By: Science Daily
An algorithm lets machines teach themselves how to recognize landscapes, even amid the changing seasons.
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By: Science Daily
New research suggests fumed silica nanoparticles (FSNs) can be used to help improve the performance of warm mix asphalt (WMA).
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New research develops a framework to understand the choices an electronic waste recycler has to make and the role that digital fraud prevention could have in preventing dishonest recycling practices.
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Scientists have developed a new technique that could revolutionize medical imaging procedures using light.
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A research team has developed bio-inks for biosensors that could help localize critical regions in tissues and organs during surgical operations.
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By: Science Daily
We’ve seen robots take to the air, dive beneath the waves and perform all sorts of maneuvers on land. Now, researchers are exploring a new frontier: the ground beneath our feet. Taking their cues from plants and animals that have evolved to navigate subterranean spaces, they’ve developed a fast, controllable soft robot that can burrow through sand.
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By: Science Daily
A team of scientists has developed millimeter-sized robots that can be controlled using magnetic fields to perform highly maneuverable and dexterous manipulations. This could pave the way to possible future applications in biomedicine and manufacturing.
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Researchers have created a first-of-its-kind metalens – a metamaterial lens – that can be focused using voltage instead of mechanically moving its components.
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By: Science Daily
Acoustic waves in gases, liquids, and solids usually travel at an almost constant speed of sound. Rotons are an exception: their speed of sound changes significantly with the wavelength, it is also possible that the waves travel backwards. Researchers are studying the possibilities of using rotons in artificial materials. These metamaterials might be used in the future to manipulate or direct sound in ways that have never been possible before.
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By: Science Daily
Research, development, and production of novel materials depend heavily on the availability of fast and at the same time accurate simulation methods. Machine learning, in which artificial intelligence autonomously acquires and applies new knowledge, will soon enable researchers to develop complex material systems in a purely virtual environment. How does this work, which applications will benefit?
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