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A Wide-range Reconfigurable Deadtime and Delay Element for Optimal-Power Conversion

2021· article· en· W3176543434 on OpenAlexaff
Mousa Karimi, Mohamed R. Ali, Ahmad Hassan, Mohamad Sawan, Benoit Gosselin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsPolytechnique MontréalUniversité Laval
Fundersnot available
KeywordsPower (physics)ConvertersCMOSElectronic engineeringDead timeElectrical engineeringCapacitive sensingComputer scienceVoltageElectronic circuitSchmitt triggerRange (aeronautics)EngineeringPhysics

Abstract

fetched live from OpenAlex

A reconfigurable dead-time circuit intended for optimum power-converters' operation is presented. The circuit provides a programmable delay element to produce a wide range of dead-time delays for different power conversion's applications with various loads and input voltages. The circuit utilises two tunable Schmitt triggers, two reconfigurable capacitive banks, and two adjustable-current sources. The post-layout simulation results show that the circuit can produce a wide range of dead-time delays, from 12.8 ns to 952.24 ns, between the control signals of the high and low sides of a power converter. The power consumption of the presented circuit ranges between 323.1 and 89.69 μW, pendant on the selected delay. The presented circuit is implemented in a 0.35-μm AMS CMOS technology where occupies an area of 150 μm×260 μm.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.870
Threshold uncertainty score1.000

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)0.0010.000

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 head0.008
GPT teacher head0.208
Teacher spread0.200 · 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.

Study designNot applicable
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

Citations4
Published2021
Admission routes1
Has abstractyes

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