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Record W2916045127 · doi:10.1063/1.5091111

Quantum dots with split enhancement gate tunnel barrier control

2019· article· en· W2916045127 on OpenAlexafffund
Sophie Rochette, M. S. Rudolph, Anindita Roy, Matthew Curry, Gregory A. Ten Eyck, Ronald P. Manginell, J. R. Wendt, Tammy Pluym, Stephen M Carr, Daniel R. Ward, Michael Lilly, Malcolm S. Carroll, Michel Pioro-Ladrière

Bibliographic record

VenueApplied Physics Letters · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum and electron transport phenomena
Canadian institutionsCanadian Institute for Advanced ResearchUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaCanada First Research Excellence FundCanada Foundation for InnovationU.S. Department of Energy
KeywordsQuantum dotOptoelectronicsMaterials scienceSiliconQuantum dot laserGate dielectricGate oxideSemiconductorVoltageElectrical engineeringTransistorEngineeringSemiconductor laser theory

Abstract

fetched live from OpenAlex

We introduce a silicon metal-oxide-semiconductor quantum dot architecture based on a single polysilicon gate stack. The elementary structure consists of two enhancement gates separated spatially by a gap, one gate forming a reservoir and the other a quantum dot. We demonstrate that, in three devices based on two different versions of this elementary structure, a wide range of tunnel rates is attainable while maintaining single-electron occupation. A characteristic change in the slope of the charge transitions as a function of the reservoir gate voltage, attributed to screening from charges in the reservoir, is observed in all devices and is expected to play a role in the sizable tuning orthogonality of the split enhancement gate structure. The all-silicon process is expected to minimize strain gradients from electrode thermal mismatch, while the single gate layer should avoid issues related to overlayers (e.g., additional dielectric charge noise) and help improve the yield. Finally, reservoir gate control of the tunnel barrier has implications for initialization, manipulation, and readout schemes in multi-quantum dot architectures.

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 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), Insufficient payload (model declined to judge)
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 score0.237
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.004
GPT teacher head0.181
Teacher spread0.177 · 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 teacher head, not a consensus.

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

Citations22
Published2019
Admission routes2
Has abstractyes

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