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Effect of Varying Threshold Voltage on Efficiency of CMOS Rectifiers for Piezoelectric Energy Harvesting Applications

2020· article· en· W3107681255 on OpenAlexafffund
Xingwen Li, Edward S. Rogers, Seyedfakhreddin Nabavi, Lihong Zhang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicInnovative Energy Harvesting Technologies
Canadian institutionsMemorial University of NewfoundlandUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaResearch and Development Corporation of Newfoundland and LabradorCanada Foundation for Innovation
KeywordsRectifier (neural networks)CMOSThreshold voltageVoltageMOSFETEnergy harvestingElectrical engineeringCapacitorMaterials scienceElectronic engineeringEngineeringEnergy (signal processing)Computer scienceTransistorPhysics

Abstract

fetched live from OpenAlex

In this paper, the efficiency of a conventional cross-coupled gate CMOS bridge rectifier used in MEMS (microelectromechanical system) piezoelectric energy harvesters is investigated. The MOSFET threshold voltage is varied between 10 mV and 800 mV to evaluate the performance of the circuit for various threshold voltage levels. The circuit is simulated using the 130 nm CMOS technology process for each MOSFET to generate performance metrics for the rectifier. The results are evaluated for optimal load resistance, and it is confirmed that a lower threshold voltage results in significant improvements to the efficiency of the rectifier at lower input voltage amplitudes, with up to 62% at 0.5 V input amplitude when a smoothing capacitor is placed across the load.

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)0.001
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 score0.891
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.234
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; 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

Citations3
Published2020
Admission routes2
Has abstractyes

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