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Record W2097834335 · doi:10.1021/ic4026975

Hybrid Nanomaterials: Anchoring Magnetic Molecules on Naked Gold Nanocrystals

2013· article· en· W2097834335 on OpenAlexafffund
Rebecca J. Holmberg, Amy-Jayne Hutchings, Fatemah Habib, Ilia Korobkov, J. C. Scaiano, Muralee Murugesu

Bibliographic record

VenueInorganic Chemistry · 2013
Typearticle
Languageen
FieldMaterials Science
TopicNanocluster Synthesis and Applications
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNanotechnologyNanomaterialsDysprosiumChemistryColloidal goldNanoparticleMagnetic nanoparticlesNanostructureNanocrystalMaterials science

Abstract

fetched live from OpenAlex

The pairing of molecular magnets and nanomaterials couples top-down and bottom-up approaches to nanotechnology; facilitating a unique methodology to the controlled study of interfacial magnetic properties. Attaching Single-Molecule Magnets (SMMs) to "naked" gold nanoparticles is a novel method of exploring various avenues of magnetic nanotechnology, such as drug delivery, information storage, catalysis, and assembly of magnetic-nanostructural motifs. Herein we report the successful capping of laser ablation synthesized "naked" gold nanoparticles with a dinuclear dysprosium complex, while introducing new information regarding the changes in molecular magnetic properties upon surface attachment. We anticipate that this methodology in producing these magneto-plasmonic nanostructures not only provides answers to fundamental questions but also has the potential to provide new avenues to applications including information storage, multimodal imaging, biomedicine, and optoelectronics.

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 score0.003

Distilled classifier scores by category (both heads)

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 integrity0.0010.000
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 head0.008
GPT teacher head0.206
Teacher spread0.198 · 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

Citations26
Published2013
Admission routes2
Has abstractyes

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