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Record W4408359591 · doi:10.1021/acs.langmuir.4c05089

Effect of Ion-Specific Hydration Forces on the Stability of Water Films on Calcite Surfaces

2025· article· en· W4408359591 on OpenAlexaff
Kazuya Kobayashi, Naoya Nishi, Tetsuo Sakka

Bibliographic record

VenueLangmuir · 2025
Typearticle
Languageen
FieldMaterials Science
TopicCalcium Carbonate Crystallization and Inhibition
Canadian institutionsCarbon Engineering (Canada)
Fundersnot available
KeywordsCalciteIonChemical engineeringChemistryMaterials scienceMineralogyOrganic chemistry

Abstract

fetched live from OpenAlex

The hydration force is indispensable for understanding short-range interfacial forces in aqueous systems. Perturbation of the hydration structure by ions generates an ion-specific hydration force. Surface-force measurements on calcite surfaces have suggested that Na + decreases the repulsive hydration force by directly adsorbing the surface and disrupting the hydration layers. However, the influence of structural changes on the surface force remains unclear. We conducted molecular dynamics simulations for water films between calcite (104) surfaces and oil/water interfaces. Ion-specific hydration forces estimated by the simulations were consistent with the experimental results. Notably, the ion-specific hydration forces cannot be explained solely by the structure of water molecules because ions do not significantly change the structure of the hydration layers, such as density distributions and orientations. We propose a novel mechanism whereby ion-specific electrostatic potentials in the water films control the adhesive and repulsive nature of the interfaces. The directly adsorbed Na + on the calcite causes the monotonically decreasing electrostatic potential from the calcite surface, thereby enhancing adhesion. Ca 2+ results in a convex shape of the electrostatic potential curve, which enhances repulsion. Importantly, the shape of the electrostatic potential curve depends on the Stern layer structure and the perturbation between the surface and interfaces. This study offers important insight for interpreting surface-force measurements in aqueous systems.

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)0.001
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 score0.008
Threshold uncertainty score0.792

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.013
GPT teacher head0.249
Teacher spread0.235 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

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