Bibliographic record

VenueNano Research · 2016
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsRaman spectroscopyMaterials sciencePolyfluoreneSemiconductorCarbon nanotubeSpectroscopyExcitationOptoelectronicsWavelengthAnalytical Chemistry (journal)NanotechnologyOpticsChemistryPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

Tunable filter Raman spectroscopy is used to efficiently produce Raman excitation maps of unpurified and type-purified single walled carbon nanotubes (SWCNTs). Maps with fine excitation resolution (1 nm) are created over a wide wavelength range (727 to 980 nm), extending from metallic to semiconducting resonances. At a given wavelength, the wide bandwidth (>3,000 cm–1) allows the comparison of the G band with the radial breathing mode (RBM), and shows the 2D band and other less prominent bands. Materials examined included unsorted powders, aqueous sorted semiconductors, aqueous sorted metals, and polyfluorene sorted semiconductors in toluene. The Raman excitation profiles of the G band are broad, relative to the RBM bands. The maps offer evidence of minority species contamination, except in the case of the polyfluorene sorted semiconductors. Tunable Raman spectroscopy data help validate the simpler fixed wavelength Raman spectroscopy approaches to purity assessment.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.798

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.062
GPT teacher head0.343
Teacher spread0.281 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2016
Admission routes1
Has abstractyes

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