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Record W2331909254 · doi:10.1103/physreve.89.043307

Algorithm to enforce uniform density in liquid atomistic subdomains with specular boundaries

2014· article· en· W2331909254 on OpenAlexfundno aff
K. M. Issa, Pietro Poesio

Bibliographic record

VenuePhysical Review E · 2014
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Dynamics and Properties
Canadian institutionsnot available
FundersMinistero dell’Istruzione, dell’Università e della RicercaWestern Canada Research GridUniversity of Calgary
KeywordsSpecular reflectionMaterials scienceStatistical physicsComputer sciencePhysicsOptics

Abstract

fetched live from OpenAlex

An important component in hybrid atomistic-continuum (HAC) modeling of liquids is the proper termination of the atomistic subdomain (ΩA). When the HAC model is based on the Schwarz domain decomposition method, the total number of particles in ΩA is conserved using specular boundaries in an overlap region, where information is exchanged with the continuum subdomain (ΩC). This non-periodic termination of ΩA fails to account for forces otherwise included in a periodic system, through the minimum image convention. The absence of such forces results in spurious density fluctuations adjacent to the specular boundaries. In this work, we present a new boundary force algorithm that establishes a uniform density profile at non-periodic boundaries of ΩA. We also examine the effects of the non-periodic termination of ΩA on the liquid properties. The algorithm relies on force measurements carried out over a spatially discretized atomistic subdomain. It is relatively straightforward to implement and can be seamlessly extended to higher dimensions.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.655
Threshold uncertainty score0.504

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 head0.008
GPT teacher head0.249
Teacher spread0.241 · 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 designTheoretical or conceptual
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

Citations10
Published2014
Admission routes1
Has abstractyes

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