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The thermal properties and thermoelectric performance of<i>γ</i>-graphyne nanoribbons

2016· article· en· W2291798932 on OpenAlexaff
Zhi Yang, Yu-Long Ji, Guoqiang Lan, Li-Chun Xu, Hua Wang, Xuguang Liu, Bingshe Xu

Bibliographic record

VenueJournal of Physics D Applied Physics · 2016
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsGraphyneThermoelectric effectMaterials scienceThermalEngineering physicsNanotechnologyPhysicsThermodynamics

Abstract

fetched live from OpenAlex

The thermal properties and thermoelectric performance of one-dimensional armchair and zigzag γ -graphyne nanoribbons ( γ -GYNRs) are theoretically investigated in the present study. We found that the pristine γ -GYNRs hold lower phononic thermal conductance and better figure of merit ( ZT ) than graphene nanorribons. The maximal ZT values for the armchair and zigzag γ -GYNRs are 0.93 and 0.61, respectively. By introducing 14 C atoms, the thermoelectric conversion efficiencies of γ -GYNRs are greatly enhanced, thus the isotope effect can significantly improve the thermoelectric properties of the systems. More importantly, under a relatively low temperature, the maximal ZT of a defective zigzag γ -GYNR is as high as 2.12, indicating that γ -GYNRs are promising materials for constructing excellent thermoelectric nanodevices.

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 score0.074
Threshold uncertainty score0.240

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 head0.020
GPT teacher head0.218
Teacher spread0.198 · 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

Citations21
Published2016
Admission routes1
Has abstractyes

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