Ion Valency and Concentration Effect on the Structural and Thermodynamic Properties of Brine–Decane Interfaces with Anionic Surfactant (SDS)
Bibliographic record
Abstract
Salt ion valency and concentration vary in actual oil reservoirs, which play an important role in the functionalities of surfactant formula during chemical flooding processes to enhance oil recovery. Herein, we report a molecular dynamics (MD) study to investigate the ion valency and concentration effect on the structural and thermodynamic properties of brine–decane interfaces with anionic surfactant (SDS), under typical reservoir conditions (353 K and 200 bar). We use two different cations (Na + and Ca 2+ ) and a wide range of ion concentrations (up to 3.96 M) to simulate reservoir conditions. We find that ion valency has a significant effect on the molecular configurations, which further influences the thermodynamic properties. Ca 2+ ions can have a strong adsorption at the interface due to the strong electrostatic interactions between Ca 2+ ions and SDS, which also results in the Cl – ion enrichment at the interface. Furthermore, Ca 2+ ions can form pentagon-like SDS–Ca 2+ complexes through SDS–Ca 2+ –SDS cation bridging, which renders a nonuniform distribution of SDS at the interface. On the other hand, the cation bridging density monotonically increases as ion concentration increases for the systems without Ca 2+ ions, while first increases, then decreases for the systems with Ca 2+ ions. This is because the accumulation of Cl – ions at the interface at high salt concentrations can melt SDS–Ca 2+ complexes. This work should provide new insights into the structural and thermodynamic properties of brine–oil interfaces with an anionic surfactant, which can facilitate the optimization of chemical flooding processes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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