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Record W2013454286 · doi:10.1063/1.3463204

Influence of pressure on the Pt nanoparticle growth modes during pulsed laser ablation

2010· article· en· W2013454286 on OpenAlexafffund
Daria Riabinina, Éric Irissou, Boris Le Drogoff, Mohamed Chaker, Daniel Guay

Bibliographic record

VenueJournal of Applied Physics · 2010
Typearticle
Languageen
FieldEngineering
TopicLaser-Ablation Synthesis of Nanoparticles
Canadian institutionsInstitut National de la Recherche ScientifiqueUniversité de Montréal
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsTorrLaser ablationPulsed laser depositionNanoparticleDiffusionAnalytical Chemistry (journal)Materials scienceThin filmAtmosphere (unit)PlasmaSubstrate (aquarium)PlatinumSpectroscopyDeposition (geology)LaserChemistryNanotechnologyOptics

Abstract

fetched live from OpenAlex

Pulsed laser deposition of a platinum target was performed in solution and in a He background gas atmosphere at pressures ranging from 10−5 to 11 Torr. The influence of the plasma dynamics on the structural properties of the nanostructured Pt films was investigated by time-of-flight and space-resolved emission spectroscopy (velocity measurements). It is shown that two different growth modes exist. In the first, formation of nanoparticle is occurring in the surrounding media (gas or solution), while in the second one, diffusion and reorganization of atomic species at the substrate surface is favored. In a gaseous environment, the transition between both modes is occurring at He pressure of ∼0.5 Torr, which corresponds to a velocity of ∼5.8×103 m s−1.

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)0.001
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
Metaresearch0.0000.001
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)0.0010.000

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 head0.007
GPT teacher head0.195
Teacher spread0.187 · 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

Citations44
Published2010
Admission routes2
Has abstractyes

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