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Record W3194836547 · doi:10.1038/s41427-021-00325-9

Monolithic polymeric porous superhydrophobic material with pneumatic plastron stabilization for functionally durable drag reduction in blood-contacting biomedical applications

2021· article· en· W3194836547 on OpenAlexaff
Jennifer Marlena, Justin Kok Soon Tan, Zenggan Lin, David Li, Boxin Zhao, Hwa Liang Leo, Sangho Kim, Choon Hwai Yap

Bibliographic record

VenueNPG Asia Materials · 2021
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversity of WaterlooUniversity of Alberta
FundersNational Medical Research CouncilMedical Research Council
KeywordsMaterials scienceDurabilityDragPorosityFoulingComposite materialResistDissolutionAbrasion (mechanical)Porous mediumSlip (aerodynamics)Pressure dropPolytetrafluoroethyleneChemical engineeringChemistryLayer (electronics)

Abstract

fetched live from OpenAlex

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.000

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 head0.013
GPT teacher head0.232
Teacher spread0.220 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations27
Published2021
Admission routes1
Has abstractyes

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