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Record W2110624352 · doi:10.1109/pvsc.2014.6924885

Effects of luminescent coupling in single- and 4-junction dilute nitride solar cells

2014· article· en· W2110624352 on OpenAlexaff
Matthew M. Wilkins, Ahmed M. Gabr, Anna H. Trojnar, Henry Schriemer, Karin Hinzer

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
Topicsolar cell performance optimization
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsLuminescenceCoupling (piping)PlanarOptoelectronicsOrganic solar cellMaterials scienceTopology (electrical circuits)Analytical Chemistry (journal)PhysicsChemistryElectrical engineeringComputer sciencePolymerOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

A novel method for incorporating the effects of luminescent coupling and photon recycling in numerical simulations of planar devices is described. The carrier generation is incorporated directly in the device simulator as an additional term in the continuity equation, so that no additional iterations are required. The method is applied to single- and four-junction solar cells containing ~1.0 eV dilute nitride material. We find that luminescent coupling increases the short-circuit current (JSC) of the 1-junction dilute nitride cell by 2.4% due to coupling with the Al0.05Ga0.95As filter. In the 4-junction design, there is significant photon recycling within the GaAs and GaInP sub-cells, providing a 60 mV increase in open-circuit voltage. There is a 1.9% relative increase in calculated efficiency to 44.4%.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.003
GPT teacher head0.151
Teacher spread0.148 · 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

Citations13
Published2014
Admission routes1
Has abstractyes

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