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Record W3045239048 · doi:10.1063/5.0011810

Phonon localization in single wall carbon nanotube: Combined effect of 13C isotope and vacancies

2020· article· en· W3045239048 on OpenAlexaff
Md. Sherajul Islam, Ashraful Hossain Howlader, Khalid N. Anindya, Rongkun Zheng, Jeongwon Park, Akihiro Hashimoto

Bibliographic record

VenueJournal of Applied Physics · 2020
Typearticle
Languageen
FieldMaterials Science
TopicThermal properties of materials
Canadian institutionsPolytechnique MontréalUniversity of OttawaRegroupement Québécois sur les Matériaux de Pointe
Fundersnot available
KeywordsPhononKinetic isotope effectRaman spectroscopyGrapheneCarbon nanotubeMaterials scienceIsotopeCondensed matter physicsMolecular physicsChemistryDeuteriumAtomic physicsNanotechnologyPhysicsOptics

Abstract

fetched live from OpenAlex

The combined effect of 13C isotope doping and vacancies on the phonon properties of a single-wall carbon nanotube is theoretically investigated using the forced oscillation method. The phonon density of states (PDOS) is calculated for all (0%–100%) 13C isotope contents and wide (0%–30%) vacancy concentrations. We found a redshift of the Raman active E2g peak in the PDOS with increasing isotope contents, while the disappearance of the E2g peak and the appearance of a new sharp peak in the low-energy region with increasing combined defects. Both 13C isotope and combined defects cause the localization of the high-energy optical phonons. We calculated the typical mode patterns for the in-plane longitudinal optical phonon to visualize the localization phenomena elaborately at the presence of isotope and vacancies. The calculated average localization length shows an asymmetric behavior with increasing 13C isotope concentrations which is in good agreement with the 13C isotope dependence localization length of single-layer graphene. We noticed that a typical localization length is on the order of ∼1 nm at 70% isotope concentrations. The combined effect of 13C isotope and vacancies shows an abruptly decreasing localization length with increasing defect densities. These results are important to understand the heat conduction as well as nanoscopic vibrational studies such as tip-enhanced Raman spectra in carbon nanotubes where the local phonon energies may be mapped.

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 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 score0.007
Threshold uncertainty score0.385

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 head0.205
Teacher spread0.192 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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