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Record W4309187721 · doi:10.1088/2632-959x/aca2c8

Broadband nanoplasmonic photodetector fabricated in ambient condition

2022· article· en· W4309187721 on OpenAlexaff
Debika Banerjee, Ivy M. Asuo, François-Xavier Fortier, A. Pignolet, Sylvain G. Cloutier

Bibliographic record

VenueNano Express · 2022
Typearticle
Languageen
FieldEngineering
TopicNanowire Synthesis and Applications
Canadian institutionsInstitut National de la Recherche ScientifiqueÉcole de Technologie Supérieure
Fundersnot available
KeywordsPhotodetectorPhotodetectionResponsivityMaterials scienceOptoelectronicsNanophotonicsPlasmonHeterojunctionNanowireAbsorption (acoustics)FabricationSurface plasmonOpticsPhysics

Abstract

fetched live from OpenAlex

Abstract Surface plasmon are widely used to promote the exciton generation and light absorption in solar cells and photodetectors. In this work, a feasible approach for UV–vis-NIR photodetection using plasmon-enhanced silicon nanowires (SiNWs) and amorphous TiO2 heterostructure is presented. The photodetector shows excellent photo response up to 3.3 orders of magnitude enhancement with rise/decay times of 77/51 μs. Under small external bias (1V), the photodetector exhibits very high responsivity up to 49 A W−1 over a broadband wavelength range from 300–1100 nm. All the experimental procedures are performed at room temperature in ambient conditions. Its simple fabrication route and excellent performance make this photodetector distinct from similar architectures. Our finding offers new opportunities to engineer plasmon-based nanostructures in chemical sensors, optoelectronics and nanophotonic devices and 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 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 integrity0.0010.001
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 head0.007
GPT teacher head0.205
Teacher spread0.198 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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