MétaCan
Menu
Back to cohort
Record W2642313695

Atomic Silicon Quantum Dot Wires and Logic Gates For Binary Computation

2017· article· en· W2642313695 on OpenAlexfundvenueno aff
Taleana Huff, Hatem Labidi, Mohammad Rashidi, Roshan Achal, Lucian Livadaru, Thomas Dienel, Jason Pitters, Robert A. Wolkow

Bibliographic record

VenueNPARC · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSurface and Thin Film Phenomena
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates - Technology Futures
KeywordsDangling bondSiliconQuantum dotBinary numberSubstrate (aquarium)Materials scienceNanotechnologyElectronOptoelectronicsPhysicsQuantum mechanics
DOInot available

Abstract

fetched live from OpenAlex

Nanoelectronics has long striven for the ultimate limit of fabrication: reliable use of single atoms as building blocks for computational components. This has required years of development in tools not only to manipulate single atoms with sub-angstrom precision, but also tools that can read the sensitive outputs and dynamics. Here, we report the first example of reversible information transmission through an atomic silicon quantum dot fabricated binary wire and OR gate. We used an atomic force microscope operating in the non-contact regime (NC-AFM) to fabricate, read the output, and actuate both the wire and gate into different readable states. These changes are clearly seen in both raw AFM images, and in kelvin probe force microscopy (KPFM) spectroscopy taken above the silicon quantum dots. This sets the platform for a potential new class of ultra-fast, ultra-power efficient, and ultra dense computing.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.026
GPT teacher head0.283
Teacher spread0.256 · 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

Citations0
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueNPARCSame topicSurface and Thin Film PhenomenaFrench-language works237,207