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Record W2544752294 · doi:10.1109/icm.2007.4497723

A novel fully-integrated dropless voltage CMOS rectifier for wirelessly powered devices

2007· article· en· W2544752294 on OpenAlexafffund
Saeid Hashemi, Mohamad Sawan, Yvon Savaria

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCMC Microsystems
KeywordsRectifier (neural networks)CMOSTransconductanceElectrical engineeringTransistorVoltageElectronic engineeringPower semiconductor deviceEngineeringVoltage dropComputer science

Abstract

fetched live from OpenAlex

We present in this paper a new topology of a full-wave passive rectifier. It uses MOS transistors as low-loss switches to achieve significant increase in its overall power efficiency and negligible voltage drop across them. The highest voltages available in the circuit are used to drive the gate of a transistor in order to reduce the leakages and to lower the channel resistance while having high transconductance. It is implemented using standard TSMC 0.18 um CMOS process and is characterized by SpectreS simulator under the Cadence environment. The proposed full-wave rectifier is targeted for wirelessly powered applications such as neural stimulators. In the nominal source amplitude it allows improving the power efficiency by 10% and average output voltage by 16% comparing with other published results.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.013
GPT teacher head0.229
Teacher spread0.216 · 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 source (direct Gemma or distilled Codex), 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

Citations13
Published2007
Admission routes2
Has abstractyes

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