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Record W2966317366 · doi:10.1002/chem.201903138

Aromatic Embrace Motifs for Bulk Supramolecular Polymers

2019· article· en· W2966317366 on OpenAlexafffund
Nicholas Lanigan, Abdeljalil Assoud, Wei Zhang, Xiaosong Wang

Bibliographic record

VenueChemistry - A European Journal · 2019
Typearticle
Languageen
FieldChemistry
TopicSupramolecular Chemistry and Complexes
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSupramolecular chemistryPolymerCyclopentadienyl complexAmorphous solidCrystallizationGlass transitionMaterials scienceMelting temperatureMoleculePolymerizationStructural motifCrystallographyCrystal structurePolymer chemistryChemistryChemical physicsOrganic chemistryComposite materialCatalysis

Abstract

fetched live from OpenAlex

Abstract Frequently encountered in crystalline materials, aromatic embraces (AEs) are formed when arylated molecules interact through multiple concerted aromatic interactions. AEs are a robust motif that is suitable for the preparation of amorphous bulk supramolecular polymers (BSPs). Crystal engineering revealed that the polymorphic compound (PPh 3 )(Cp)Fe(CO){CO(CH 2 ) 5 CH 3 } (Cp=cyclopentadienyl), known as FpC 6 , assembled into various chain structures through several AE motifs. Upon melting, FpC 6 always adopted the same AE motif, which extended into the corresponding embracing “ladder” chains. The resultant BSP displayed typical polymer behaviour, including the presence of a glass transition and viscoelasticity, which allowed the effect of thermal history on the polymerisation behaviour to be explored. The ladder chains formed by the AE remain assembled at temperatures of up to 130 °C and were able to effectively suppress crystallisation during cooling. The ability of the AE to form chains at high temperatures and suppress crystallisation is a new opportunity to advance the field of BSPs and supramolecular chemistry.

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 categoriesMeta-epidemiology (narrow), Insufficient 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 score0.081
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.009
GPT teacher head0.208
Teacher spread0.199 · 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

Citations5
Published2019
Admission routes2
Has abstractyes

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