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Spatially Resolved Defect Analysis in Cz-Silicon after Copper-Nickel Co-Precipitation by Virtue of Light-Beam-Induced Current Measurements

2009· article· en· W2013085060 on OpenAlexfundno aff
Philipp Saring, C. Rudolf, L. Stolze, A. Falkenberg, M. Seibt

Bibliographic record

VenueDiffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomena · 2009
Typearticle
Languageen
FieldEngineering
TopicSilicon and Solar Cell Technologies
Canadian institutionsnot available
FundersInstitute of Gender and Health
KeywordsMaterials scienceCopperPrecipitationWaferNickelNucleationSiliconTransmission electron microscopyMetallurgySilicideAnalytical Chemistry (journal)OptoelectronicsNanotechnology

Abstract

fetched live from OpenAlex

We report on a light-beam-induced current (LBIC)-analysis of metal silicide defects arising from co-precipitation of copper and nickel in Cz-silicon-bicrystals produced by wafer direct bonding. Large colonies of silicide precipitates in the one wafer emerging from undisturbed growth from few nucleation sites were observed in different orientations with respect to the surface which correspond to Si {110} planes. From this, the colonies formed during copper-nickel co-precipitation reveal the same attributes as those colonies typical for copper precipitation in the absence of nickel. Oxygen related defects associated with a higher defect distribution in the other wafer were characterized by means of high resolution Transmission Electron Microscopy (TEM) and their temperature dependent LBIC signal.

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 score0.002
Threshold uncertainty score0.004

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 head0.040
GPT teacher head0.300
Teacher spread0.260 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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Same venueDiffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomenaSame topicSilicon and Solar Cell TechnologiesFrench-language works237,207