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Record W620625916

Low temperature p+ nc-Si:H window layers for large area thin-film solar cells

2007· dissertation· en· W620625916 on OpenAlexfundno aff
Wing Fai Lydia Tse

Bibliographic record

VenueSummit (Simon Fraser University) · 2007
Typedissertation
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaBritish Columbia Knowledge Development FundSimon Fraser University
KeywordsMaterials scienceThin filmPlasma-enhanced chemical vapor depositionSolar cellChemical vapor depositionAmorphous solidSubstrate (aquarium)Amorphous siliconSiliconNanocrystalline materialNanocrystalline siliconLayer (electronics)FabricationOptoelectronicsDopingNanotechnologyChemical engineeringAnalytical Chemistry (journal)Crystalline siliconChemistryCrystallography
DOInot available

Abstract

fetched live from OpenAlex

Hydrogenated nanocrystalline silicon (nc-Si:H) has attracted attention recently over amorphous silicon (a-Si:H) for use in thin-film solar cell applications primarily due to its higher stability and light absorbing capacity. In addition, there is increasing interest in device fabrication on low-cost, light weight and flexible substrates where optimizing deposition conditions of nc-Si:H thin films at low substrate temperatures (< 200 °C) poses challenges. In such solar cells, the thin boron-doped (p+) window layer significantly determines crystalline growth of the overlying intrinsic absorber layer, quality of which eventually governs device performance. In this research, material properties of thin p+ nc-Si:H films (50 – 300 nm) were investigated. Samples were deposited using plasma enhanced chemical vapor deposition (PECVD) at low temperatures (75 or 150 °C) with various RF power and/or pressure conditions. Results from characterization experiments and feasibility of incorporating such low-temperature thin p+ nc-Si:H films as solar cell window layers are discussed.

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 categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.002
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 head0.007
GPT teacher head0.197
Teacher spread0.190 · 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.

Study designNot applicable
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
Published2007
Admission routes1
Has abstractyes

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