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Record W2794255118 · doi:10.1002/anie.201800175

Highly Efficient Artificial Light‐Harvesting Systems Constructed in Aqueous Solution Based on Supramolecular Self‐Assembly

2018· article· en· W2794255118 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAngewandte Chemie International Edition · 2018
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence and Fluorescent Materials
Canadian institutionsMinistry of Education and Child Care
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of ChinaAlexander von Humboldt-StiftungNational Science Foundation
KeywordsSupramolecular chemistryAqueous solutionArtificial lightSelf-assemblyComputer scienceNanotechnologyBiological systemArtificial intelligenceMaterials scienceChemistryBiologyPhysicsOrganic chemistryOpticsMolecule

Abstract

fetched live from OpenAlex

Highly efficient light-harvesting systems were successfully fabricated in aqueous solution based on the supramolecular self-assembly of a water-soluble pillar[6]arene (WP6), a salicylaldehyde azine derivative (G), and two different fluorescence dyes, Nile Red (NiR) or Eosin Y (ESY). The WP6-G supramolecular assembly exhibits remarkably improved aggregation-induced emission enhancement and acts as a donor for the artificial light-harvesting system, and NiR or ESY, which are loaded within the WP6-G assembly, act as acceptors. An efficient energy-transfer process takes place from the WP6-G assembly not only to NiR but also to ESY for these two different systems. Furthermore, both of the WP6-G-NiR and WP6-G-ESY systems show an ultrahigh antenna effect at a high donor/acceptor ratio.

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.

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 score0.019
Threshold uncertainty score0.788

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 studies0.0000.000
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 head0.013
GPT teacher head0.246
Teacher spread0.232 · 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