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Record W3124378241 · doi:10.1063/5.0033243

Porous SiC electroluminescence from p–i–n junction and a lateral carrier diffusion model

2021· article· en· W3124378241 on OpenAlexafffund
Salman Bawa, Tingwei Zhang, Liam Dow, Samuel Peter, Adrian Kitai

Bibliographic record

VenueJournal of Applied Physics · 2021
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceElectroluminescenceHomojunctionHeterojunctionOptoelectronicsPhotoluminescenceDiodep–n junctionSilicon carbideDiffusionCarrier lifetimeDiamondWide-bandgap semiconductorPorous siliconLayer (electronics)SiliconSemiconductorNanotechnologyComposite material

Abstract

fetched live from OpenAlex

Electroluminescence of porous silicon carbide is achieved in a forward-biased SiC p–i–n junction. A broad green spectral feature centered at ∼510 nm is shown to arise from porous SiC. A large SiC surface area in the vicinity of the junction is created by diamond cutting followed by an electrochemically enhanced hydrogen fluoride etch that produces a layer of porous SiC. Photoluminescence is shown not to be responsible for the green emission. This supports the model of carrier recombination at the porous region via lateral bipolar diffusion of carriers. A lateral bipolar diffusion model is presented in which mobile carriers diffuse laterally from the junction toward the porous SiC surface region driven by a lateral carrier concentration gradient. Lateral bipolar diffusion in conjunction with suitable radiative recombination centers provides a possible pathway to achieve high quantum efficiencies in future SiC p–n homojunction or double heterojunction light-emitting diodes. Competing recombination processes and associated ideality factors in 4H-SiC diodes are also examined.

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 score0.020
Threshold uncertainty score0.488

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)0.0000.000

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 head0.008
GPT teacher head0.210
Teacher spread0.202 · 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

Citations9
Published2021
Admission routes2
Has abstractyes

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