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Designing High-Efficiency Thin Silicon Solar Cells Using Parabolic-Pore Photonic Crystals

2018· article· en· W2795542312 on OpenAlexaff
Sayak Bhattacharya, Sajeev John

Bibliographic record

VenuePhysical Review Applied · 2018
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsUniversity of Toronto
FundersBasic Energy SciencesU.S. Department of Energy
KeywordsMaterials scienceOptoelectronicsSiliconPhotovoltaicsEnergy conversion efficiencyPlasmonic solar cellSolar cellPhotovoltaic systemQuantum dot solar cellThin filmPhotonicsPolymer solar cellNanotechnologyElectrical engineering

Abstract

fetched live from OpenAlex

A flexible thin-film silicon solar cell with power conversion efficiency approaching 30% would be a game-changer for the photovoltaics industry. This dream has been considered unattainable, though, due to Si's indirect band gap. Also, silicon solar cells are typically thick, inflexible, and limited in efficiency by nonradiative charge-carrier losses in the large bulk volume of the cell. This research demonstrates how light trapping based on wave interference in photonic crystals could raise conversion efficiency to ~28%, over a large wavelength range of 300---1100 nm. This would set a new record for silicon-based photovoltaic technology.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.285
Teacher spread0.266 · 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 designSimulation or modeling
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

Citations36
Published2018
Admission routes1
Has abstractyes

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