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Record W2131468059 · doi:10.1063/1.4931663

Memory operation devices based on light-illumination ambipolar carbon-nanotube thin-film-transistors

2015· article· en· W2131468059 on OpenAlexafffund
Brahim Aïssa, Mourad Nedil, Jens Kroeger, Thomas Haddad, Federico Rosei

Bibliographic record

VenueJournal of Applied Physics · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced Memory and Neural Computing
Canadian institutionsMcGill UniversityUniversité du Québec en Abitibi-TémiscamingueRaymor (Canada)Université TÉLUQInstitut National de la Recherche Scientifique
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaQatar Foundation
KeywordsAmbipolar diffusionMaterials scienceOptoelectronicsTransistorCarbon nanotubeThin-film transistorTrappingNanotechnologyThin filmNon-volatile memoryNanotubeField-effect transistorElectronElectrical engineeringVoltagePhysics

Abstract

fetched live from OpenAlex

We report the memory operation behavior of a light illumination ambipolar single-walled carbon nanotube thin film field-effect transistors devices. In addition to the high electronic-performance, such an on/off transistor-switching ratio of 104 and an on-conductance of 18 μS, these memory devices have shown a high retention time of both hole and electron-trapping modes, reaching 2.8 × 104 s at room temperature. The memory characteristics confirm that light illumination and electrical field can act as an independent programming/erasing operation method. This could be a fundamental step toward achieving high performance and stable operating nanoelectronic memory devices.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.222
Teacher spread0.207 · 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

Citations3
Published2015
Admission routes2
Has abstractyes

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