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Record W2314101965 · doi:10.1149/1.2773984

Methods for the Controlled Reduction of Carrier Lifetime in Power Devices

2007· article· en· W2314101965 on OpenAlexaff
F.‐J. Niedernostheide, Hans‐Joachim Schulze

Bibliographic record

VenueECS Transactions · 2007
Typearticle
Languageen
FieldEngineering
TopicPower Transformer Diagnostics and Insulation
Canadian institutionsInfineon Technologies (Canada)
Fundersnot available
KeywordsDiodeMaterials scienceOptoelectronicsCarrier lifetimeCharge carrierDopingPower (physics)Semiconductor devicePower semiconductor deviceLayer (electronics)NanotechnologySilicon

Abstract

fetched live from OpenAlex

Power devices require a thick lightly doped drift layer to support the required blocking capability. In order to obtain also an optimized on-state and dynamic switching behavior, the shape of excess charge carrier profile in the drift region has to be tailored. Often, and especially for freewheeling diodes, this can only be achieved by a precise adjustment of the carrier lifetime. In this work, we use the free carrier absorption technique to determine the excess charge carrier profile in power diodes. Methods to extract the carrier lifetime from the carrier profile of platinum diffused diodes are demonstrated. The injection level and temperature dependence of the carrier lifetime are determined. The origin of the specific shape of the excess charge carrier profile is analyzed by complementary measurements of the deep level profile by DLTS.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.972
Threshold uncertainty score0.239

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 integrity0.0000.000
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 head0.011
GPT teacher head0.292
Teacher spread0.281 · 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 designSimulation or modeling
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

Citations0
Published2007
Admission routes1
Has abstractyes

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