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The Role of Spectrum in Encapsulated Bifacial Silicon Heterojunction Solar Cell Carrier Loss

2021· article· en· W3196722664 on OpenAlexaff
Erin M. Tonita, Christopher E. Valdivia, Mariana I. Bertoni, Karin Hinzer

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSilicon and Solar Cell Technologies
Canadian institutionsUniversity of Ottawa
FundersOffice of Energy EfficiencyNational Science Foundation
KeywordsMaterials scienceOptoelectronicsHeterojunctionSolar cellSiliconPolymer solar cellPhotovoltaic systemEnergy conversion efficiencyCarrier lifetimeWavelengthElectrical engineering

Abstract

fetched live from OpenAlex

The effect of encapsulant on solar cell performance is widely understood to decrease overall cell power output due to absorption in encapsulating layers. In this work, we quantify the effect of encapsulation across the solar spectrum for high-efficiency bifacial silicon heterojunction solar cells in Synopsys TCAD Sentaurus to determine whether encapsulation causes a significant deviation in current loss trends compared to bare cells. Bare and encapsulated cells are modelled between 300-1200 nm and for air masses (AMs) between 1 and 10.0. Comparing current densities relative to bare cells for front illumination, encapsulation results in a 4.3% increase in parasitic absorption under AM1 illumination, and a 3.9% increase at AM10 as a consequence of the red-shift under higher AM. Despite spectral effects influencing current loss, trends of efficiency with AM are the same for bare and encapsulated cells, peaking around AM5. Encapsulated efficiency is decreased by 1.40 ± 0.02 % abs. compared to bare cells between AM1-10. Thus, while carrier transport is influenced by encapsulation in a wavelength-dependent manner, the overall effect on cell efficiency is a uniform offset for all spectra considered.

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 score0.025
Threshold uncertainty score0.292

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 head0.004
GPT teacher head0.173
Teacher spread0.169 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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