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Record W2734610877 · doi:10.1021/acs.joc.7b01333

Predictably Ordered Open Hydrogen-Bonded Networks Built from Indeno[1,2-<i>b</i>]fluorenes

2017· article· en· W2734610877 on OpenAlexafffund
Daniel Beaudoin, Joao-Nicolas Blair-Pereira, Sophie Langis‐Barsetti, Thierry Maris, James D. Wuest

Bibliographic record

VenueThe Journal of Organic Chemistry · 2017
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence and Fluorescent Materials
Canadian institutionsUniversité de Montréal
FundersUniversité de MontréalNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for Innovation
KeywordsCruciformFluoreneChemistryModular designConjugated systemMoleculeRational designHydrogen bondLuminescenceCombinatorial chemistryTopology (electrical circuits)NanotechnologyPolymerOrganic chemistryOptoelectronicsMaterials scienceComputer science

Abstract

fetched live from OpenAlex

Predictably ordered materials can be constructed by a modular strategy in which properly designed molecular components are positioned in space by reliable interactions. In principle, this approach can be used to control the arrangement of adjacent systems of π-conjugation, thereby creating molecular materials with valuable optoelectronic properties. To explore this possibility, we have synthesized compounds in which 2,4-diamino-1,3,5-triazinyl groups are attached to derivatives of 6,12-dihydroindeno[1,2-b]fluorene to produce molecules with well-defined cruciform topologies, extended π-conjugated aromatic cores, and an ability to form multiple hydrogen bonds. These compounds crystallize to form robust open hydrogen-bonded networks with parallel indenofluorenyl cores, significant volume (64-70%) available for accommodating guests, and characteristic luminescence. Our results will help permit the rational design of complex new molecular materials in which multiple optoelectronically active components are arranged in productive ways.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.006
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0050.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.263
Teacher spread0.244 · 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.

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

Citations15
Published2017
Admission routes2
Has abstractyes

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