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Record W1999349220 · doi:10.1115/imece2011-64747

Molecular Dynamics Simulation of Thermal Accommodation Coefficients for Laser-Induced Incandescence Sizing of Nickel Nanoparticles

2011· article· en· W1999349220 on OpenAlexaff
Kyle J. Daun, Mikko Karttunen, J. T. Titantah

Bibliographic record

VenueVolume 11: Nano and Micro Materials, Devices and Systems; Microsystems Integration · 2011
Typearticle
Languageen
FieldEngineering
TopicLaser-Ablation Synthesis of Nanoparticles
Canadian institutionsWestern UniversityUniversity of Waterloo
FundersUniversität Bremen
KeywordsIncandescenceMaterials scienceArgonMolecular dynamicsNanoparticleThermal desorptionChemical physicsAtomic physicsMolecular physicsChemistryDesorptionNanotechnologyAdsorptionPhysical chemistryComputational chemistryPhysics

Abstract

fetched live from OpenAlex

While time-resolved laser-induced incandescence is most often used to characterize the size and concentration of aerosolized carbonaceous particles, it has recently been applied to aerosols containing metal nanoparticles. This calculation requires the thermal accommodation coefficient, however, which is often difficult to determine experimentally. This paper presents a molecular dynamics investigation of the thermal accommodation coefficient between laser-energized nickel nanoparticles immersed in argon, and the underlying the gas-surface scattering physics. The predicted interaction between gas molecules and the laser-energized surface depends strongly on the potential between the gas molecule and a surface atom: a Lennard-Jones 6–12 potential derived using the Lorentz-Berthelot combination rules overestimates the potential well due to a bond-order effect in the nickel, resulting in strong trapping-desorption and near-perfect thermal accommodation. A Morse potential with parameters obtained directly from ab initio free energies predicts a relatively brief interaction between the gas molecule and nickel surface, on the other hand, and a lower thermal accommodation coefficient similar to experimentally-derived values for laser-energized iron nanoparticles in argon reported in the literature.

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)0.001
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 score0.143
Threshold uncertainty score0.840

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.023
GPT teacher head0.230
Teacher spread0.207 · 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 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

Citations1
Published2011
Admission routes1
Has abstractyes

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Same venueVolume 11: Nano and Micro Materials, Devices and Systems; Microsystems IntegrationSame topicLaser-Ablation Synthesis of NanoparticlesFrench-language works237,207