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Record W2172046262 · doi:10.1109/pvsc.2009.5411483

Amorphous-crystalline silicon interface prepared using DC saddle-field pecvd

2009· article· en· W2172046262 on OpenAlexafffund
Barzin Bahardoust, Alongkarn Chutinan, Thomas W. Blaine, Adel B. Gougam, Keith Leong, Davit Yeghikyan, Tome Kosteski, Nazir P. Kherani, S. Źükotyński

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSilicon and Solar Cell Technologies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPassivationMaterials scienceAnnealing (glass)Carrier lifetimePlasma-enhanced chemical vapor depositionWaferSiliconHeterojunctionField effectAnalytical Chemistry (journal)Electric fieldCrystalline siliconOptoelectronicsAmorphous solidNanotechnologyComposite materialChemistryCrystallography

Abstract

fetched live from OpenAlex

The DC saddle field glow discharge method was used to deposit a-Si:H in order to passivate c-Si surfaces. The process temperature and the thickness of the a-Si:H films were varied. In addition subsequent annealing of the samples were studied. Passivation quality of the a-Si:H overlayers were studied by measuring the effective minority carrier lifetime in the heterostructures as a function of the minority carrier density in the c-Si wafer. These results are then used to model the surface recombination mechanism in our samples. The defect density and the charge density at the interface are inferred which helps us to distinguish between the effects of electric field and chemical passivation at the interface. It is shown that for our intrinsic a-Si:H samples improvements in surface passivation are directly correlated with the reduction of interface defect density and field effect passivation is minimal. We have achieved surface passivation with effective carrier lifetime > 5 ms for a 40 nm intrinsic a-Si:H sample deposited at a process temperature of 200°C. It is also demonstrated that subsequent annealing, at 240°C, of the samples which were prepared at process temperatures < 240°C drastically increases the effective lifetime.

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 score0.196
Threshold uncertainty score0.714

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 head0.016
GPT teacher head0.247
Teacher spread0.230 · 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
Published2009
Admission routes2
Has abstractyes

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