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Record W4408902677 · doi:10.1021/jacs.5c02096

Molecular Design Principles for Photoactive Transition Metal Complexes: A Guide for “Photo-Motivated” Chemists

2025· review· en· W4408902677 on OpenAlexaff
Giacomo Morselli, Christian Reber, Oliver S. Wenger

Bibliographic record

VenueJournal of the American Chemical Society · 2025
Typereview
Languageen
FieldEngineering
TopicOrganic Light-Emitting Diodes Research
Canadian institutionsUniversité de Montréal
FundersUniversität Basel
KeywordsChemistryTransition metalNanotechnologyOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide Luminescence and photochemistry involve electronically excited states that are inherently unstable and therefore spontaneously decay to electronic ground states, in most cases by nonradiative energy release that generates heat. This energy dissipation can occur on a time scale of 100 fs (∼10 –13 s) and usually needs to be slowed down to at least the nanosecond (∼10 –9 s) time scale for luminescence and intermolecular photochemistry to occur. This is a challenging task with many different factors to consider. An alternative emerging strategy is to target dissociative excited states that lead to metal–ligand bond homolysis on the subnanosecond time scale to access synthetically useful radicals. Based on a thorough review at the most recent advances in the field, this article aims to provide a concise guide to obtaining luminescent and photochemically useful coordination compounds with d-block elements. We hope to encourage “photo-motivated” chemists who have been reluctant to apply their synthetic and other knowledge to photophysics and photochemistry, and we intend to stimulate new approaches to the synthetic control of excited state behavior.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0020.001
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.007

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 head0.039
GPT teacher head0.328
Teacher spread0.289 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations65
Published2025
Admission routes1
Has abstractyes

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