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Record W2130646162 · doi:10.1039/c0jm03494k

Colloidal approach to Au-loaded TiO2 thin films with optimized optical sensing properties

2011· article· en· W2130646162 on OpenAlexaff
Enrico Della Gaspera, Alessandro Antonello, M. Guglielmi, Michael L. Post, Valentina Bello, G. Mattei, Filippo Romanato, Alessandro Martucci

Bibliographic record

VenueJournal of Materials Chemistry · 2011
Typearticle
Languageen
FieldEngineering
TopicGas Sensing Nanomaterials and Sensors
Canadian institutionsNational Research Council Canada
FundersRoyal Society of ChemistryRoyal SocietyFondazione Cassa di Risparmio di Padova e Rovigo
KeywordsMaterials scienceMicrostructureNanocompositePorosityNanoparticleThin filmColloidEllipsometryChemical engineeringOxideCharacterization (materials science)PlasmonNanotechnologyComposite materialOptoelectronicsMetallurgy

Abstract

fetched live from OpenAlex

TiO2 and Au nanoparticles are synthesized by the colloidal technique and used for nanocomposite thin film preparation. The effect of thermal treatment and organic template presence is analyzed in order to tailor film microstructure. The Au-TiO2 interfaces as well as the overall porosity of the films are analyzed combining structural and morphological characterization along with spectroscopic ellipsometry and surface plasmon spectroscopy analyses. An efficient surrounding of TiO2 nanoparticles around Au colloids is obtained, leading to an extensive noble metal–metal oxide interface, improving functional properties of the films, while keeping a porous structure. Gas sensing tests are performed on these nanocomposites films: reversible sensing dynamics for CO detection are observed with high sensitivity and a correlation between response and recovery times and microstructure is reported.

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 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 score0.076
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.022
GPT teacher head0.178
Teacher spread0.156 · 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

Citations41
Published2011
Admission routes1
Has abstractyes

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