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Record W1770697966 · doi:10.1038/srep15313

Highly Crystalline CVD-grown Multilayer MoSe2 Thin Film Transistor for Fast Photodetector

2015· article· en· W1770697966 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

VenueScientific Reports · 2015
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaNational Research Foundation of KoreaKorea Institute of Science and TechnologyNational Research Foundation
KeywordsMaterials scienceChemical vapor depositionOptoelectronicsThin-film transistorAmbipolar diffusionPhotodetectorTungsten diselenideThin filmEpitaxyTorrTransistorNanotechnologyElectronChemistryCatalysis

Abstract

fetched live from OpenAlex

Hexagonal molybdenum diselenide (MoSe2) multilayers were grown by chemical vapor deposition (CVD). A relatively high pressure (>760 Torr) was used during the CVD growth to achieve multilayers by creating multiple nuclei based on the two-dimensional crystal growth model. Our CVD-grown multilayer MoSe2 thin-film transistors (TFTs) show p-type-dominant ambipolar behaviors, which are attributed to the formation of Se vacancies generated at the decomposition temperature (650 °C) after the CVD growth for 10 min. Our MoSe2 TFT with a reasonably high field-effect mobility (10 cm(2)/V · s) exhibits a high photoresponsivity (93.7 A/W) and a fast photoresponse time (τ(rise) ~ 0.4 s) under the illumination of light, which demonstrates the practical feasibility of multilayer MoSe2 TFTs for photodetector 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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.167
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.031
GPT teacher head0.265
Teacher spread0.234 · 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