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Record W3094920897 · doi:10.1109/tnano.2020.3036629

Atomic Silicon Quantum Dot: A New Designing Paradigm of an Atomic Logic Circuit

2020· article· en· W3094920897 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 Nanotechnology · 2020
Typearticle
Languageen
FieldComputer Science
TopicQuantum-Dot Cellular Automata
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsXNOR gateLogic gateNAND gateAND-OR-InvertNMOS logicPass transistor logicNOR logicCMOSNAND logicElectronic circuitLogic familyAdderElectronic engineeringResistor–transistor logicComputer scienceLogic synthesisAND gateMaterials scienceTransistorDigital electronicsElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

The recent fabrication progress in logic circuits using atomic-scale silicon dangling bond (DB) makes it a promising candidate for field coupled nanocomputing. Moreover, the use of silicon substrate opens the possibilities to integrate DB circuits with existing infrastructure for the complementary metal-oxide-semiconductors (CMOS) devices. However, this emerging technology is still in its initial stage. This paper presents a T-shape structure to realize logic circuits. In addition, fundamental logic gates, such as, two-input AND, NAND, OR, XOR, and XNOR gates, are reported using the T-shape structure. Besides, a novel three-input majority (Si-DBM3) gate and a three-input XOR (Si-DBX3) gate, based on DB pairs, have been presented. Using the proposed Si-DBX3 and Si-DBM3 logic gates, a Full-adder (FA) is designed. All the logic gates are designed and verified using the SiQAD simulation tool.

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 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 score0.693
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.038
GPT teacher head0.246
Teacher spread0.208 · 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