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Record W2888905441 · doi:10.1002/adma.201801996

Perovskites for Light Emission

2018· review· en· W2888905441 on OpenAlexaff
Li Na Quan, F. Pelayo Garcı́a de Arquer, Randy P. Sabatini, Edward H. Sargent

Bibliographic record

VenueAdvanced Materials · 2018
Typereview
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials sciencePerovskite (structure)HalideLight emissionBrightnessOptoelectronicsCompatibility (geochemistry)Nanoscopic scaleNanotechnologyBand gapOpticsChemical engineeringInorganic chemistry

Abstract

fetched live from OpenAlex

Next-generation displays require efficient light sources that combine high brightness, color purity, stability, compatibility with flexible substrates, and transparency. Metal halide perovskites are a promising platform for these applications, especially in light of their excellent charge transport and bandgap tunability. Low-dimensional perovskites, which possess perovskite domains spatially confined at the nanoscale, have further extended the degree of tunability and functionality of this materials platform. Herein, the advances in perovskite materials for light-emission applications are reviewed. Connections among materials properties, photophysical and electrooptic spectroscopic properties, and device performance are established. It is discussed how incompletely solved problems in these materials can be tackled, including the need for increased stability, efficient blue emission, and efficient infrared emission. In conclusion, an outlook on the technologies that can be realized using this material platform is presented.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.006

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 head0.026
GPT teacher head0.318
Teacher spread0.291 · 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 designNot applicable
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

Citations600
Published2018
Admission routes1
Has abstractyes

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