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Alternative Highly Homogenous Drift Layer Doping for 650 V SiC Devices

2016· article· en· W2404666705 on OpenAlexaff
Roland Rupp, Werner Schustereder, T. Höchbauer, Ronny Kern, Michael Rüb, Constantin Csato, Florian Krippendorf, Shavkat Akhmadaliev, J. von Borany

Bibliographic record

VenueMaterials science forum · 2016
Typearticle
Languageen
FieldEngineering
TopicSilicon Carbide Semiconductor Technologies
Canadian institutionsInfineon Technologies (Canada)
Fundersnot available
KeywordsMaterials scienceDopingWaferOptoelectronicsIon implantationDiodeSchottky diodeHomogeneity (statistics)IonComputer science

Abstract

fetched live from OpenAlex

A new method for homogenous drift layer doping is introduced. Instead of in-situ doping during epitaxial growth a subsequent high energy ion implant step is used to dope the drift layer of 650V MPS (Merged-PN-Schottky) diodes. In order to avoid multiple implant steps with various energies for emulating a box-like doping profile, a novel “energy filter” membrane is used to transform the monochromatic ion beam to a beam with a continuous energy spectrum suited for box-like doping. The electrical characteristics of the diodes manufactured by this means show a very homogenous blocking behavior on wafer level, however the expected improved homogeneity in differential resistance of the wafers could not be confirmed by wafer level measurements. More work is needed to understand this discrepancy between experiment and theory.

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: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.526

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 communication0.0000.001
Open science0.0010.000
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 head0.021
GPT teacher head0.250
Teacher spread0.229 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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