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Record W1496317172 · doi:10.1109/iscas.2004.1329265

A novel fast low voltage dynamic threshold true single phase clocking adiabatic circuit

2004· article· en· W1496317172 on OpenAlexafffund
Mu Yang, J.A. Barby

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicLow-power high-performance VLSI design
Canadian institutionsUniversity of Waterloo
FundersNational Taiwan UniversityUniversity of WaterlooCMC Microsystems
KeywordsAdiabatic circuitElectronic circuitLogic gateAdiabatic processCMOSElectronic engineeringInverterElectrical engineeringComputer sciencePass transistor logicVoltagePhysicsDigital electronicsEngineering

Abstract

fetched live from OpenAlex

A novel fast true single phase clocking (TSPC) adiabatic differential logic circuit using dynamic threshold (DTMOS) is proposed (DT-TSPC-A). It is capable of operating at 0.7 V. The performance of four circuit architectures (DT-TSPC-A, conventional static CMOS logic, and two other published adiabatic circuits) is compared using a four inverter chain as the test circuit. At 50 MHz and 0.8 V with 20 fF load, this circuit consumes the least amount of energy of the four circuit architectures compared. It takes about the same area and consumes 55% less energy than the static circuit. It has the shortest delay and is 56% faster than other adiabatic circuits and takes at most 2.3 times the area. In addition results for more complex circuits are supplied demonstrating the improved performance of DT-TSPC-A circuits.

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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.216
Teacher spread0.202 · 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

Citations5
Published2004
Admission routes2
Has abstractyes

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