Monolithic polymeric porous superhydrophobic material with pneumatic plastron stabilization for functionally durable drag reduction in blood-contacting biomedical applications
Bibliographic record
Abstract
Abstract Superhydrophobic (SHP) surfaces can provide substantial reductions in flow drag forces and reduce blood damage in cardiovascular medical devices. However, strategies for functional durability are necessary, as many SHP surfaces have low durability under abrasion or strong fluid jetting or eventually lose their air plastron and slip-flow capabilities due to plastron gas dissolution, high fluid pressure, or fouling. Here, we present a functional material that extends the functional durability of superhydrophobic slip flow. Facile modification of a porous superhydrophobic polytetrafluoroethylene (PTFE, Teflon) foam produced suitable surface structures to enable fluid slip flow and resist protein fouling. Its monolithic nature offered abrasion durability, while its porosity allowed pressurized air to be supplied to resist fluid impalement and to replenish the air plastron lost to the fluid through dissolution. Active pore pressure control could resist high fluid pressures and turbulent flow conditions across a wide range of applied pressures. The pneumatically stabilized material yielded large drag reductions (up to 50%) even with protein fouling, as demonstrated from high-speed water jetting and closed loop pressure drop tests. Coupled with its high hemocompatibility and impaired protein adsorption, this easily fabricated material can be viable for incorporation into blood-contacting medical devices.
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) | 0.001 | 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.
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".