Reduced Friction: Inspired by Nature

Python-regius

Darvin’s theory of evolution is widely held concept which states that all the life has evolved from a common ancestor: fruits, animals, trees, flowers. During the gradual process of evolution, beneficial random genetic mutations in simple creatures accumulated and resulted in more complex species. The process of accumulation of only beneficial mutations, called natural selection, adapts species to the surrounding conditions, so that they perform optimally. Therefore, nature offers a good starting point for design solutions, containing the result of a long evolutionary adaption process.

There are many examples of successful application of nature inspired solutions in engineering. Genetic algorithm is a famous and powerful optimization tool, Velcro fasteners, were inspired by seed burrs of the Burdock plant and self-cleaning paints are based on Lotus effect. A team of researchers at Karlsruhe Institute of Technology have found a way to reduce friction in metallic systems using the patterns of the skin of Phyton regius snake and the sand skink lizard (Scincus scincus). These animals have a scale-like surface structure albeit of different pattern size and it was used as a base for texturing.

A typical bearing steel was laser textured to transfer the natural surface structure to the surface of the metal and the friction tests were performed. It was found, that this bio-inspired surface texture reduces friction forces by more than 40%, in unlubricated conditions. These results can be applied in nanoelectromechanical and micro-positioning and other tribological systems which cannot be lubricated.

Interestingly, the friction in lubricated contacts was increased by scale-like sirface texturing. This means, that the natural selection has optimized the snakes skin only for the dry environment and great care has to be taken to benefit from the biological solutions, containing the long evolution outcomes.

The details of the research can be found in article by Christian Greiner and Michael Schäfer.

Credit for the image: wikipedia.

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