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Record W2111978884 · doi:10.1002/chem.201406143

Ratiometric Fluorescent Nanosensors for Copper(II) Based on Bis(rhodamine)‐Derived PMOs with J‐Type Aggregates

2015· article· en· W2111978884 on OpenAlexaff
Xiaoyong Qiu, Shuhua Han, Yongfeng Hu, Baowen Sun

Bibliographic record

VenueChemistry - A European Journal · 2015
Typearticle
Languageen
FieldChemistry
TopicMolecular Sensors and Ion Detection
Canadian institutionsCanadian Light Source (Canada)
FundersNatural Science Foundation of Shandong Province
KeywordsFluorescenceRhodamineQuantum yieldSiloxaneMoietyMetal ions in aqueous solutionCopperPhotochemistryChemistryRhodamine BMetalMaterials scienceStereochemistryPolymerOrganic chemistryPhotocatalysisCatalysis

Abstract

fetched live from OpenAlex

By using pentyl-linked bis(rhodamine)-derived tetra-siloxane (PRh-Si4 ) as the organosilica precursor, highly ordered PRh-bridged periodic mesoporous organosilicas (PRhPMOs) were prepared. When excited at λ=500 nm, the PRhPMO suspension that contained metal ions showed two separate emission peaks at λ=550 and 623 nm. The first peak, located at λ=550 nm, was due to ring-opening of the spiro structure in the rhodamine moiety and the second, located at λ=623 nm, originated from fluorescent aggregates of the PRh units embedded in the silica framework of the PRhPMO. By using the different intensity ratios of the two fluorescence signals (FI550/623), PRhPMOs could be used as turn-ON type fluorescent ratiometric chemosensors for Cu(2+). Furthermore, based on the single-exciton theory, it was deduced that the fluorescent aggregates formed were of the J-type and had a coplanar configuration. Consequently, PRhPMOs display a longer fluorescence lifetime and greater fluorescent quantum yield than the respective monomers dissolved in solution, which is consistent with the experimental results.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.066
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.028
GPT teacher head0.228
Teacher spread0.200 · 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

Citations28
Published2015
Admission routes1
Has abstractyes

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