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Record W2761321363 · doi:10.1021/acsami.7b11628

Moving Beyond Boron-Based Substituents To Achieve Phosphorescence in Tellurophenes

2017· article· en· W2761321363 on OpenAlexafffund
William Torres Delgado, Christina A. Braun, Michael P. Boone, Olena Shynkaruk, Yanyu Qi, Robert McDonald, Michael J. Ferguson, Przemysław Data, Shawan K. C. Almeida, Inara de Aguiar, Gabriel L. C. de Souza, Alex Brown, Gang He, Eric Rivard

Bibliographic record

VenueACS Applied Materials & Interfaces · 2017
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence and Fluorescent Materials
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaHorizon 2020 Framework ProgrammeCanada Foundation for InnovationKillam TrustsAlexander von Humboldt-Stiftung
KeywordsPhosphorescenceQuenching (fluorescence)PhosphorBoronPhotochemistryLuminescenceTelluriumArylMaterials scienceOxygenPersistent luminescenceSolid-stateFluorescenceOptoelectronicsChemistryPhysical chemistryOrganic chemistryPhysicsThermoluminescenceOptics

Abstract

fetched live from OpenAlex

Previous research in our group showed that tellurophenes with pinacolboronate (BPin) units at the 2- and/or 5-positions displayed efficient phosphorescence in the solid state, both in the presence of oxygen and water. In this current study, we show that luminescence from a tellurophene is possible when various aryl-based substituents are present, thus greatly expanding the family of known (and potentially accessible) Te-based phosphors. Moreover, for the green phosphorescent perborylated tellurium heterocycle, 2,3,4,5-TeC 4 BPin 4 ( 4BTe ), oxygen-mediated quenching of phosphorescence is an important contributor to the lack of emission in solution (when exposed to air); thus, this system displays aggregation-enhanced emission (AEE). These discoveries should facilitate the future design of color tunable tellurium-based luminogens.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.014
GPT teacher head0.260
Teacher spread0.247 · 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 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

Citations49
Published2017
Admission routes2
Has abstractyes

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