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Record W4409482299 · doi:10.1364/oe.558023

Pressure-induced white light emission based on a single-component organic molecule

2025· article· en· W4409482299 on OpenAlexaff
Jianhui Han, Bifa Cao, H. Yin, Jianbo Gao, Cailong Liu, Ying Shi

Bibliographic record

VenueOptics Express · 2025
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence and Fluorescent Materials
Canadian institutionsBrock University
FundersNational Natural Science Foundation of ChinaNatural Science Foundation of Jilin Province
KeywordsWhite lightOpticsComponent (thermodynamics)Materials scienceMoleculePhysics

Abstract

fetched live from OpenAlex

White light-emitting diodes hold great significance in the realm of lighting technology, as they possess the potential to considerably reduce energy consumption and mitigate greenhouse gas emissions. Nonetheless, transitioning individual organic molecules from emitting no white light to bright white-light remains an arduous task. In this paper, we present a straightforward and highly efficient approach known as compression, which successfully induces the transition from dark to radiant white luminescence. Unexpectedly, we have discovered that the molecule transformed from exhibiting no white light emission under ambient pressure to emitting brilliant white light with Commission Internationale de I'Éclairage coordinates of (0.31, 0.32) at 0.8 GPa. Furthermore, the intensity of the emitted light increased by more than tenfold. By employing steady-state absorption and fluorescence, transient-state spectra measurements, and density functional theory simulation, we elucidated that the distinct responses of luminescence to pressure can be attributed to the effective manipulation of molecular structure. Our work represents the pioneering utilization of compression as a robust tool in the fabrication of white light and the optimization of luminescent properties using a simple-component organic molecule.

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 score0.004

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 head0.014
GPT teacher head0.239
Teacher spread0.226 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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