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Monochromatic Light Trapping in Photonic Power Converters

2022· article· en· W4312353367 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venue2022 IEEE 49th Photovoltaics Specialists Conference (PVSC) · 2022
Typearticle
Languageen
FieldEngineering
Topicsolar cell performance optimization
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMonochromatic colorTrappingOptoelectronicsMaterials sciencePhotonicsAbsorption (acoustics)ConvertersPhotovoltaic systemOpticsPower (physics)PhysicsElectrical engineering

Abstract

fetched live from OpenAlex

Photonic power converters (PPC) are photovoltaic devices that convert monochromatic light into electricity. Recent records with III-V PPC have achieved 68.9% but demand high carrier lifetimes. This report shows that the introduction of light trapping can yield substantially higher efficiencies, as all the incident light is weakly absorbed and thus amenable to absorption enhancement. For PPCs with low carrier lifetimes (i.e., 1–100 ns for moderately-doped GaAs), light trapping yields significant gains by enabling thinning of the material and reduction of recombination. In this report, multiple light trapping designs are compared, including nanostructures, rear diffuse reflectors, and angular selective filters. While some light-trapping designs achieve higher ideal PPC performance, other designs are seen to be more tolerant to dimensional variation in fabricated structures and incident angles.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.668
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.012
GPT teacher head0.200
Teacher spread0.188 · 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