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Record W1979419578 · doi:10.1149/1.1393266

Effect of Heavy Boron Doping on Oxygen Precipitation in Czochralski Silicon Substrates of Epitaxial Wafers

2000· article· en· W1979419578 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of The Electrochemical Society · 2000
Typearticle
Languageen
FieldEngineering
TopicSilicon and Solar Cell Technologies
Canadian institutionsResearch & Development Corporation
Fundersnot available
KeywordsWaferMaterials scienceNucleationEpitaxyBoronSiliconPrecipitationDopingAnnealing (glass)GetterAnalytical Chemistry (journal)Chemical engineeringChemistryMetallurgyNanotechnologyOptoelectronicsLayer (electronics)

Abstract

fetched live from OpenAlex

The effect of heavy boron doping on oxygen precipitation in Czochralski silicon substrates of epitaxial wafers has been studied with transmission electron microscopy observations and a preferential etching method. Prolonged isothermal annealing between 700 and 1000°C for up to 700 h was performed on p/p+ (5–20 mΩ cm) and p/p− (10 Ω cm) wafers. It was found that, with an increase in boron concentration, the precipitate density increased, and the precipitates could nucleate at a higher temperature. The growth process of platelet precipitates was also investigated and compared with the process in polished p− wafers. It was confirmed that precipitate growth rate in p/p+ wafers was higher than that in p− wafers, and precipitate nucleation in p/p− wafers was delayed compared with p/p+ wafers. The precipitate growth in p/p+ wafers was determined to be reaction‐limited, which differed from the diffusion‐limited growth in p− wafers. © 2000 The Electrochemical Society. All rights reserved.

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.

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 score0.004
Threshold uncertainty score0.331

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 head0.005
GPT teacher head0.219
Teacher spread0.214 · 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