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Record W2526131355 · doi:10.11159/iccpe16.122

Turn-Off Fluorescence Detector for Cu2+ Ions; GdVO4:Eu Nanoparticles

2016· article· en· W2526131355 on OpenAlexvenueno aff
Hyunsub Kim, Song‐Ho Byeon

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2016
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence Properties of Advanced Materials
Canadian institutionsnot available
Fundersnot available
KeywordsFluorescenceDetectorNanoparticleIonMaterials scienceChemistryNanotechnologyComputer sciencePhysicsOpticsTelecommunications

Abstract

fetched live from OpenAlex

Europium-doped gadolinium orthovanadate (GdVO4:Eu) nanoparticles (NPs), which provide narrow and photobleaching resistant emissions, are currently successfully prepared and are attracting considerable attention for biomedical applications, such as multifunctional bio-probes capable of fluorescent probing as well as magnetic resonance imaging (MRI).[1]However, while extensive investigations for fluorescence imaging, magnetic relaxivity, and cytotoxicity revealed the excellent biocompatibility of GdVO4:Eu NPs, [2] not much attention has been paid to elucidate the effect of transition metal ions that exist in the human body on the fluorescence probe function of GdVO4:Eu NPs.For most biomedical applications of NPs, understanding the possible effects induced by adsorption of biologically important metal ions is an interesting issue because the adsorbed metal ions can affect the function of NPs to limit their sensitivity, performance, stability, and resolution in applications.In this work, GdVO4:Eu NPs were prepared using layered gadolinium hydroxychloride (Gd2(OH)5Cl•nH2O) as a precursor to react with meta-vanadate (VO3ˉ) in aqueous solutions at room temperature.The large quantities of hydroxyl groups remaining on the surface make GdVO4:Eu particles prepared by this route homogeneously dispersible in water without any further surface modification.Despite surface O-H oscillators, the emission from GdVO4:Eu NPs prepared in the present work was sufficiently strong and easily monitored.As the adsorption and true toxic effects of metals arise mainly from metal ions, rather than elemental metals or their stable organic/inorganic complexes, [3] the adsorption of metal ions on the GdVO4:Eu particles was performed in aqueous MgCl2, CaCl2, FeCl2, CuCl2, ZnCl2, CdCl2, PbCl2, and AlCl3 solutions at room temperature.Interestingly, plots of the excitation and emission intensities of the GdVO4:Eu NPs showed quite different quenching behaviors depending on the type of adsorbed metal ion.Compared to essentially no influence of the Mg 2+ , Ca 2+ , Fe 2+ , Zn 2+ , Cd 2+ , Pb 2+ , and Al 3+ ion adsorptions, significant quenching of the GdVO4:Eu emission was achieved within 3 min with the adsorption of Cu 2+ .We attributed this difference to the absorption of the emitted light by adsorbed Cu 2+ ions through the so-called 'inner filter effect'.Because such a filter effect can effectively occur only if the absorption band of the metal ion is complementarily overlapped with the emission bands of GdVO4:Eu, highly selective and sensitive fluorescence quenching could be achieved by the Cu 2+ ion adsorption.As a consequence, even if we consider that many Cu 2+ ions may exist in the form of stable organic/inorganic complexes in the human body, the possibility of this filter effect on the fluorescence of GdVO4:Eu nanoprobes cannot be ignored.Inversely, the high selectivity and sensitivity may make GdVO4:Eu NPs a "turn-off" fluorescent sensing material to monitor and maintain a toxic Cu 2+ concentration in environmental water.

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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.210
Teacher spread0.201 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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Same venueProceedings of the World Congress on Mechanical, Chemical, and Material EngineeringSame topicLuminescence Properties of Advanced MaterialsFrench-language works237,207