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Record W4288038269 · doi:10.3390/electronics11152320

Ultra-Low-Cost Design of Ripple Carry Adder to Design Nanoelectronics in QCA Nanotechnology

2022· article· en· W4288038269 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.

Bibliographic record

VenueElectronics · 2022
Typearticle
Languageen
FieldComputer Science
TopicQuantum-Dot Cellular Automata
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsAdderElectronic engineeringQuantum dot cellular automatonElectronic circuitComputer scienceNanoelectronicsLogic gateInverterDigital electronicsEngineeringElectrical engineeringCMOSNanotechnologyMaterials science

Abstract

fetched live from OpenAlex

Due to the development of integrated circuits and the lack of responsiveness to existing technology, researchers are looking for an alternative technology. Quantum-dot cellular automata (QCA) technology is one of the promising alternatives due to its higher switch speed, lower power dissipation, and higher device density. One of the most important and widely used circuits in digital logic calculations is the full adder (FA) circuit, which actually creates the problem of finding its optimal design and increasing performance. In this paper, we designed and implemented two new FA circuits in QCA technology and then implemented ripple carry adder (RCA) circuits. The proposed FAs and RCAs showed excellent performance in terms of QCA evaluation parameters, especially in cost and cost function, compared to the other reported designs. The proposed adders’ approach was 46.43% more efficient than the best-known design, and the reason for this superiority was due to the coplanar form, without crossovers and inverter gates in the designs.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.929
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.001
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 head0.228
Teacher spread0.213 · 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