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Record W2316524902 · doi:10.1021/ic200200j

Charge Transfer and Intraligand Excited State Interactions in Platinum-Sensitized Dithienylethenes

2011· article· en· W2316524902 on OpenAlexaff
Matthew N. Roberts, Jeffrey K. Nagle, Marek B. Majewski, Jeremy Finden, Neil R. Branda, Michael O. Wolf

Bibliographic record

VenueInorganic Chemistry · 2011
Typearticle
Languageen
FieldMaterials Science
TopicPhotochromic and Fluorescence Chemistry
Canadian institutionsSimon Fraser UniversityUniversity of British Columbia
Fundersnot available
KeywordsChemistryIntramolecular forceExcited statePhotochemistryTerpyridinePhosphorescencePhotochromismPlatinumMetalFluorescenceStereochemistryCatalysisAtomic physicsOrganic chemistry

Abstract

fetched live from OpenAlex

The photophysical behavior for two photochromic Pt-terpyridine acetylide complexes containing pendant dithienylethenes (DTEs) bound to the metal through the alkynyl linkage is presented. Selective excitation of the Pt complex with visible light resulted in the metal-sensitized ring closing of the DTE unit. The central purpose of this study was to understand how excited state interactions govern the photophysics by correlating differences in the linkage of the two components with differences in the intramolecular energy transfer processes that occur between the Pt complex and the DTE. A series of model complexes without photochromic ligands were prepared and studied to elucidate the contributions of the triplet metal-to-ligand charge transfer and triplet intraligand states. It is demonstrated that reducing the orbital overlap of the metal-based and intraligand states by lengthening the linkage and eliminating a conjugated pathway is effective at dramatically decreasing the efficiency of intramolecular energy transfer. This is evidenced by the appearance of Pt-terpyridine based phosphorescence and a significant decrease in the observed rate of metal-sensitized ring closing of the DTE.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.003
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

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)0.0030.000

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 head0.020
GPT teacher head0.224
Teacher spread0.204 · 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

Citations43
Published2011
Admission routes1
Has abstractyes

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