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Record W1977175396 · doi:10.1039/b604032m

Electronic properties and reactivity of Pt-doped carbon nanotubes

2006· article· en· W1977175396 on OpenAlexaff
Wei Quan Tian, Lei Vincent Liu, Yan Alexander Wang

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2006
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPhysisorptionChemisorptionRodAdsorptionMaterials scienceDopingCarbon nanotubeAtom (system on chip)NanotechnologyDensity functional theoryCarbon fibersReactivity (psychology)Chemical physicsPhysical chemistryChemistryComputational chemistryComposite numberComposite material

Abstract

fetched live from OpenAlex

The structures of the (5,5) single-walled carbon nanotube (SWCNT) segments with hemispheric carbon cages capped at the ends (SWCNT rod) and the Pt-doped SWCNT rods have been studied within density functional theory. Our theoretical studies find that the hemispheric cages introduce localized states on the caps. The cap-Pt-doped SWCNT rods can be utilized as sensors because of the sensitivity of the doped Pt atom. The Pt-doped SWCNT rods can also be used as catalysts, where the doped Pt atom serves as the enhanced and localized active center on the SWCNT. The adsorptions of C(2)H(4) and H(2) on the Pt atom in the Pt-doped SWCNT rods reveal different adsorption characteristics. The adsorption of C(2)H(4) on the Pt atom in all of the three Pt-doped SWCNT rods studied (cap-end-doped, cap-doped, and wall-doped) is physisorption with the strongest interaction occurring in the middle of the sidewall of the SWCNT. On the other hand, the adsorption of H(2) on the Pt atom at the sidewall of the SWCNT is chemisorption resulting in the decomposition of H(2), and the adsorption of H(2) at the hemispheric caps is physisorption.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.010
GPT teacher head0.213
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations30
Published2006
Admission routes1
Has abstractyes

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