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Record W2303256406 · doi:10.14288/1.0167534

A molecular dynamics investigation of ice nucleation induced by electric fields

2014· article· en· W2303256406 on OpenAlexaff
Jingyi Yan

Bibliographic record

VenuecIRcle (University of British Columbia) · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicnanoparticles nucleation surface interactions
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNucleationElectric fieldDynamics (music)Statistical physicsPhysicsThermodynamicsAcoustics

Abstract

fetched live from OpenAlex

This thesis aims to understand the influence of electric fields on ice nucleation. Molecular dynamics simulations are employed to investigate heterogeneous ice nucleation induced by electric fields, and why external electric fields promote freezing in liquid water models. The first project considers heterogeneous ice nucleation in systems, where water molecules experience an electric field in a narrow region over an entire surface. The specific focus is ice nucleation and growth processes. Different water models are considered, and the influences of temperature and field parameters are examined. We find no qualitative difference between the two water models. By analyzing structure, we show that a ferroelectric cubic ice layer freezes inside the field region, and unpolarized ice grows beyond the field region, at temperatures not far below the melting point. We explore ice nucleation by electric field bands, which act only over a portion of a surface. Field bands of different geometry nucleate ice, provided that the band is sufficiently large. Analysis of different systems reveals that ice strongly prefers to grow at the (111) crystal plane of cubic ice, and that ice nucleated by field bands usually grows as a mixture of cubic and hexagonal ice. Our results suggest that local electric fields could play a major role in heterogeneous ice nucleation, particularly for rough particles with many surface structural variations, that serve as ice nuclei in the environment. We also investigate the electrofreezing of water subject to a uniform field. The aim is to obtain an understanding of why electric fields facilitate ice nucleation. It is shown that the melting point of water increases significantly when water is polarized by a field. The increased melting point is mainly due to the favourable interaction of near perfectly polarized cubic ice with the applied field. Relevant to the mechanism of heterogeneous ice nucleation by local surface fields, our results suggest that local fields effectively increase the degree of supercooling of locally polarized liquid. This decreases the size of the critical nucleus in the region influenced by the field, facilitating ice nucleation.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.738
Threshold uncertainty score0.873

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 head0.006
GPT teacher head0.159
Teacher spread0.153 · 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 designObservational
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

Citations0
Published2014
Admission routes1
Has abstractyes

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