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Record W1954672870 · doi:10.1109/pvsc.2002.1190834

Very low surface recombination velocities on p- and n-type silicon wafers passivated with hydrogenated amorphous silicon films

2003· article· en· W1954672870 on OpenAlexfundno aff
Stefan Dauwe, Jan Schmidt, Rudolf Hezel

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsnot available
FundersInstitute of Gender and Health
KeywordsPassivationPlasma-enhanced chemical vapor depositionMaterials scienceSilicon nitrideWaferSiliconAmorphous siliconChemical vapor depositionCarrier lifetimeAmorphous solidNanocrystalline siliconAnalytical Chemistry (journal)Crystalline siliconOptoelectronicsNanotechnologyLayer (electronics)CrystallographyChemistry

Abstract

fetched live from OpenAlex

Outstanding surface passivation of single-crystalline p- as well as n-type silicon is obtained using hydrogenated amorphous silicon (a-Si:H) films deposited at very low temperature in a plasma-enhanced chemical vapor deposition (PECVD) system. It is demonstrated that a-Si:H films with excellent surface passivation properties can be deposited in the temperature range between 200 and 250/spl deg/C. Despite the low deposition temperature, the surface passivation of low-resistivity (/spl sim/1 /spl Omega/cm) p-type silicon provided by the films exceeds that provided by high-temperature (/spl sim/1000/spl deg/C) thermal oxides and PECVD silicon nitride films deposited at temperatures around 400/spl deg/C. A record-low surface recombination velocity (SRV) of 3 cm/s is achieved on 1.6-/spl Omega/cm p-Si. In addition, on 3.4-/spl Omega/cm n-Si wafers, very low SRVs of 7 cm/s are obtained. Investigations regarding the thermal stability of the passivation quality of the a-Si:H films show that the passivation is stable for temperatures exceeding the deposition temperature.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.174
Teacher spread0.167 · 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 source (direct Gemma or distilled Codex), 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

Citations87
Published2003
Admission routes1
Has abstractyes

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