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Record W3097177843 · doi:10.1021/acsomega.0c03764

Probing Electronic Communication and Excited-State Dynamics in the Unprecedented Ferrocene-Containing Zinc MB-DIPY

2020· article· en· W3097177843 on OpenAlexafffundabout
Yuriy V. Zatsikha, Liliya I. Shamova, Jacob W. Schaffner, Andrew T. Healy, Tanner S. Blesener, Gabriel Cohen, Brandon Wozniak, David A. Blank, Victor N. Nemykin

Bibliographic record

VenueACS Omega · 2020
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence and Fluorescent Materials
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaMinnesota Supercomputing Institute, University of MinnesotaCanada Foundation for InnovationWestern Canada Research GridDivision of Materials ResearchUniversity of Manitoba
KeywordsFerroceneExcited statePhotochemistryChemistryZincElectron transferBODIPYSinglet stateGround stateQuenching (fluorescence)ElectrochemistryMaterials scienceAtomic physicsFluorescencePhysical chemistryElectrodePhysicsOpticsOrganic chemistry

Abstract

fetched live from OpenAlex

The electronic communication between two ferrocene groups in the electron-deficient expanded aza-BODIPY analogue of zinc manitoba-dipyrromethene (MB-DIPY) was probed by spectroscopic, electrochemical, spectroelectrochemical, and theoretical methods. The excited-state dynamics involved sub-ps formation of the charge-separated state in the organometallic zinc MB-DIPYs, followed by recovery of the ground state via charge recombination in 12 ps. The excited-state behavior was contrasted with that observed in the parent complex that lacked the ferrocene electron donors and has a much longer excited-state lifetime (670 ps for the singlet state). Much longer decay times observed for the parent complex without ferrocene confirm that the main quenching mechanism in the ferrocene-containing 4 is reflective of the ultrafast ferrocene-to-MB-DIPY core charge transfer (CT).

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)0.001
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 score0.198
Threshold uncertainty score0.455

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 science0.0010.000
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 head0.018
GPT teacher head0.247
Teacher spread0.229 · 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.

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

Citations17
Published2020
Admission routes3
Has abstractyes

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