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Record W4388225050 · doi:10.1002/app.54852

Charge transfer of 1,3,4‐oxadiazole derivative, its functional polymers and study of their different aggregation‐induced emission enhancement behaviors

2023· article· en· W4388225050 on OpenAlexaff
Juan Liu, Jingjing Xi, Mei Xiao, Lingyun Xu, Youhao Zhang, Linhan Nie, Tingting Mao, Zifan Lu, Huiying Zha, Xuke Zhou

Bibliographic record

VenueJournal of Applied Polymer Science · 2023
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence and Fluorescent Materials
Canadian institutionsCanadian General-Tower (Canada)
Fundersnot available
KeywordsPhotochemistryCarbazoleFluorescenceOxadiazolePolymerPolystyrenePolymerizationAtom-transfer radical-polymerizationDelocalized electronQuenching (fluorescence)Materials scienceChemistryPolymer chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract In this study, a symmetrical D‐π‐A‐π‐D initiator ViOXD, based on substituted amino donor (D) and 1,3,4‐oxadiazole acceptor (A), with rigid stilbene π‐bridge was synthesized. The photophysical investigation of ViOXD in solution and aggregate state showed its solvatochromic and aggregation‐caused quenching characteristics, because of its strong charge transfer and the formation of H‐aggregates, respectively. The introduction of peripheral polystyrene or carbazole‐containing PVPCz chains via atom transfer radical polymerization not only recovered the fluorescence of the ViOXD core, but also tuned its maximum emission wavelength in aggregate state, due to the stronger electron‐donating ability and better conjugation of PVPCz chains than polystyrene chains. On the other hand, the large conjugation length and symmetrical charge transfer from the ends to the cores of ViOXD facilitated the electronic delocalization and bestowed the end‐functionalized polymers with good fluorescence in aggregate state, which we have applied in cellular imaging by preparation of their fluorescent nanoparticles.

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 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 score0.017
Threshold uncertainty score0.511

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.027
GPT teacher head0.262
Teacher spread0.234 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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