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Record W4412491882 · doi:10.1021/acs.nanolett.5c01829

Current Crowding in a High-Efficiency Black Phosphorus Light-Emitting Diode Using a Reflective Back Contact

2025· article· en· W4412491882 on OpenAlexafffund
Julien Brodeur, Éloïse Rahier, Mathieu Chartray-Pronovost, Étienne Robert, Oussama Moutanabbir, Stéphane Kéna‐Cohen

Bibliographic record

VenueNano Letters · 2025
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for Innovation
KeywordsCurrent crowdingHeterojunctionOptoelectronicsMaterials scienceDiodeQuantum tunnellingQuantum efficiencyDopingSaturation currentCurrent densityLight-emitting diodeVoltagePhysics

Abstract

fetched live from OpenAlex

We demonstrate a high-performance mid-infrared (MIR) light-emitting diode (LED) based on a black phosphorus (b-P)/n-MoS 2 heterojunction. A gold back contact combined with a rhenium-doped n-type MoS 2 layer is used to enhance light extraction. The device shows a MIR peak external quantum efficiency (EQE) of (1.6 ± 0.2)% at room temperature and a record (7.0 ± 0.5)% EQE at 77 K, with a maximum radiant power density of (108 ± 8) W/cm 2 . Finite-element simulations highlight the importance of phonon-assisted band-to-band tunneling under reverse bias and the influence of carrier velocity saturation under forward bias. The simulations also reveal that the high ideality factors extracted from the current–voltage characteristic are due to current crowding at the heterojunction and a consequence of the device geometry. These findings establish a new high-performance b-P LED architecture and provide crucial insights into the physics of MIR sources based on 2D materials.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.769

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.296
Teacher spread0.278 · 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 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

Citations2
Published2025
Admission routes2
Has abstractyes

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