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Record W2029390074 · doi:10.1142/s1088424613501150

Origin of the temperature dependence of the rate of singlet energy transfer in a three-component truxene-bridged dyads

2013· article· en· W2029390074 on OpenAlexafffund
Adam Langlois, Haijun Xu, Bertrand Brizet, Franck Denat, Jean‐Michel Barbe, Claude P. Gros, Pierre D. Harvey

Bibliographic record

VenueJournal of Porphyrins and Phthalocyanines · 2013
Typearticle
Languageen
FieldMaterials Science
TopicPorphyrin and Phthalocyanine Chemistry
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaConseil régional de Bourgogne-Franche-ComtéCentre National de la Recherche ScientifiqueUniversité de BourgogneFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsChemistrySinglet statePorphyrinExcited stateFörster resonance energy transferPhotochemistryEnergy transferChemical physicsCrystallographyAtomic physicsFluorescence

Abstract

fetched live from OpenAlex

We report a truxene-based dyad built upon one donor (tri-meso-phenylzinc(II)porphyrin) and two acceptors (octa-β-alkylporphyrin free base) in which the donor exhibits free rotation around a Ctruxene-Cmesosingle bond at 298 K in fluid solution but not at 77 K in a glass matrix, whereas the acceptors have very limited motion as they are blocked by β-methyl groups. This case is interesting because all the structural and spectroscopic parameters affecting the rate for singlet energy transfer according to a Förster Resonance Energy Transfer are only weakly temperature dependent, leaving only the Dexter mechanism explaining the larger variation in rate of energy transfers with the temperature hence providing a circumstantial evidence for a dual mechanism (Föster and Dexter) in truxene-based dyads (or polyads) in the S1excited states.

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 score0.001
Threshold uncertainty score0.004

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)0.0010.000

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 head0.012
GPT teacher head0.214
Teacher spread0.202 · 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

Citations15
Published2013
Admission routes2
Has abstractyes

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