MétaCan
Menu
Back to cohort

Mathematical Modelling and Nonlinear Analysis of Reaction Diffusion Mechanism of the Volatile Compounds Alongside Spherical Electrodes Embedded within the Chemically Modified Electrodes

2025· article· en· W4413380603 on OpenAlexvenueno aff
A. Uma, R. Swaminathan

Bibliographic record

VenueInternational Journal of Analysis and Applications · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced Chemical Sensor Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsElectrodeMechanism (biology)Nonlinear systemDiffusionGaseous diffusionChemistryMaterials scienceChemical engineeringThermodynamicsPhysical chemistryPhysicsEngineering

Abstract

fetched live from OpenAlex

The main objective of the present research is to propose a new mathematical formulation for the concentration of volatile substances corresponding to spherical electrodes through applying steady state reaction diffusion equations within the electrode surface in the presence of chemically modified electrodes. This model requires into consideration the diffusion of reactants and charge carriers that occur within the chemically modified layer that is positioned at the electrode surface. All probable experimental responses of the parameter may utilise appropriate mediator, substrate, and current concentrations evaluated analytically through the implementation of the Akbari Ganji Method. A numerical representation of the issue being studied can also be obtained implementing MATLAB software aimed at assisting comprehend the dynamics of the system. An appropriate degree of concurrence is subsequently provided once the ensuring results have been examined using currently accessible numerical data with previously discovered information.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.239
Teacher spread0.233 · 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 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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Analysis and ApplicationsSame topicAdvanced Chemical Sensor TechnologiesFrench-language works237,207