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Record W2923027571 · doi:10.1021/acs.iecr.9b00504

Effects of Salt and Surfactant on Interfacial Characteristics of Water/Oil Systems: Molecular Dynamic Simulations and Dissipative Particle Dynamics

2019· article· en· W2923027571 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2019
Typearticle
Languageen
FieldChemistry
TopicSurfactants and Colloidal Systems
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaMemorial University of Newfoundland
KeywordsDissipative particle dynamicsPulmonary surfactantRadius of gyrationSurface tensionMolecular dynamicsThermodynamicsChemistryMicroemulsionMaterials scienceChemical engineeringOrganic chemistryComputational chemistryPhysicsPolymer

Abstract

fetched live from OpenAlex

Multiphase systems and their behaviors/characteristics appear to be crucial in a variety of industries such as the oil and gas sector, pharmaceutical industry, and food industry. In this paper, the mesoscale simulation method is used to predict the interfacial behaviors of the water/oil systems at different temperatures and salt concentrations in the presence of a nonionic surfactant (hexaethylene glycol monododecyl ether). Dissipative particle dynamics (DPD) is employed to model the interfacial properties (e.g., interfacial density and interfacial tension) and structural properties such as the radius of gyration as a function of water/oil ratio, surfactant concentration, temperature, and salinity of oil/surfactant/water mixtures. Molecular dynamics (MD) simulations are carried out to estimate the Flory–Huggins chi parameter by means of temperature-dependent solubility parameter and cohesive energy calculations using Monte Carlo (MC) method, which is then utilized as an input for the DPD approach. The DPD repulsive interaction parameter (aij) is also obtained from the dependence of chi parameter to temperature using MD simulations. Both the density profiles and simulation snapshots indicate a well-defined interface between water and oil phases, where the thickness of the layer increases with increasing the surfactant concentration and the peak of density becomes higher accordingly. It is found that the radius of gyration is a weak function of salinity; however, it increases with an increase in the surfactant concentration, revealing that the surfactant molecules become more stretched at the interface. By increasing the water content or water/oil ratio (WC), the interfacial tension increases to reach a maximum value. After the maximum interfacial tension, increasing the water/oil ratio lowers this important parameter. According to the results of the MD simulations, the presence of salt improves the interfacial efficiency of the surfactant by decreasing the interfacial tension, which is in a good agreement with the literature data. Integrating the micro- and mesoscale modeling through chi parameter determination improves the accuracy of the calculations. This integration also decreases the calculation time (and costs). Employing the integrated modeling approach, the dynamic performance of the targeted systems can be thus well-reproduced with respect to the results reported in the literature. This research work offers useful tips for surfactant selection as well as important results and information on the interactions of molecules at water/oil interface, which are central to analyze emulsion stability at different process and thermodynamic conditions.

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.

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 score0.073
Threshold uncertainty score0.684

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 science0.0000.000
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 head0.017
GPT teacher head0.273
Teacher spread0.256 · 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