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Limit Temperature Coefficient in Silicon Solar Cells

2020· article· en· W3120585929 on OpenAlexaff
Anatoliy Sachenko, V. P. Kostylyov, I.O. Sokolovskyi, Behnam Arzhang, Mykhaylo Evstigneev

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSilicon and Solar Cell Technologies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsAbsorptanceTemperature coefficientSiliconReflection coefficientMaterials scienceOpticsSolar cellEquivalent series resistanceDopingOptoelectronicsTheory of solar cellsSolar cell efficiencyReflectivityComposite materialPhysics

Abstract

fetched live from OpenAlex

The photoconversion efficiency and its temperature coefficient of silicon solar cells are investigated within the thin-base model with Lambertian light trapping. Fresnel reflection of the trapped photons from the front surface is accounted for in the absorptance expression. In the absence of extrinsic recombination mechanisms and parasitic resistance effects, the maximal efficiency under the AM1.5G illumination conditions at 25 ° C is 29.99% at the thickness 63.3 μm, with the temperature coefficient of 0.23% /K. Calculations performed for real solar cells revealed that the extrinsic recombination mechanisms, doping, and series resistance result in an increase of the temperature coefficient, whereas shunt resistance results in its reduction relative to the value obtained for an ideal solar cell.

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 score0.064
Threshold uncertainty score0.385

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 head0.011
GPT teacher head0.184
Teacher spread0.173 · 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
Published2020
Admission routes1
Has abstractyes

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