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Record W2807857473 · doi:10.1063/1.5023430

Integrated tandem device with photoactive layer for near-infrared to visible upconversion imaging

2018· article· en· W2807857473 on OpenAlexafffund
Shou‐Jie He, Dengke Wang, Zhenxin Yang, Jiaxiu Man, Zheng‐Hong Lu

Bibliographic record

VenueApplied Physics Letters · 2018
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsUniversity of Toronto
FundersYunnan UniversityNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsPhoton upconversionTandemOptoelectronicsOLEDMaterials scienceInfraredPhotonDiodePhotoactive layerEnergy conversion efficiencyOpticsLayer (electronics)NanotechnologyLuminescencePolymer solar cellPhysics

Abstract

fetched live from OpenAlex

An efficient organic near-infrared (NIR) to visible upconversion imaging device is obtained by integrating a photoactive buffer layer between two organic light-emitting diodes in a tandem configuration. As both types of photo-carriers (electrons and holes) are harvested to generate visible photons, this tandem device exhibits a significantly higher On/Off switching and has higher photon-photon conversion efficiency than conventional upconversion devices. We show that a high 5% photon-photon conversion rate is possible by optimizing the various functional layers in the tandem structure. We also demonstrate that a pixel-less NIR imaging chip can be made simply by using a large area single tandem organic upconversion device.

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 score0.002
Threshold uncertainty score0.007

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.219
Teacher spread0.209 · 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

Citations30
Published2018
Admission routes2
Has abstractyes

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