MétaCan
Menu
Back to cohort
Record W2313281865 · doi:10.1021/la200596c

A General Poisson−Boltzmann Model with Position-Dependent Dielectric Permittivity for Electric Double Layer Analysis

2011· article· en· W2313281865 on OpenAlexaff
Guigao Le, Junfeng Zhang

Bibliographic record

VenueLangmuir · 2011
Typearticle
Languageen
FieldChemistry
TopicElectrostatics and Colloid Interactions
Canadian institutionsLaurentian University
Fundersnot available
KeywordsPermittivityRelative permittivityBoltzmann constantDielectricMaterials scienceLayer (electronics)Poisson distributionPosition (finance)Condensed matter physicsDielectric permittivityChemistryMolecular physicsComputational physicsPhysicsThermodynamicsComposite materialOptoelectronicsMathematics

Abstract

fetched live from OpenAlex

In this paper, we propose a general Poisson-Boltzmann model for electric double layer (EDL) analysis with the position dependence of dielectric permittivity considered. This model provides physically reasonable property profiles in the EDL region, and it is then utilized to investigate the depletion layer effect on EDL structure and interaction near hydrophobic surfaces. Our results show that both the electric potential and the interaction pressure between surfaces decrease due to the lower permittivity in the depletion layer. The reduction becomes more profound at larger variation magnitude and range. This trend is in general agreement with that observed from the previous stepwise model; however, that model has overestimated the influence of permittivity variation effect. For the thin depletion layer and the relative thick EDL, our calculation indicates that the permittivity variation effect on EDL usually can be neglected. Furthermore, our model can be readily extended to study the permittivity variation in EDL due to ion accumulation and hydration in the EDL region.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0030.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.024
GPT teacher head0.260
Teacher spread0.236 · 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 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

Citations13
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueLangmuirSame topicElectrostatics and Colloid InteractionsFrench-language works237,207