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Record W2036364974 · doi:10.1002/cjce.20669

Multilayer thin films of colloidal gold and silica nanoparticles: Effect of polyelectrolyte coating

2011· article· en· W2036364974 on OpenAlexvenueaboutno aff
Zaheer Khan, Rachana Kumar, Joydeep Dutta

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2011
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsnot available
FundersNational Nanotechnology Center
KeywordsMaterials scienceNanoparticleThin filmColloidal goldPolyelectrolyteColloidCoatingSurface plasmon resonanceAbsorption (acoustics)PlasmonRefractive indexAbsorption spectroscopyNanotechnologyVisible spectrumUltravioletChemical engineeringOptoelectronicsOpticsComposite material

Abstract

fetched live from OpenAlex

Abstract The use of oppositely charged colloidal nanoparticles to build multilayered structures is an approach in thin film science. In this work, uniform spherical nano‐dispersions of gold (ca. 20 nm) and silica (ca. 30 nm) were synthesised with specific volume concentration to achieve colloidal stability. Exploiting the use of self‐assembly, multilayers of these oppositely charged nanoparticles were built using alternate coating with chitosan. Gold nanoparticles have strong optical absorption in visible region of electromagnetic spectrum resulting from its surface plasmon resonance. Silica nanoparticles have low refractive index and absorb light mostly in the ultraviolet (UV) region. The optical absorption band of the fabricated thin films extends from UV to visible region of the electromagnetic spectrum. The spectral characteristics of these thin‐film assemblies are a combination of thickness and the order of the layers in a stack. These films have potential applications as optical elements and in optoelectronics. © 2011 Canadian Society for Chemical Engineering

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 score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
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 head0.009
GPT teacher head0.187
Teacher spread0.177 · 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
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicGold and Silver Nanoparticles Synthesis and ApplicationsFrench-language works237,207