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Record W4411647719 · doi:10.5488/cmp.28.23602

Replica RISM molecular solvation theory for electric double layer in nanoporous materials

2025· article· en· W4411647719 on OpenAlexafffund
Andriy Kovalenko

Bibliographic record

VenueCondensed Matter Physics · 2025
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsAlberta Environment and Protected Areas
FundersNatural Sciences and Engineering Research Council of CanadaAlberta InnovatesWestern Canada Research GridCompute Canada
KeywordsNanoporousReplicaSolvationMaterials scienceLayer (electronics)Chemical physicsNanotechnologyPhysicsMoleculeQuantum mechanics

Abstract

fetched live from OpenAlex

Applications of 3D-RISM-KH molecular solvation theory range from solvation energy of small molecules to phase behavior of polymers and biomolecules. It predicts the molecular mechanisms of chemical and biomolecular systems. Replica RISM-KH-VM molecular solvation theory predicts and explains the structure, thermodynamics, and electrochemistry of electrolyte solutions sorbed in a nanoporous material. It was tested on nanoporous carbon supercapacitors with aqueous electrolyte and nanoporous electrosorption cells. The mechanisms in these systems are steered by the electric double layer potential drop across the Stern layer at the nanopores surface and the Gouy-Chapman layer averaged over the nanoporous material, the osmotic term due to the ionic concentrations difference in the two nanoporous electrodes and in the electrolyte solution outside, and the solvation chemical potentials of sorbed ions averaged over the nanoporous material. The latter strongly depends on chemical specificity of ions, solvent, surface functional groups, and steric effects for solvated ions confined in nanopores.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.248
Teacher spread0.239 · 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 routes2
Has abstractyes

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