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Author Spotlight: Exploring Self-Assembled MOF-Polymer Composites
Published on: June 14, 2024
A predictive framework for the design and fabrication of icephobic polymers
Kevin Golovin1,2, Anish Tuteja1,2,3,4
1Department of Materials Science and Engineering, University of Michigan, Ann Arbor, MI 48109, USA.
Abstract:
Ice accretion remains a costly, hazardous concern worldwide. Icephobic coatings reduce the adhesion between ice and a surface. However, only a handful of the icephobic systems reported to date reduce the ice adhesion sufficiently for the facile and passive removal of ice, such as under its own weight or by mild winds. Most of these icephobic surfaces have relied on sacrificial lubricants, which may be depleted over time, drastically raising the ice adhesion. In contrast, surfaces that use interfacial slippage to lower their adhesion to ice can remain icephobic indefinitely. However, the mechanism of interfacial slippage, as it relates to ice adhesion, is largely unexplored. We investigate how interfacial slippage reduces the ice adhesion of polymeric materials. We propose a new, universally applicable framework that may be used to predict the reduction in the adhesion of ice to surfaces exhibiting interfacial slippage. This framework allows one to rationally engender icephobicity in essentially any polymeric system, including common thermoplastics. Hence, we present several new, extremely icephobic systems fabricated from a wide range of materials, including everyday engineering plastics and sustainable, natural oils.
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However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

