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Record W2126826038 · doi:10.1142/s1088424615500327

Very fast singlet and triplet energy transfers in a tri-chromophoric porphyrin dyad aided by the truxene platform

2015· article· en· W2126826038 on OpenAlexaff
Adam Langlois, Haijun Xu, Paul‐Ludovic Karsenti, Claude P. Gros, Pierre D. Harvey

Bibliographic record

VenueJournal of Porphyrins and Phthalocyanines · 2015
Typearticle
Languageen
FieldMaterials Science
TopicPorphyrin and Phthalocyanine Chemistry
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsChemistryChromophorePorphyrinSinglet statePhotochemistryAcceptorSonogashira couplingArylEnergy transferPhenanthreneElectron transferAlkylCrystallographyPalladiumChemical physicsAtomic physicsCatalysisOrganic chemistry

Abstract

fetched live from OpenAlex

A trichromophoric dyad composed of an octa-β-alkyl-palladium(II)porphyrin (donor) and two tri-meso-aryl-zinc(II)porphyrins (acceptors) held by a truxene spacer exhibits very fast rates for triplet energy transfers at 77 (kET(T1) = 1.63 × 108s-1) and 298 K (kET(T1) = 3.44 × 108s-1), whereas the corresponding singlet energy transfer rates, kET(S1) = 3.9 × 1010s-1(77 K) and kET(S1) = 6.0 × 1010s-1(298 K), are also considered fast. The interpretation for these results is that the energy transfer processes proceed via a through bond Dexter mechanism (i.e. double electron exchange) supported by comparison with literature data and evidence for a moderate MO coupling between the donor and acceptor chromophores in the frontier MOs.

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 score0.005

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 head0.022
GPT teacher head0.229
Teacher spread0.207 · 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

Citations7
Published2015
Admission routes1
Has abstractyes

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