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Record W2094127172 · doi:10.1109/ecce.2010.5617920

An integrated segmented gate driver with adjustable driving capability

2010· article· en· W2094127172 on OpenAlex
Armin A. Fomani, Wai Tung Ng, Andrew Shorten

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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSilicon Carbide Semiconductor Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGate driverGate equivalentRingingNAND gateLogic gatePower (physics)Node (physics)ConvertersElectrical engineeringCMOSElectronic engineeringComputer scienceEngineeringTransistorVoltageGate oxide

Abstract

fetched live from OpenAlex

The effect of varying the driving strength of the gate driver IC on the efficiency of synchronous buck converters is the focus of this work. To reduce the switching losses in the output stage, gate drivers are often designed to charge and discharge the gate electrodes of the power MOSFETs as fast as possible. However, fast switching requires power hungry gate drivers and the gate driver power consumption could exceed the switching loss at light load. In this work, a segmented gate driver IC with adjustable driving capability is presented. By choosing the appropriate gate driving capability for each particular load condition, it is possible to continuously optimize the overall power conversion efficiency. In a 20W DC-DC converter, regulated at 1.2V, 0-20A output, a 7% efficiency improvements at light load and significant reduction in ringing and overshoot at the switching node is achieved with the proposed 0.25μm CMOS compatible gate driver IC.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.743

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 integrity0.0000.001
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 head0.006
GPT teacher head0.205
Teacher spread0.199 · 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