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Record W2000441222 · doi:10.1149/1.2128099

2D Dopant Determination in Laser-Diffused Si Resistors Using Dopant-Selective Etching

2005· article· en· W2000441222 on OpenAlexafffund
Yuanfeng Liao, Jean-Yves Degorce, Jon Belisle, Michel Meunier

Bibliographic record

VenueJournal of The Electrochemical Society · 2005
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaPolytechnique Montréal
KeywordsDopantMaterials scienceEtching (microfabrication)Isotropic etchingOptoelectronicsSiliconAnalytical Chemistry (journal)ResistorTransmission electron microscopyDopingChemistryNanotechnologyElectrical engineeringChromatography

Abstract

fetched live from OpenAlex

Two-dimensional (2D) dopant profiles, in the range of to , in laser-diffused silicon resistors were obtained using dopant selective etching (DSE) in combination with cross-sectional transmission electron microscopy (TEM) and focused ion beam technique. Compared with conventional DSE/TEM dopant evaluation, the properties of this technique, related to the reliability, reproducibility, and accuracy of quantification of dopant concentration from to , have been improved by considering a vector instead of a scalar etching rate, as determined by an etching model and by a novel calibration method. Those evaluated profiles were accurately compared with a numerical simulation based on heat-transfer and diffusion equations.

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 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 score0.418

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 science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.251
Teacher spread0.241 · 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.

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

Citations7
Published2005
Admission routes2
Has abstractyes

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