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Record W2964382135 · doi:10.1002/anie.201906976

2D Poly(arylene vinylene) Covalent Organic Frameworks via Aldol Condensation of Trimethyltriazine

2019· article· en· W2964382135 on OpenAlexafffund
Thaksen Jadhav, Yuan Fang, W. J. Patterson, Chenghao Liu, Ehsan Hamzehpoor, Dmitrii F. Perepichka

Bibliographic record

VenueAngewandte Chemie International Edition · 2019
Typearticle
Languageen
FieldMaterials Science
TopicCovalent Organic Framework Applications
Canadian institutionsMcGill University
FundersU.S. ArmyCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsAryleneCovalent bondAldol condensationCondensationMaterials sciencePolymer chemistryAldol reactionChemistryOrganic chemistryPhysicsCatalysisThermodynamics

Abstract

fetched live from OpenAlex

Abstract Designing structural order in electronically active organic solids remains a great challenge in the field of materials chemistry. Now, 2D poly(arylene vinylene)s prepared as highly crystalline covalent organic frameworks (COFs) by base‐catalyzed aldol condensation of trimethyltriazine with aromatic dialdehydes are reported. The synthesized polymers are highly emissive (quantum yield of up to 50 %), as commonly observed in their 1D analogues poly(phenylene vinylene)s. The inherent well‐defined porosity (surface area ca. 1000 m2 g−1, pore diameter ca. 11 Å for the terephthaldehyde derived COF‐1) and 2D structure of these COFs also present a new set of properties and are likely responsible for the emission color, which is sensitive to the environment. COF‐1 is highly hydrophilic and reveals a dramatic macroscopic structural reorganization that has not been previously observed in framework materials.

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 score0.005

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.257
Teacher spread0.246 · 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

Citations217
Published2019
Admission routes2
Has abstractyes

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