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Record W2904675977 · doi:10.1515/ijcre-2018-0152

A Diffusion Cell for the Mass Transfer Investigation in the Solid Porous Media

2018· article· en· W2904675977 on OpenAlexfundno aff
Alexey Zhokh, Andrii Trypolskyi, P. E. Strizhak

Bibliographic record

VenueInternational Journal of Chemical Reactor Engineering · 2018
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsnot available
FundersNational Academy of Sciences of UkraineYork University
KeywordsMass transferDiffusionPorous mediumBoundary (topology)MechanicsPorosityBoundary value problemMaterial balanceMaterials scienceGaseous diffusionThermodynamicsChemistryPhysicsMathematical analysisProcess engineeringPhysical chemistryMathematicsComposite materialEngineering

Abstract

fetched live from OpenAlex

Abstract A diffusion cell for the mass transfer investigation of the gases through the solid porous media is developed. The diffusion cell may be configured in two different ways. One configuration corresponds to the reflecting boundary condition, whereas another configuration satisfies the absorbing boundary. The mass balance equations for different cell configurations are provided. The mass balance equations are applicable for the calculations of the diffusate quantity decays. The latter are suitable for the mass transfer parameters estimation using the solutions of the transport equations, obtained for the boundary conditions that correspond to the diffusion cell configurations. Accounting for the impact of the apparatus function of the diffusion cell on the experimental data is also revisited. In addition, the practical use of the diffusion cell based on the installation of the cell into the gas chromatograph for the investigation of the methane transport through the porous silica pellet as an example is demonstrated.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.277

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 science0.0010.000
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 head0.230
Teacher spread0.220 · 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 designBench or experimental
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

Citations3
Published2018
Admission routes1
Has abstractyes

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