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Record W2160388394 · doi:10.1039/c5nr05877e

Selective photochemical synthesis of Ag nanoparticles on position-controlled ZnO nanorods for the enhancement of yellow-green light emission

2015· article· en· W2160388394 on OpenAlexaff
Hyeong‐Ho Park, Xin Zhang, Ahrum Sohn, Dongwook Kim, Joondong Kim, Jin-Won Song, Young Su Choi, Hee Kwan Lee, Sang Hyun Jung, In-Geun Lee, Young-Dae Cho, Hyun-Beom Shin, Ho Kun Sung, Kyung Ho Park, Ho Kwan Kang, Won-Kyu Park, Hyung‐Ho Park

Bibliographic record

VenueNanoscale · 2015
Typearticle
Languageen
FieldMaterials Science
TopicZnO doping and properties
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsNanorodPhotoluminescenceMaterials sciencePhotochemistryNanoparticleNanotechnologyGreen-lightOptoelectronicsVisible spectrumLight emissionChemical engineeringBlue lightChemistry

Abstract

fetched live from OpenAlex

A novel technique for the selective photochemical synthesis of silver (Ag) nanoparticles (NPs) on ZnO nanorod arrays is established by combining ultraviolet-assisted nanoimprint lithography (UV-NIL) for the definition of growth sites, hydrothermal reaction for the position-controlled growth of ZnO nanorods, and photochemical reduction for the decoration of Ag NPs on the ZnO nanorods. During photochemical reduction, the size distribution and loading of Ag NPs on ZnO nanorods can be tuned by varying the UV-irradiation time. The photochemical reduction is hypothesized to facilitate the adsorbed citrate ions on the surface of ZnO, allowing Ag ions to preferentially form Ag NPs on ZnO nanorods. The ratio of visible emission to ultraviolet (UV) emission for the Ag NP-decorated ZnO nanorod arrays, synthesized for 30 min, is 20.5 times that for the ZnO nanorod arrays without Ag NPs. The enhancement of the visible emission is believed to associate with the surface plasmon (SP) effect of Ag NPs. The Ag NP-decorated ZnO nanorod arrays show significant SP-induced enhancement of yellow-green light emission, which could be useful in optoelectronic applications. The technique developed here requires low processing temperatures (120 °C and lower) and no high-vacuum deposition tools, suitable for applications such as flexible electronics.

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)0.001
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 score0.002
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.021
GPT teacher head0.259
Teacher spread0.238 · 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.

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

Citations23
Published2015
Admission routes1
Has abstractyes

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