Reentrant Microtexture

Reentrant microtexture is an engineered surface architecture composed of microscale features with overhanging or inward-curving profiles, enabling control of how liquids, particles, and contacting materials interact with a surface. Its geometry can pin contact lines, trap air, and create capillary barriers that resist liquid penetration, while overhangs also promote mechanical interlocking at interfaces. In engineering, these textures support water-repellent and anti-icing surfaces, droplet manipulation, adhesion control, and protective coatings. By linking feature shape and spacing to wetting, friction, and interfacial stability, reentrant microtexture provides a design strategy for tailoring surface performance across diverse technologies.

Reentrant Microtexture - Related Videos

Research

JoVE Journal - Engineering
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Rendering SiO2/Si Surfaces Omniphobic by Carving Gas-Entrapping Microtextures Comprising Reentrant and Doubly Reentrant Cavities or Pillars

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Cited by 17 •

2020

This work presents microfabrication protocols for achieving cavities and pillars with reentrant and doubly reentrant profiles on SiO2/Si wafers using photolithography and dry etching. Resulting microtextured surfaces demonstrate remarkable liquid repellence, characterized by robust long-term entrapment of air under wetting liquids, despite the intrinsic wettability of silica.

Research

JoVE Journal - Medicine
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Non-fluoroscopic Catheter Tracking for Fluoroscopy Reduction in Interventional Electrophysiology

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Cited by 4 •

2015

Radiation exposure is an underestimated risk in complex ablation procedures. Here, we describe a protocol to significantly decrease fluoroscopy time and dosage for both the patient and the lab staff by using a novel non-fluoroscopic catheter visualization system.

Research

JoVE Journal - Bioengineering

Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations

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Cited by 14 •

2013

A methodology to estimate ventricular fiber orientations from in vivo images of patient heart geometries for personalized modeling is described. Validation of the methodology performed using normal and failing canine hearts demonstrate that that there are no significant differences between estimated and acquired fiber orientations at a clinically observable level.

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