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Record W2317213298 · doi:10.1149/1.2355752

Hydrogen-Related Donor Formation: Fabrication Techniques, Characterization, and Application to High-voltage Superjunction Transistors

2006· article· en· W2317213298 on OpenAlexaff
Hans‐Joachim Schulze, M. Buzzo, F.‐J. Niedernostheide, Michael Rueb, Holger Schulze, R. Job

Bibliographic record

VenueECS Transactions · 2006
Typearticle
Languageen
FieldEngineering
TopicSilicon Carbide Semiconductor Technologies
Canadian institutionsInfineon Technologies (Canada)
Fundersnot available
KeywordsMaterials scienceDopingOptoelectronicsHydrogenDopantAnnealing (glass)CapacitanceInertBipolar junction transistorInert gasTransistorFabricationAnalytical Chemistry (journal)VoltageElectrodeElectrical engineeringChemistryMetallurgy

Abstract

fetched live from OpenAlex

Hydrogen-induced doping can be used to create n-doped layers and columns in semiconductor devices. We investigated two techniques to form n-type layers and columns: Proton implantation followed by an annealing step in an inert atmosphere, and helium implantation followed by a hydrogen- plasma treatment. Spreading-resistance measurements and capacitance-voltage measurements were applied to analyze the doping distribution along the implantation direction. Scanning capacitance microscopy and light microscope images after selective etching were used for two-dimensional dopant profiling. Finally, we showed that hydrogen-related donor formation can be successfully applied to create high-voltage superjunction transistors.

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)0.000
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: none
Teacher disagreement score0.524
Threshold uncertainty score0.854

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.004
GPT teacher head0.176
Teacher spread0.172 · 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

Citations5
Published2006
Admission routes1
Has abstractyes

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