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Record W4406469767 · doi:10.1002/lpor.202401590

Superbly Bright Tin‐Based Perovskite LEDs

2025· article· en· W4406469767 on OpenAlexaff
Zeyu Miao, Jie Guo, Dan Jiang, Weijia Zheng, Wenxu Yin, Zhao Luo, Xinyan Zhou, Zhou Jiang, Wei Zhang, Xiuyun Zhang, Cong Chen, Xingliang Dai, Qingfeng Dong, Xuyong Yang, Ning Wang, Tom Wu, Xiaoyu Zhang, Jiaqi Zhang

Bibliographic record

VenueLaser & Photonics Review · 2025
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsUniversity of Victoria
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsLight-emitting diodeTinPerovskite (structure)Materials scienceOptoelectronicsBusinessMetallurgyChemistryCrystallography

Abstract

fetched live from OpenAlex

Abstract Tin (Sn)‐based perovskites have made notable advances with external quantum efficiency of over 20%, but still exhibit low electroluminescence brightness insufficient for outdoor displays. Here, it is demonstrated that compact phenethylammonium tin iodide (PEA 2 SnI 4 ) films with an intact crystal structure can offer high luminance by optimizing the perovskite crystallization rate simultaneously with engineering the grain surface. Ammonium thiocyanate is added to the precursor solution to generate the film with PEA 2 SnI x SCN 4‐ x and NH 4 I after spin‐coating. Sn 2+ and SCN − have a strong interaction that slows crystallization to improve PEA 2 SnI 4 crystal quality. During the subsequent annealing, I − from NH 4 I replaces SCN − in PEA 2 SnI x SCN 4‐ x by forming thiourea, which can escape from the film to leave intact PEA 2 SnI 4 crystals. It is found that the optimized PEA 2 SnI 4 emitting layers can provide outstanding film coverage, high crystallinity, low trap state density, and superior photophysical performance. Consequently, an impressive brightness of 8285 cd m −2 for pure red electroluminescence is achieved, the first report of Sn‐based perovskite light‐emitting diodes that meet outdoor display requirements.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.353
Threshold uncertainty score0.838

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 studies0.0000.000
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 head0.005
GPT teacher head0.236
Teacher spread0.231 · 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 designNot applicable
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

Citations9
Published2025
Admission routes1
Has abstractyes

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