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Record W2046482201 · doi:10.1080/0141590412331316753

Computer simulations of the condensation of nanoparticles from the gas phase

2005· article· en· W2046482201 on OpenAlexaff
Ralf Meyer, Yu. Ya. Gafner, С. Л. Гафнер, Sonja Stappert, Bernd Rellinghaus, P. Entel

Bibliographic record

VenuePhase Transitions · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicnanoparticles nucleation surface interactions
Canadian institutionsUniversité de Montréal
FundersDeutsche ForschungsgemeinschaftDeutscher Akademischer Austauschdienst
KeywordsAgglomerateCondensationEconomies of agglomerationNanoclustersNanoparticleChemical physicsMaterials scienceCrystallizationParticle (ecology)Phase (matter)SinteringDiffusionMolecular dynamicsGas phaseChemical engineeringNanotechnologyThermodynamicsChemistryPhysical chemistryComposite materialComputational chemistryPhysics

Abstract

fetched live from OpenAlex

The crystallization of Ni nanoclusters from the gas phase is investigated with the help of molecular dynamics simulations using empirical tight-binding potentials. In these simulations, the condensation of hot liquid droplets from the gas phase is observed which later crystallize and agglomerate. It is shown that agglomeration of crystallized particles is the dominating growth mode and that the shapes of the final particles are similar to the shapes of experimentally grown Ni nanoparticles. In the second part, the evolution of the structure and the morphology of an agglomerated particle during sintering at 600 and 900K is studied. While in both cases the original disordered interface between the agglomerated particles vanishes, the shapes of the resulting particles differ considerably due to the different surface diffusion rates.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.029
GPT teacher head0.280
Teacher spread0.251 · 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 designSimulation or modeling
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

Citations32
Published2005
Admission routes1
Has abstractyes

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