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Record W4255625108 · doi:10.22215/etd/2013-09972

Electrostatic Discharge Protection for a 10 GHz Low Noise Amplifier

2013· dissertation· en· W4255625108 on OpenAlexaff
Wilson Machado

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicElectrostatic Discharge in Electronics
Canadian institutionsCarleton University
Fundersnot available
KeywordsElectrostatic dischargeElectrical engineeringHuman-body modelAmplifierLow-noise amplifierDiodeInductorEngineeringDegradation (telecommunications)Noise figureRadio frequencyElectronic engineeringCMOSVoltage

Abstract

fetched live from OpenAlex

Electrostatic discharge (ESD) is one of the most important failure mechanisms of integrated circuits (ICs). ESD can damage ICs during manufacture, assembly of the component on the printed circuit boards and use in the field as part of a system. Therefore, an adequate ESD protection is required to improve yield and to reduce field return due to ESD damage, consequently, it is necessary that all ICs are protected against ESD. However, ESD protection can adversely cause degradation of IC performance, particularly on radio frequency (RF) ICs. These types of ICs are the most affected by the introduction of ESD protection, which cause the degradation of RF parameters. As a result, reduction of the RF performance degradation is highly desired and was the focus of this study. Two LNAs, one with ESD protection and another without ESD protection were designed and implemented in 0.13 m RFCMOS technology. The operation frequency of the LNA was 10 GHz. The ESD protection used encompasses PI topology ESD protection, comprising the primary ESD protection diodes, LNA gate inductor, secondary ESD protection diodes, and power clamps. The desired level of ESD protection for the LNA was 2000 V for the Human Body Model (HBM). The study was limited to the verification of the degradation of the S-parameters, noise figure, and ESD protection level at the LNA input.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.569
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.007
GPT teacher head0.226
Teacher spread0.219 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2013
Admission routes1
Has abstractyes

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