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Record W2070160019 · doi:10.1021/jp1037552

Nanoclustered Co−Au Particles Fabricated by Femtosecond Laser Fragmentation in Liquids

2010· article· en· W2070160019 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2010
Typearticle
Languageen
FieldEngineering
TopicLaser-Ablation Synthesis of Nanoparticles
Canadian institutionsPolytechnique MontréalRegroupement Québécois sur les Matériaux de Pointe
Fundersnot available
KeywordsNanoclustersBimetallic stripMaterials scienceNanoparticleMagnetizationFemtosecondAnalytical Chemistry (journal)NanostructureLaserNanotechnologyChemistryOpticsOrganic chemistryMetalMagnetic field

Abstract

fetched live from OpenAlex

Heterostructured nanoparticles, consisting of Au and Co nanoclusters, have been synthesized by a two-step femtosecond laser technique. Au and Co targets were ablated and fragmented in acetone resulting in nanoparticles with an average diameter of 11 nm. Particles showed concomitant optical characteristics of Au and magnetic properties of Co. Energy dispersive X-ray scattering confirmed the presence of both material in each nanoparticle and showed that the relative concentration of Au and Co can be controlled. Unalloyed Au nanoclusters are estimated to be 1.5 nm from X-ray diffraction measurement of the 220 peak width and position. Pure Co nanoparticles have a room temperature magnetization of 28 emu/g, much lower than the bulk value of 143 emu/g, probably due to surface oxidation. In the bimetallic nanostructures, Au replaced oxidized Co and protected the core from oxidation. Nanoparticles consisting of 68% Co and 32% Au showed a magnetization of 51.3 emu/g which represents a 83% increase per Co atom compared to pure Co nanoparticles.

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.

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 score0.004
Threshold uncertainty score0.323

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)0.0000.000

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 head0.007
GPT teacher head0.229
Teacher spread0.222 · 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