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ROBO SPACE
Synthetic two-sided gecko's foot could enable underwater robotics
by Staff Writers
Washington DC (SPX) Apr 27, 2017


File image.

Geckos are well known for effortlessly scrambling up walls and upside down across ceilings. Even in slippery rain forests, the lizards maintain their grip. Now scientists have created a double-sided adhesive that copies this reversible ability to stick and unstick to surfaces even in wet conditions.

They say their development, reported in ACS' Journal of Physical Chemistry C, could be useful in underwater robotics, sensors and other bionic devices.

Inspired by geckos' natural ability to attach and release their feet from surfaces as slick as glass, scientists have made a number of adhesives that can similarly stick and unstick with changes in temperature, light or magnetic field, but mostly in dry conditions. One promising approach to expanding this to underwater scenarios involves hydrogels that can swell and shrink in response to different acidity levels and other conditions.

These volume differences change the gels' friction and stickiness levels. Feng Zhou, Daniele Dini and colleagues recently developed a method to integrate nanostructured hydrogel fibers on an inorganic membrane.

The material's friction and stickiness levels changed with pH even when wet. The researchers wanted to further expand on this strategy to make the adhesive work on two sides. The researchers first made the inorganic membrane double-faced and then added the hydrogel nanofibers on both sides.

Testing showed that the material exhibited ultra-high friction and adhesion in an acidic liquid (pH of 2), and would rapidly switch to a state of ultra-low friction and stickiness when a basic solution (pH of 12) was added. Additionally, the two sides of the material can stick and slide independently of each other.

ROBO SPACE
Human prejudices sneak into artificial intelligence systems
Princeton NJ (SPX) Apr 19, 2017
In debates over the future of artificial intelligence, many experts think of the new systems as coldly logical and objectively rational. But in a new study, researchers have demonstrated how machines can be reflections of us, their creators, in potentially problematic ways. Common machine learning programs, when trained with ordinary human language available online, can acquire cultural bi ... read more

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