journal article·2012-10

Local elasticity and adhesion of nanostructures on Drosophila melanogaster wing membrane studied using atomic force microscopy

Ryan Wagner, Barry R. Pittendrigh, Arvind Raman

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Abstract

Abstract Insect wings have a naturally occurring, complex, functional, hierarchical microstructure and nanostructure, which enable a remarkably water-resistant and self-cleaning surface. Insect wings are used as a basis for engineering biomimetic materials; however, the material properties of these nanostructures such as local elastic modulus and adhesion are poorly understood. We studied the wings of the Canton-S strain of Drosophila melanogaster (hereafter referred to as Drosophila) with atomic force microscopy (AFM) to quantify the local material properties of Drosophila wing surface nanostructures. The wings are found to have a hierarchical structure of 10–20 μm long, 0.5–1 μm diameter hair, and at a much smaller scale, 100 nm diameter and 30–60 nm high bumps. The local properties of these nanoscale bumps were studied under ambient and dry conditions with force-volume AFM. The wing membrane was found to have a elastic modulus on the order of 1000 MPa and the work of adhesion between the probe and wing membrane surface was found to be on the order of 100 mJ/m2, these properties are the same order of magnitude as common thermoplastic polymers such as polyethylene. The difference in work of adhesion between the nanoscale bump and membrane does not change significantly between ambient (relative humidity of 30%) or dry conditions. This suggests that the nanoscale bumps and the surrounding membrane are chemically similar and only work to increase hydrophobicity though surface roughening or the geometric lotus effect.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Force Microscopy Techniques and Applications · Adhesion, Friction, and Surface Interactions · Calcium Carbonate Crystallization and Inhibition

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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