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Record W2990674573 · doi:10.1038/s41598-019-54481-8

Low-cost photodetector architectures fabricated at room-temperature using nano-engineered silicon wafer and sol-gel TiO2 – based heterostructures

2019· article· en· W2990674573 on OpenAlexafffund
Debika Banerjee, Ivy M. Asuo, A. Pignolet, Sylvain G. Cloutier

Bibliographic record

VenueScientific Reports · 2019
Typearticle
Languageen
FieldEngineering
TopicNanowire Synthesis and Applications
Canadian institutionsInstitut National de la Recherche ScientifiqueÉcole de Technologie Supérieure
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsPhotodetectorMaterials scienceResponsivityPhotodetectionOptoelectronicsHeterojunctionWaferAmorphous solidNanowireNanocrystalline materialSiliconUltravioletNanotechnologyTitanium dioxideComposite materialChemistry

Abstract

fetched live from OpenAlex

Abstract In the last decades, significant research has been done on the nanocrystalline forms of titanium dioxide (TiO 2 ). Amorphous TiO 2 has not been studied intensively despite being significantly less expensive compared to crystalline TiO 2 . This study reveals significant improvement in UV-VIS photodetection properties from heterostructures fabricated in ambient environment using n-type silicon nanowire arrays and amorphous TiO 2 sol-gel. Our ultra-low-cost UV-VIS photodetectors can cover a wide range of applications. We report fast rise/decay time constants of 0.23 ms/0.17 ms and high responsivity up-to 6.0 A/W in the UV and 25.0 A/W in the visible range under low (1 V) external bias. The large surface area due to the nanowire array architecture leads to 2 orders of magnitude enhancement in photo-response. Besides the final electrode deposition, the entire device fabrication is performed using low-cost, all solution-based methods in ambient conditions. These low-cost UV-Visible broadband photodetectors can potentially serve a wide range of 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 score0.008
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 head0.007
GPT teacher head0.201
Teacher spread0.194 · 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

Citations16
Published2019
Admission routes2
Has abstractyes

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