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Record W2315756578 · doi:10.1021/la4019794

Plasmon Excitation of Supported Gold Nanoparticles Can Control Molecular Release from Supramolecular Systems

2013· article· en· W2315756578 on OpenAlexafffund
Daniela T. Marquez, Adela I. Carrillo, J. C. Scaiano

Bibliographic record

VenueLangmuir · 2013
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMesoporous silicaPlasmonNanotechnologyMesoporous materialColloidal goldNanoparticleMaterials scienceControlled releaseNaproxenHybrid materialSupramolecular chemistryDrug deliveryPlasmonic nanoparticlesMoleculeChemistryOrganic chemistryCatalysisOptoelectronics

Abstract

fetched live from OpenAlex

Hybrid mesoporous silica materials containing gold nanoparticles (AuNPs) have been investigated as potential molecular delivery systems. The photophysical properties of AuNPs, particularly their plasmon band transitions, have been used to control the rate of the release of naproxen from the pores of mesoporous silica matrices. Two different approaches were employed to incorporate AuNPs into the silica network: that is, grafting (using 3-aminopropyltriethoxisilane) and direct absorption. In this research, the anti-inflamatory drug naproxen serves as a test molecule, showing how localized plasmon heating could be used to modify diffusion kinetics within mesoporous materials. Beyond naproxen release, the methodology developed could be employed to release other drugs, sensors, or active molecules, not just in medicine, but in many other fields where nanotechnology is leading to many innovative applications. The hybrid materials developed show a new simple system to efficiently control the release of active cargo from mesoporous silica matrices.

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 score0.009
Threshold uncertainty score0.959

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)0.0000.001

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 head0.006
GPT teacher head0.197
Teacher spread0.191 · 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

Citations11
Published2013
Admission routes2
Has abstractyes

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