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Record W2972175924 · doi:10.5539/ijc.v11n2p127

Derivation of a pH Dependent Solid-Liquid Interfacial Tension and Theoretical Interpretation of the Physicochemistry of Dewetting in the CO2-Brine-Silica System

2019· article· en· W2972175924 on OpenAlexafffundvenue
Mumuni Amadu, Adango Miadonye

Bibliographic record

VenueInternational Journal of Chemistry · 2019
Typearticle
Languageen
FieldEngineering
TopicElectrowetting and Microfluidic Technologies
Canadian institutionsCape Breton UniversityDalhousie University
FundersDalhousie UniversityCape Breton University
KeywordsWettingSurface tensionChemistryDewettingContact angleThermodynamicsChemical engineering

Abstract

fetched live from OpenAlex

The solid-liquid interfacial tension is a fundamental parameter in areas of wettability pertaining to adhesive bonds and petroleum engineering practice. In wettability issues related to surface functionalized polymeric materials design to achieve specific adhesive properties, the solid-liquid interfacial tension can be pH dependent due to amphoteric behavior. In this paper, we have used the theory of pH dependent surface charging and the 2-pk model as well as the site binding model of the electric double layer theory to derive a pH dependent solid-liquid interfacial tension equation. Following the fundamental relationship between solid-liquid interfacial tension and contact angle in light of Young’s equation, we have extended the theoretical basis of the derivation. Consequently, we have also derived a pH dependent cosine of the thermodynamic contact angle. Both equations give satisfactory explanations for observed experimental data available in the literature.

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.002
GPT teacher head0.206
Teacher spread0.204 · 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

Citations6
Published2019
Admission routes3
Has abstractyes

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