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Record W2027497055 · doi:10.1021/jp709688g

Nucleation of NaCl Nanoparticles in Supercritical Water: Molecular Dynamics Simulations

2008· article· en· W2027497055 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicnanoparticles nucleation surface interactions
Canadian institutionsTrent University
Fundersnot available
KeywordsNucleationSupercritical fluidMolecular dynamicsCluster (spacecraft)Chemical physicsNanoparticleAmorphous solidIonParticle (ecology)Particle sizeCluster sizeMaterials scienceParticle-size distributionRange (aeronautics)ChemistryPhysical chemistryCrystallographyNanotechnologyComputational chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Formation of NaCl nanoparticles in supercritical water is studied using molecular dynamics simulation method. We have simulated particle nucleation and growth in NaCl-H2O fluids, with salt concentration of 5.1 wt %, in the temperature and density range of 673-1073 K and 0.17-0.34 g/cm(3), respectively. The cluster size distributions, the size of critical nuclei and cluster lifetimes are reported. The size distribution of emerging clusters shows a very strong dependence on the system's density, with larger clusters forming at lower densities. Clusters consisting of approximately 14-24 ions appear critical for the thermodynamic states examined. The local structures of critical clusters are found to be amorphous. The lifetime values for clusters containing more than 20 ions are in the range of 10-50 ps. We have calculated the NaCl nucleation rates, which appear to be on the order of 10(28) cm(-3) 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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.400

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 head0.010
GPT teacher head0.229
Teacher spread0.218 · 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