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Record W1986484256 · doi:10.1002/chem.200902712

Spontaneous Hierarchical Assembly of Crown Ether‐like Macrocycles into Nanofibers and Microfibers Induced by Alkali‐Metal and Ammonium Salts

2010· article· en· W1986484256 on OpenAlexafffund
Joseph K.‐H. Hui, Peter D. Frischmann, Chien‐Hsin Tso, Carl A. Michal, Mark J. MacLachlan

Bibliographic record

VenueChemistry - A European Journal · 2010
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence and Fluorescent Materials
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCrown etherAlkali metalAmmoniumMicrofiberNanofiberPolymer chemistryMaterials scienceEtherCrown (dentistry)ChemistryChemical engineeringOrganic chemistryNanotechnologyComposite materialIon

Abstract

fetched live from OpenAlex

Schiff base macrocycle 1, which has a crown ether like central pore, was combined with different alkali-metal and ammonium salts in chloroform, resulting in one-dimensional supramolecular aggregates. The ion-induced self-assembly was studied with solid-state NMR spectroscopy, transmission electron microscopy (TEM), scanning electron microscopy (SEM), and atomic force microscopy (AFM). It was found that the lengths and widths of the superstructures depend on the cation and counteranion of the salts. Among the salts being used, Na(+) and NH(4) (+) ions with BF(4) (-) ions showed the most impressive fibrous structures that can grow up to 1 mum in diameter and hundreds of microns in length. In addition, the size of the fibers can be controlled by the evaporation rate of the solvent. A new macrocycle with bulky triptycenyl substituents that prevent supramolecular assembly was prepared and did not display any nanofibers with alkali-metal ions in chloroform when studied with TEM.

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 score0.000
Threshold uncertainty score0.001

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)0.0000.000

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 head0.007
GPT teacher head0.219
Teacher spread0.213 · 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

Citations36
Published2010
Admission routes2
Has abstractyes

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Same venueChemistry - A European JournalSame topicLuminescence and Fluorescent MaterialsFrench-language works237,207