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Record W1982196573 · doi:10.1109/tbcas.2011.2177267

A High-Efficiency Low-Voltage CMOS Rectifier for Harvesting Energy in Implantable Devices

2012· article· en· W1982196573 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Biomedical Circuits and Systems · 2012
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsPolytechnique Montréal
FundersCMC Microsystems
KeywordsRectifier (neural networks)TransconductanceCMOSElectrical engineeringCapacitorTransistorVoltageElectronic engineeringEnergy harvestingPrecision rectifierVoltage multiplierPower semiconductor deviceEngineeringMaterials sciencePower (physics)Computer scienceVoltage sourcePower factorDropout voltagePhysics

Abstract

fetched live from OpenAlex

We present, in this paper, a new full-wave CMOS rectifier dedicated for wirelessly-powered low-voltage biomedical implants. It uses bootstrapped capacitors to reduce the effective threshold voltage of selected MOS switches. It achieves a significant increase in its overall power efficiency and low voltage-drop. Therefore, the rectifier is good for applications with low-voltage power supplies and large load current. The rectifier topology does not require complex circuit design. The highest voltages available in the circuit are used to drive the gates of selected transistors in order to reduce leakage current and to lower their channel on-resistance, while having high transconductance. The proposed rectifier was fabricated using the standard TSMC 0.18 μm CMOS process. When connected to a sinusoidal source of 3.3 V peak amplitude, it allows improving the overall power efficiency by 11% compared to the best recently published results given by a gate cross-coupled-based structure.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.867
Threshold uncertainty score0.869

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 communication0.0000.000
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 head0.017
GPT teacher head0.221
Teacher spread0.204 · 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