MétaCan
Menu
Back to cohort
Record W4249401280 · doi:10.1002/ange.201611834

Helically Coiled Graphene Nanoribbons

2017· article· en· W4249401280 on OpenAlexafffund
Maxime Daigle, Dandan Miao, Andrea Lucotti, Matteo Tommasini, Jean‐François Morin

Bibliographic record

VenueAngewandte Chemie · 2017
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGraphene nanoribbonsGrapheneRaman spectroscopyMaterials scienceBand gapX-ray photoelectron spectroscopyDelocalized electronNanotechnologyChemical physicsChemistryChemical engineeringOptoelectronicsPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Graphene is a zero‐gap, semiconducting 2D material that exhibits outstanding charge‐transport properties. One way to open a band gap and make graphene useful as a semiconducting material is to confine the electron delocalization in one dimension through the preparation of graphene nanoribbons (GNR). Although several methods have been reported so far, solution‐phase, bottom‐up synthesis is the most promising in terms of structural precision and large‐scale production. Herein, we report the synthesis of a well‐defined, helically coiled GNR from a polychlorinated poly( m ‐phenylene) through a regioselective photochemical cyclodehydrochlorination (CDHC) reaction. The structure of the helical GNR was confirmed by 1 H NMR, FT‐IR, XPS, TEM, and Raman spectroscopy. This Riemann surface‐like GNR has a band gap of 2.15 eV and is highly emissive in the visible region, both in solution and the solid state.

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 score0.027
Threshold uncertainty score0.797

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.030
GPT teacher head0.301
Teacher spread0.271 · 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

Citations42
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueAngewandte ChemieSame topicGraphene research and applicationsFrench-language works237,207