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Record W3043148371 · doi:10.1021/acsanm.0c01544

Impact of Incoherent Coupling within Localized Surface Plasmon Resonance on Singlet Oxygen Production in Rose Bengal-Modified Silica-Coated Silver Nanoshells (SiO<sub>2</sub>@Ag@SiO<sub>2</sub>-RB)

2020· article· en· W3043148371 on OpenAlexafffund
Vladimir Kabanov, Belinda Heyne

Bibliographic record

VenueACS Applied Nano Materials · 2020
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaAlberta InnovatesCanada Foundation for InnovationUniversity of Calgary
KeywordsNanoshellSurface plasmon resonanceMaterials scienceSinglet oxygenPlasmonNanotechnologyNanomaterialsPhotosensitizerNanoparticleNanostructurePhotodynamic therapyOptoelectronicsPhotochemistryChemistryOxygen

Abstract

fetched live from OpenAlex

The use of metal-containing nanoparticles capable of localized surface plasmon resonance (LSPR)-enhanced singlet oxygen (1O2) production, via photosensitization, are currently promising candidates for cytotoxic medical purposes. Despite the ongoing advances in fabricating plasmonic nanomaterials, much of the insight into the fundamental mechanisms governing the photosensitizer (PS)–plasmon interactions remain unexplored. Silver nanoshells (SiO2@Ag) possess seemingly promising optical properties to investigate the underlying LSPR effects on photosensitization, while also raising questions about the nature of LSPR generation in such dielectric-core metallic-shell nanostructures. In the present study, we synthesize and use silica-coated hybrid SiO2@Ag nanoparticles with an outer surface-conjugated PS, and Ag shell densities ranging from ∼50 to >90%, to experimentally investigate these nanostructures’ LSPR-enhanced 1O2 generation properties. Using both direct and indirect 1O2 detection approaches, and with rigorous consideration of 1O2 kinetics, we show that the SiO2@Ag-based structures produce severe inner filter effects in bulk-solution measurements, making them impractical for photodynamic applications. Furthermore, we make a case for the SiO2@Ag nanoparticles’ poor LSPR generation efficiency to be the consequence of the species’ incoherently coupled plasmonic field and resultant lack of enhancement of the nearby chromophore’s photophysical properties.

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 categoriesMeta-epidemiology (narrow)
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 score0.018
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.243
Teacher spread0.220 · 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.

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

Citations12
Published2020
Admission routes2
Has abstractyes

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