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Record W1964354534 · doi:10.1351/pac-con-11-09-22

Tetrathiafulvalene vinylogues as versatile building blocks for new organic materials

2012· article· en· W1964354534 on OpenAlexafffund
Yuming Zhao, Guang Chen, Karimulla Mulla, Ilias Mahmud, Shuai Liang, Prateek Dongare, David W. Thompson, Louise N. Dawe, Stephen Bouzan

Bibliographic record

VenuePure and Applied Chemistry · 2012
Typearticle
Languageen
FieldMaterials Science
TopicOrganic and Molecular Conductors Research
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaMemorial University of Newfoundland
KeywordsTetrathiafulvaleneMolecular tweezersChemistryMolecular electronicsNanotechnologyTweezersCharacterization (materials science)Combinatorial chemistryElectronic materialsPolymerOrganic electronicsMoleculeOrganic chemistryMaterials scienceSupramolecular chemistryTransistorPhysical chemistry

Abstract

fetched live from OpenAlex

Although tetrathiafulvalene (TTF) and its derivatives have been extensively studied as important organic electronic materials over the past half century, tetrathiafulvalene vinyl-ogues (TTFVs) still remain a relatively underdeveloped branch in the family of TTF derivatives. Our recent work has investigated the synthesis and characterization of a class of diphenyl-substituted TTFVs carrying alkynyl functionality. The unique conformational and redox properties of such TTFV derivatives along with the versatile chemistry enabled by acetylenic groups (e.g., metal-catalyzed coupling and click reactions) have led us to a variety of functional molecular architectures ranging from oligoynes, polymers, and molecular tweezers, to macrocycles. Property studies of these new TTFV-based molecular materials point to appealing applications in molecular electronics and optoelectronics.

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 score0.002
Threshold uncertainty score0.006

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.015
GPT teacher head0.257
Teacher spread0.242 · 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

Citations47
Published2012
Admission routes2
Has abstractyes

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