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Record W3042607910 · doi:10.1038/s43246-020-00054-6

Two-photon photocurrent in InGaN/GaN nanowire intermediate band solar cells

2020· preprint· en· W3042607910 on OpenAlexafffund
Ross Cheriton, Sharif Sadaf, Luc Robichaud, Jacob J. Krich, Zetian Mi, Karin Hinzer

Bibliographic record

VenueCommunications Materials · 2020
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsMcGill UniversityInstitut National de la Recherche ScientifiqueNational Research Council CanadaUniversity of Ottawa
FundersCMC MicrosystemsNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsMcGill University
KeywordsOptoelectronicsPhotocurrentMaterials scienceHeterojunctionNanowireBand gapMultiple exciton generationSolar cellWide-bandgap semiconductorSemiconductorQuantum dot solar cellBiasingQuantum dotSiliconQuantum efficiencyGallium nitridePolymer solar cellNanotechnologyVoltagePhysics

Abstract

fetched live from OpenAlex

Abstract Intermediate band solar cells hold the promise of ultrahigh power conversion efficiencies using a single semiconductor junction. Many current implementations use materials with bandgaps too small to achieve maximum efficiency or use cost-prohibitive substrates. Here we demonstrate a material system for intermediate band solar cells using InGaN/GaN quantum-dot-in-nanowire heterostructures grown directly on silicon to provide a lower cost, large-bandgap intermediate band solar cell platform. We demonstrate sequential two-photon current generation with sub-bandgap photons, the hallmark of intermediate band solar cell operation, through vertically stacked quantum dots in the nanowires. Near-infrared light biasing with an 850 nm laser intensity up to 200 W/cm2 increases the photocurrent above and below the bandgap by up to 19% at 78 K, and 44% at room temperature. The nanostructured III-nitride strategy provides a route towards realistic room temperature intermediate band solar cells while leveraging the cost benefits of silicon substrates.

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 score0.001
Threshold uncertainty score0.003

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 communication0.0000.000
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 head0.042
GPT teacher head0.305
Teacher spread0.263 · 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

Citations1
Published2020
Admission routes2
Has abstractyes

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