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Record W4404799579 · doi:10.1002/asia.202401325

Computational Investigation of Meso‐Substituted, Heavy Atom‐Free BODIPY Derivatives as Photosensitizers: Insights From TDDFT and Dynamics Studies

2024· article· en· W4404799579 on OpenAlexfundno aff
Moumita Banerjee, Anakuthil Anoop

Bibliographic record

VenueChemistry - An Asian Journal · 2024
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence and Fluorescent Materials
Canadian institutionsnot available
FundersNova Scotia Museum
KeywordsIntersystem crossingBODIPYTime-dependent density functional theorySinglet oxygenDensity functional theoryChemical physicsExcited statePhotochemistrySinglet statePhotodynamic therapyChemistryComputational chemistryAtom (system on chip)Quantum yieldRational designPopulationFluorescenceNanotechnologyMaterials scienceAtomic physicsPhysicsComputer scienceOxygenQuantum mechanicsOrganic chemistry

Abstract

fetched live from OpenAlex

This study investigates the structural and electronic properties of BODIPY (BDP) derivatives featuring meso-substituted donors arranged orthogonally, leveraging Time-Dependent Density Functional Theory (TD-DFT). These deriva-tives, selected based on experimental evidence of their quantum yield towards singlet oxygen generation, exhibit intricate excited-state dynamics, transitioning from fluorescence to intersystem crossing (ISC), thereby presenting a promising avenue for applications in photodynamic therapy. Emphasizing heavy-atom-free organic triplet photosensitizers, with BDP dyes highlighted for their exceptional adaptability in photophysical characteristics, our analysis contributes to a deeper understanding of the fundamental design principles governing such photosensitizers. Through a combined approach of static and dynamic calculations, we elucidate the mechanisms underlying the population transfer from singlet to triplet states, thereby providing valuable insights for the development of efficient photodynamic therapy agents.

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 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 score0.032
Threshold uncertainty score0.707

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 studies0.0000.001
Scholarly communication0.0000.001
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 head0.019
GPT teacher head0.272
Teacher spread0.253 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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