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Record W2970793051 · doi:10.1109/pn.2019.8819568

Optimizing Bifacial Silicon Heterojunction Solar Cells for High-Latitude

2019· article· en· W2970793051 on OpenAlexaffabout
Erin M. Tonita, Mandy R. Lewis, Christopher E. Valdivia, Karin Hinzer

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSilicon and Solar Cell Technologies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSiliconHeterojunctionMaterials scienceOptoelectronicsSilicon solar cellSolar cellEngineering physicsEnvironmental sciencePhysics

Abstract

fetched live from OpenAlex

Bifacial silicon heterojunction solar cells are modelled via 2D optoelectronic simulations in Synopsys TCAD Sentaurus to optimize and characterize cell performance in regions of high latitude with high average air mass and increased angles of incidence. Device structure, such as amorphous silicon layer thickness and doping, is being optimized for bifacial illumination conditions representative of the Canadian High Arctic, with independent spectra illuminating the front and rear faces of the cell. The present cell structure has an efficiency of 20.3% under front-face illumination with AM1.5G. Cell performance will be optimized via improvements in the antireflection coating, surface texturing, doping, and layer thicknesses.

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 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 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 score0.056
Threshold uncertainty score0.484

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 science0.0000.000
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 head0.009
GPT teacher head0.196
Teacher spread0.187 · 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 teacher head, 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

Citations2
Published2019
Admission routes2
Has abstractyes

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