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Record W4231665971 · doi:10.5194/acpd-9-22929-2009

Size dependence of volume and surface nucleation rates for homogeneous freezing of supercooled water droplets

2009· preprint· en· W4231665971 on OpenAlexafffund
Thomas Kühn, Michael E. Earle, Alexei F. Khalizov, J. J. Sloan

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsUniversity of WaterlooEnvironment and Climate Change Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNucleationSupercoolingIce nucleusAerosolVolume (thermodynamics)RADIUSSurface tensionMaterials scienceClassical nucleation theoryHomogeneousThermodynamicsChemistryPhysics

Abstract

fetched live from OpenAlex

Abstract. We investigated the relative roles of volume and surface nucleation in the freezing of water droplets. Nucleation experiments were carried out in a cryogenic laminar aerosol flow tube using supercooled liquid water aerosols with radii between about 1 and 3 μ m. Temperature- and size-dependent values of volume- and surface-based homogeneous nucleation rate between 234.8 and 236.2 K are derived with help of a microphysical model from aerosol compositions and size distributions based on infrared extinction measurements in the aerosol flow tube. The results show that the contribution from nucleation at the droplet surface increases with decreasing droplet radius and dominates over nucleation in the bulk droplet volume for droplets with radii smaller than approximately 5 μm. This is interpreted in terms of a lowered free energy of ice germ formation in the surface-based process and has implications for the parameterization of homogeneous ice nucleation in numerical models.

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: Simulation or modeling · Consensus signal: none
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 head0.008
GPT teacher head0.233
Teacher spread0.224 · 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

Citations5
Published2009
Admission routes2
Has abstractyes

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