Lifeboat Foundation

Energy storage in lithium-sulfur batteries is potentially higher than in lithium-ion batteries but they are hampered by a short life. Researchers from Uppsala University in Sweden have now identified the main bottlenecks in performance.

Lithium-sulfur batteries are high on the wish-list for future batteries as they are made from cheaper and more environmentally friendly materials than lithium-ion batteries. They also have higher energy storage capacity and work well at much lower temperatures. However, they suffer from short lifetimes and energy loss. An article just published in the journal Chem by a research group from Uppsala University has now identified the processes that are limiting the performance of the sulfur electrodes that in turn reduces the current that can be delivered. Various different materials are formed during the discharge/charge cycles and these cause various problems. Often a localized shortage of lithium causes a bottleneck.

“Learning about problems allows us to develop new strategies and materials to improve battery performance. Identifying the real bottlenecks is needed to take the next steps. This is big research challenge in a system as complex as lithium-sulfur,” says Daniel Brandell, Professor of Materials Chemistry at Uppsala University who works at the Ångström Advanced Battery Centre.

In recent decades, machine learning and deep learning algorithms have become increasingly advanced, so much so that they are now being introduced in a variety of real-world settings. In recent years, some computer scientists and electronics engineers have been exploring the development of an alternative type of artificial intelligence (AI) tools, known as diffractive optical neural networks.

Diffractive optical neural networks are deep neural networks based on diffractive optical technology (i.e., lenses or other components that can alter the phase of light propagating through them). While these networks have been found to achieve ultra-fast computing speeds and high energy efficiencies, typically they are very difficult to program and adapt to different use cases.

Researchers at Southeast University, Peking University and Pazhou Laboratory in China have recently developed a diffractive deep neural network that can be easily programmed to complete different tasks. Their network, introduced in a paper published in Nature Electronics, is based on a flexible and multi-layer metasurface array.

Every industry will be affected by quantum computing. They will alter the way business is done and the security systems in place which protect data, how we battle illnesses and create new materials, as well as how we tackle health and climate challenges.

As the race to build the first commercially functional quantum computer heats up, here we discuss a handful of the ways quantum computing will alter our world.

A UK consortium wants to build the world’s largest and longest “drone superhighway,” connecting towns and cities across the United Kingdom.

Also read: 14 amazing drone photos from DJI SkyPixel contest winners

Continue reading “World’s longest 165-mile ‘drone superhighway’ proposed in the UK” »

Star’s mysterious orbit around black hole proves einstein was right all along—again.

The star, known as S2, has a 16-year elliptical orbit. It came near 20 billion kilometers of our black hole, Sagittarius A*, last year. If Isaac Newton’s traditional definition of gravity is correct, S2 should then continue on its previous orbit’s course through space. But it didn’t work.

Continue reading “Star’s Mysterious Orbit Around Black Hole Proves Einstein Was Right— Again” »

When you’re building wearables and glowables, sometimes a flashy rainbow animation is all you need. [Geeky Faye] likes to go a little further, however, and built this impressive necklace that serves to inform on the local air quality.

The necklace consists of a series of Neopixel LED strips, housed within a tidy 3D printed housing made with flexible filament. A dovetail joint makes putting on and removing the necklace a cinch. A TinyPico V2, based on the ESP32, runs the show, as it’s very small and thus perfect for the wearable application. A USB power bank provides power to the microcontroller and LEDs.

Continue reading “Breathe Easy With This LED Air Sensor Necklace” »

Twenty Two Motors. Fifty gears. Eighty Two Hundred RPM. Hundreds of individual pieces, and one sheet of glossy paper cut into a disk. This isn’t a nightmare driven Rube Goldberg machine. Instead, it’s a Lego monstrosity created by [GazR] of [GazR’s Extreme Brick Machines!], and all of these parts are flying in formation for one Lego slicing purpose. In the video below the break, you can see what very well may be the worlds most powerful Lego and Paper table saw.

Starting out with a build that had a mere fourteen motors in a platform that looked quite a lot more like a table saw, [GazR] learned that having only fourteen motors turning a Lego based blade was not a good combination. In the next iteration, the same number of motors were used, but the gearing was increased to bring RPM up, and a Lego toy saw blade took care of cutting duties.

Continue reading “Brick And Motor Table Saw Delivers Paper Cuts On Demand” »

The father of the GIF passes away at the age of 74 after contracting COVID-19.

Atomic clocks are the best sensors mankind has ever built. Today, they can be found in national standards institutes or satellites of navigation systems. Scientists all over the world are working to further optimize the precision of these clocks. Now, a research group led by Peter Zoller, a theorist from Innsbruck, Austria, has developed a new concept that can be used to operate sensors with even greater precision irrespective of which technical platform is used to make the sensor. “We answer the question of how precise a sensor can be with existing control capabilities, and give a recipe for how this can be achieved,” explain Denis Vasilyev and Raphael Kaubrügger from Peter Zoller’s group at the Institute of Quantum Optics and Quantum Information at the Austrian Academy of Sciences in Innsbruck.

For this purpose, the physicists use a method from quantum information processing: Variational quantum algorithms describe a circuit of quantum gates that depends on free parameters. Through optimization routines, the sensor autonomously finds the best settings for an optimal result. “We applied this technique to a problem from metrology—the science of measurement,” Vasilyev and Kaubrügger explain. “This is exciting because historically advances in atomic physics were motivated by metrology, and in turn quantum information processing emerged from that. So, we’ve come full circle here,” Peter Zoller says. With the new approach, scientists can optimize quantum sensors to the point where they achieve the best possible precision technically permissible.