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Record W2168349988 · doi:10.5539/mas.v8n4p8

Random-Texturing of Phosphorus-Doped Layers for Multi-Crystalline Si Solar Cells by Plasmaless Dry Etching

2014· article· en· W2168349988 on OpenAlexvenueno aff
Yoji Saito, Akira Kubota, S. Iwama, Ryosuke Watanabe

Bibliographic record

VenueModern Applied Science · 2014
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceDry etchingCrystalline siliconEtching (microfabrication)DopingSolar cellChemical engineeringOptoelectronicsComposite materialLayer (electronics)

Abstract

fetched live from OpenAlex

We investigated a texturing process for crystalline Si solar cells by dry etching with chlorine trifluoride (ClF3) gas without plasma excitation. Recently our research group demonstrated improved electrical characteristics of single-crystalline Si solar cells textured by dry etching of the phosphorus-doped layers. In this report, we attempted to improve the electrical properties of multi-crystalline Si solar cells by modifying the experimental procedure and optimizing the process conditions. The reflectance of the treated surfaces was around 10% at 600 nm without an anti-reflection film. We demonstrated the characteristics of multi-crystalline solar cells by random-texturing by plasmaless etching. This is the first report to prove the validity of plasmaless dry texturing for multi-crystalline Si solar cells.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.620
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.013
GPT teacher head0.212
Teacher spread0.199 · 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 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

Citations1
Published2014
Admission routes1
Has abstractyes

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