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Record W1972183755 · doi:10.2495/afm100161

A universal multi-dimensional charge and mass transfer model

2010· article· en· W1972183755 on OpenAlexaff
Glyn Kennell, Richard W. Evitts

Bibliographic record

VenueWIT transactions on engineering sciences · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Thermodynamics and Statistical Mechanics
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMass transferElectric fieldCharge conservationElectrolyteMass transportCharge (physics)MechanicsDiffusionConductorAnodeConvectionIonic bondingMaterials scienceField (mathematics)PhysicsIonThermodynamicsElectrodeEngineering physics

Abstract

fetched live from OpenAlex

A new approach has been developed for modelling the transport of charge and mass through electrolytes. This approach utilizes a dynamically computed electric field that contributes to the transport of charged species in much the same way a flow field contributes to the transport of mass. Since a multidimensional electric field is computed, the effects of this field on redox reactions occurring in the electrolyte or at the interface of an electronic and ionic conductor can be modelled. Transport of species due to diffusion and convection is also considered, and the overall transport system is modelled using a control volume technique with a modified Peclet number. Electroneutrality and the conservation of species are incorporated into the model. This method produces a universal model capable of predicting one, two, or three-dimensional mass and charge transport for electrochemical phenomena where macroscopic anodic and cathodic couples exist. This model has the potential to simulate forms of localized corrosion and energy storage and generation applications such as batteries and fuel cells. The theoretical development and validation of this new model for a two dimensional case study is presented.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.853
Threshold uncertainty score0.328

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 head0.218
Teacher spread0.210 · 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 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

Citations0
Published2010
Admission routes1
Has abstractyes

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