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Record W4409057856 · doi:10.1109/led.2025.3556348

Nanosheet Transistors Produced in 300 mm Fabrication Platform for Quantum Computing

2025· article· en· W4409057856 on OpenAlexafffund
Claude Rohrbacher, Dominic Leclerc, Joffrey Rivard, R. Ritzenthaler, Christian Lupien, Hans Mertens, Naoto Horiguchi, Eva Dupont-Ferrier

Bibliographic record

VenueIEEE Electron Device Letters · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Semiconductor Devices and Circuit Design
Canadian institutionsUniversité de Sherbrooke
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsNanosheetFabricationTransistorQuantum computerOptoelectronicsMaterials scienceQuantumNanotechnologyComputer scienceElectronic engineeringElectrical engineeringEngineeringPhysicsVoltage

Abstract

fetched live from OpenAlex

We report on the first cryogenic characterization of a nMOS nanosheet transistor down to 1.2 K. We demonstrate that the device operates at low temperatures both in the transistor regime with improved DC characteristics (subthreshold swing) and in the quantum regime with adjustable charge occupation of the quantum dot down to a single electron. We further perform extensive low-frequency charge noise measurements in the quantum dot regime over a broad range of charge occupation numbers and observe low average charge noise of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\left \lt {{ {S}_{{0}}}}\right \gt = {28} \pm {10}\; \mu \textit {eV}/\sqrt {\textit {Hz}}$ </tex-math></inline-formula> at 1 Hz. These results demonstrate that nanosheet transistors are promising for large scale quantum/classical co-integration of CMOS devices for quantum information processing applications.

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)
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 score0.120
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)0.0000.000

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 head0.016
GPT teacher head0.258
Teacher spread0.242 · 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

Citations5
Published2025
Admission routes2
Has abstractyes

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