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Record W1999554283 · doi:10.1103/physrevb.80.045430

High-resolution investigation of metal nanoparticle growth on an insulating surface

2009· article· en· W1999554283 on OpenAlexaff
Jeffrey M. Mativetsky, Shawn Fostner, Sarah A. Burke, Peter Grütter

Bibliographic record

VenuePhysical Review B · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSurface and Thin Film Phenomena
Canadian institutionsMcGill University
Fundersnot available
KeywordsPalladiumMaterials scienceTantalumNanoparticleMonolayerEpitaxyTransmission electron microscopySubstrate (aquarium)MetalHalideNanotechnologyChemical physicsChemical engineeringAnalytical Chemistry (journal)Layer (electronics)Inorganic chemistryMetallurgyChemistryCatalysis

Abstract

fetched live from OpenAlex

The three-dimensional nanoparticle morphology and the nanoparticle-substrate relationship during the submonolayer growth of three metals (gold, tantalum, and palladium) on the alkali halide KBr (001) surface is investigated by combining in situ high-resolution noncontact atomic force microscopy and ex situ transmission electron microscopy approaches. Highly varied growth behavior between the metals is revealed. Gold produces nearly spherical multiply twinned nanoparticles at room temperature and an increasing number of epitaxial particles at elevated temperatures. In contrast, the tantalum grows as relatively flat fractal particles, despite the square symmetry of the substrate lattice, a condition which normally precludes fractal growth. The tantalum also exhibits a strong affinity for KBr surface steps, leading to one-dimensional chains of nanoparticles. The deposition of palladium results in the creation of protruding substrate distortions and monolayer-high rectangular KBr islands in addition to the growth of palladium nanoparticles. It is hypothesized that the unusual growth observed in the palladium-KBr system is caused by the interdiffusion of palladium under the KBr surface. The range of growth behavior in the three systems is described in terms of the surface and interface energies, yielding bounds on the metal/KBr interface energies.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.408

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 head0.022
GPT teacher head0.281
Teacher spread0.260 · 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 designTheoretical or conceptual
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
Published2009
Admission routes1
Has abstractyes

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