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Record W1870461189 · doi:10.1039/c5cp02938d

Electronic and optical properties of pristine and boron–nitrogen doped graphyne nanotubes

2015· article· en· W1870461189 on OpenAlexfundno aff
Barnali Bhattacharya, Ngangbam Bedamani Singh, Rajkumar Mondal, Utpal Sarkar

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2015
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsnot available
FundersCompute CanadaMcMaster University
KeywordsMaterials scienceBand gapGraphyneZigzagRefractive indexDopingDopantDensity functional theoryAnisotropyAbsorption (acoustics)BoronMolecular physicsOptoelectronicsCondensed matter physicsNanotechnologyComputational chemistryOpticsChemistryGraphenePhysics

Abstract

fetched live from OpenAlex

First principle calculations with generalized gradient approximation were carried out to analyse the electronic and optical properties of armchair and zigzag graphyne nanotubes (GNTs). The possible application of these NTs in optoelectronic devices was also investigated. The GNTs were doped with boron (B) and nitrogen (N) atoms and the resulting band gap tuning was studied with respect to the B/N substitution site and increasing diameter of the NTs. The basis of this variation was examined using the partial density of states and crystal orbital Hamilton population analysis. A decreasing trend in the optical response was seen with an increase in the diameter of the NTs. The reported systems showed anisotropic behaviour in the low-energy region. The origin of the optical responses was monitored from the infrared to the UV region depending on the doping site of the B/N. As a result of the large band gap, low reflectivity and low refractive index, B/N GNTs have been established as a suitable system for novel optoelectronic devices. The strong absorption peaks in the UV region mean that they are a good choice for use in UV light protection.

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 score0.063
Threshold uncertainty score0.593

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 studies0.0000.001
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 head0.022
GPT teacher head0.252
Teacher spread0.230 · 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

Citations82
Published2015
Admission routes1
Has abstractyes

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