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Record W3024884537 · doi:10.1021/acs.jpclett.0c01166

Multiple Self-Trapped Emissions in the Lead-Free Halide Cs<sub>3</sub>Cu<sub>2</sub>I<sub>5</sub>

2020· article· en· W3024884537 on OpenAlexafffund
Haijie Chen, João M. Pina, Fanglong Yuan, Andrew Johnston, Dongxin Ma, Bin Chen, Ziliang Li, Antoine Dumont, Xiyan Li, Yanan Liu, Sjoerd Hoogland, Zoltán Zajacz, Zheng‐Hong Lu, Edward H. Sargent

Bibliographic record

VenueThe Journal of Physical Chemistry Letters · 2020
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsUniversity of Toronto
FundersOffice of ScienceSamsungNatural Sciences and Engineering Research Council of CanadaOak Ridge National LaboratorySamsung Advanced Institute of TechnologyU.S. Department of Energy
KeywordsHalideLead (geology)Materials scienceEnvironmental scienceChemistryInorganic chemistryGeology

Abstract

fetched live from OpenAlex

Low-dimensional copper halides with high luminance have attracted increasing interest as heavy-metal-free light emitters. However, the optical mechanisms underpinning their excellent luminescence remain underexplored. Here, we report multiple self-trapped emissions in Cs 3 Cu 2 I 5 . Power-dependent photoluminescence spectra reveal the appearance of multiple self-trapped emission peaks with increasing excitation power, and this emission behavior is explored across a temperature range of 80–420 K. The zero-dimensional structure and soft crystal lattice contribute to the multiple self-trapped emissions in Cs 3 Cu 2 I 5: this explains the origin of the broad emission and the luminescence mechanism in Cs 3 Cu 2 I 5 and will assist in improving our understanding of the optical properties of other metal halides. We incorporate the Cs 3 Cu 2 I 5 in light-emitting diodes that achieve a peak luminance of 140 cd/m 2 and an external quantum efficiency of 0.27%.

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 head0.010
GPT teacher head0.201
Teacher spread0.192 · 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

Citations123
Published2020
Admission routes2
Has abstractyes

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