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Record W3004746645 · doi:10.1063/1.5128664

Photonic crystal light trapping: Beyond 30% conversion efficiency for silicon photovoltaics

2020· article· en· W3004746645 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

VenueAPL Photonics · 2020
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceOptoelectronicsPhotovoltaicsEnergy conversion efficiencyPhotonic crystalSiliconCrystalline siliconTrappingMonocrystalline siliconSolar cellPlasmonic solar cellPhotovoltaic systemOpticsPhysicsElectrical engineering

Abstract

fetched live from OpenAlex

The power conversion efficiency of single-junction silicon solar cells has increased only by 1.5% despite extensive efforts over the past two decades. The current world-record efficiencies of silicon solar cells, within the 25%–26.7% range, fall well below the thermodynamic limit of 32.3%. We review the recent progress in photonic crystal light-trapping architectures poised to achieve 28%–31% conversion efficiency in flexible 3–20 μm-thick, single-junction crystalline-silicon solar cells. These photonic crystals utilize wave-interference based light-trapping, enabling solar absorption well beyond the Lambertian limit in the 300–1200 nm wavelength range. Using experimentally feasible doping profiles, carrier lifetimes, surface recombination velocities, and established Auger recombination losses, we review considerations leading to the prediction of 31% efficiency in a 15 μm-thick silicon photonic crystal cell with interdigitated back-contacts. This is beyond the conversion efficiency of any single-material photovoltaic device of any thickness.

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)
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 score0.353
Threshold uncertainty score1.000

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 science0.0010.000
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 head0.013
GPT teacher head0.199
Teacher spread0.186 · 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