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Record W2323490048 · doi:10.1021/ph500208q

Light Management in Upconverting Nanoparticles: Ultrasmall Core/Shell Architectures to Tune the Emission Color

2014· article· en· W2323490048 on OpenAlexafffund
Marta Quintanilla, Fuqiang Ren, Dongling Ma, Fiorenzo Vetrone

Bibliographic record

VenueACS Photonics · 2014
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence Properties of Advanced Materials
Canadian institutionsInstitut National de la Recherche Scientifique
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaIndustry Canada
KeywordsNanoparticleMaterials scienceLuminescenceLanthanideDopantShell (structure)IonEmission intensityExcitationDopingNanotechnologyCore (optical fiber)OptoelectronicsChemistryComposite materialPhysics

Abstract

fetched live from OpenAlex

Ultrasmall NaGdF 4 nanoparticles with core/shell and core/shell/shell architectures have been synthesized following a microwave-based thermolysis procedure, allowing us to rapidly obtain homogeneous nanoparticles compared to conventional heating. To analyze the possibilities of the proposed structure in terms of tuning the emission color, core and shells have been doped with different lanthanide ion pairs (either Er 3+ /Yb 3+ and/or Tm 3+ /Yb 3+ ), keeping them therefore spatially separated inside the different layers of the nanoparticles. Here, we demonstrate that the position of the dopants inside the nanoparticles affects the intensity of the different emission bands of the luminescing Tm 3+ and Er 3+ ions and show how it has a relevant effect on the overall emission color of the luminescence obtained after 975 nm excitation.

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 score0.011
Threshold uncertainty score0.588

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 science0.0010.000
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 head0.014
GPT teacher head0.248
Teacher spread0.234 · 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

Citations72
Published2014
Admission routes2
Has abstractyes

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