Extraction of EPA/DHA from 18/12EE Fish Oil Using AgNO<sub>3</sub>(aq): Composition, Yield, and Effects of Solvent Addition on Interfacial Tension and Flow Pattern in Mini-Fluidic Systems
Bibliographic record
Abstract
Solvent extraction of Omega-3 polyunsaturated fatty acids (PUFA) ethyl esters (Et) from 18/12EE fish oil was performed with an aqueous silver nitrate solution in a mini-fluidic reactor framework. The resulting extraction was compared within conventional stirred-tank reactors, with practical extraction yields of EPA-Et and DHA-Et approaching 60 to 70 wt %. Equilibrium was reached in less than 36 s at 10 °C, despite stratified flow being observed rather than previously reported slug-flow profiles in idealized fluid pairs at these scales. The deviation in flow pattern was attributed to a measured order of magnitude reduction in the interfacial tension between fish oils and AgNO 3 solution relative to idealized solvent mixtures using hexane/heptane as a carrier for purified EPA/DHA. The impact of solvent addition to fish oils on interfacial tension with silver nitrate solutions was subsequently explored through spinning drop tensiometry, suggesting that the heterogeneous nature of raw fish oils will yield significantly different flow patterns than previously considered in extraction studies utilizing AgNO 3 solutions. These results are applicable both to mini-fluidic systems and for the approximation of interfacial tension in fish oil/organic/aqueous extraction 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 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) | 0.000 | 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.
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".