Researchers create ultra-stretchable, liquid-repellent materials via laser ablation

(Press-News.org) Researchers from North Carolina State University have used laser ablation to create ultra-stretchable, superomniphobic materials without the use of harsh chemical solvents. The materials – which are useful in applications ranging from soft robotics to artificial skin patches – retain their superomniphobic (i.e., super-repellent) properties when stretched up to five times their initial length and at over 5,000 stretch cycles.

“Superomniphobic materials can repel virtually any liquid – such as extremely harsh acids, bases or solvents – just as well as they can water,” says Arun Kumar Kota, associate professor of mechanical and aerospace engineering at NC State. “They are useful in a wide range of applications, such as soft robots for example, which may need materials that can withstand harsh environments, stretch and change shape.” Kota is the corresponding author of the research.

Many superomniphobic materials are created by applying a spray coating to the material of interest. The coating consists of a solvent containing nanoparticles, which creates a rough, liquid repellent surface. Unfortunately, these spray coatings delaminate, or come off, when the material is stretched beyond 100% of its length.

In previous work, Kota and his team solved the delamination issue by creating microprotrusions, or tiny pillars between 10 and 100 microns across, on the surface of a material and then spray coating it. When stretched, the coating between the pillars delaminated, but the coating on top of the pillars remained intact, allowing the material to retain its superomniphobic property.

“As a crude analogy, think of my outstretched arms as the material and my hair as the microprotrusions,” Kota says. “If you pull my arms, my hair does not feel the stress and remains unaffected. We found that spray-coated materials with microprotrusions were superomniphobic at up to five times their initial length.

“In this work, instead of spray coating, we use laser ablation to create both the microprotrusions and the rough surface that creates superomniphobicity,” Kota continues. “However, we first had to determine the optimal parameters for the laser: power, speed and spatial frequency – or how many times the laser pulses per unit length.”

A machine-learning framework was given those three important parameters as well as the material’s desired sliding angle – which refers to how easily liquids slide off a surface – to determine the optimal laser ablation technique, eliminating the need for time-consuming trial-and-error testing.

The team tested the technique on a siloxane elastomer – chosen for its stretchability – that had been modified with a fluorocarbon silane, which has hydrophobic properties. The combination of the material and the laser ablation method resulted in a superomniphobic material that retained its superomniphobicity at up to five times its initial length and over 5,000 stretch cycles.

“We have created a platform for creating stretchable superomniphobic materials without the use of chemical solvents and without needing hundreds of thousands of trial-and-error experiments,” Kota says. “This method is a greener, more cost-effective way to produce materials for a diverse array of applications ranging from textile dressings to stretchable electronics that can be used in chemically harsh environments.”

The research appears in Matter and the efforts were partially supported by the National Science Foundation (award 2245427), the National Institutes of Health (awards R21EB033960 and R01HL166724) and Congressionally Directed Medical Research Programs (award HT94252310663). Mohammad Javad Zarei, a former NC State Ph.D. student, is the first author. Other NC State contributors include current postdoctoral researcher Sreekiran Pillai, former postdoctoral researcher Adil M. Rather, former masters student Mohammed S. Barrubeeah, and Tarek Echekki, associate department head of mechanical and aerospace engineering.

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Note to editors: An abstract follows.

“Ultra-stretchable superomniphobic surfaces via machine-learning-guided laser ablation”

DOI: 10.1016/j.matt.2025.102610

Authors: Mohammad Javad Zarei, Sreekiran Pillai, Adil M. Rather, Mohammed S. Barrubeeah,
Tarek Echekki, Arun K. Kota, North Carolina State University
Published: Feb. 16, 2026 in Matter

Abstract:
In this work, we report ultra-stretchable superomniphobic surfaces fabricated using a simple, inexpensive, scalable, and solvent-free CO2 laser ablation. Since the parametric space for laser ablation is multidimensional with millions of combinations, we predicted the optimal laser ablation parameters to achieve superomniphobicity with a machine learning (ML)-based algorithm. Guided by ML, we experimentally achieved ultrastretchable superomniphobic surfaces, which retained superomniphobicity even at 400% strain and 5,000+ stretch-release cycles, as well as under a diverse range of deformations. Furthermore, through systematic experiments and theoretical analysis, we studied the influence of elongation on contact angles, breakthrough pressures, and sliding angles on our ultra-stretchable superomniphobic surfaces. We envision that our innovative ML-guided laser ablation protocol to fabricate ultra-stretchable superomniphobic surfaces will pave the way to developing novel and scalable artificial skins, textile dressings, and stretchable electronics.

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