Hierarchically Textured Oleophobic Internal Coatings that Facilitate Drag Reduction of Viscous Oils in Macroscopic Laminar Flow
Why this work is in the frame
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Bibliographic record
Abstract
For transportation of hydrocarbon liquids via pipelines, reducing the frictional forces between internal walls and viscous oils through modification of the interfacial surface chemistry and topography represents a key imperative, enabling viscous oil flow at lower temperatures while mitigating the need for diluents. Although drag reduction of aqueous flows in lithographically patterned microchannels has been widely explored, herein drag reduction of oil flows within macroscopic tubing spanning several feet in length is demonstrated. Multiscale texturation is derived from the introduction of micron‐sized pits during electroless deposition of nickel and is augmented by nanoscale texturation derived from the incorporation of polytetrafluoroethylene (PTFE) beads within the coating. Further functionalization with a monolayer of 1 H ,1 H ,2 H ,2 H ‐perfluorooctanephosphonic acid yields a surface that is not wetted by water or viscous oils, yielding 17% drag reduction under laminar flow for castor oil and a slip length that approaches 329 μm. The results demonstrate a promising solution for obtaining robust plastronic architectures embedded within the inner walls of macroscopic tubing. The performance of such coatings is constrained primarily by the robustness of plastrons and molecular properties of the flow liquid with the latter modifying the solid/liquid interface energy as a result of surface adsorption.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 it