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New machine learning methods bring insights into how lithium ion batteries degrade, and show it’s more complicated than many thought.

Lithium-ion batteries lose their juice over time, causing scientists and engineers to work hard to understand that process in detail. Now, scientists at the Department of Energy’s SLAC National Accelerator Laboratory have combined sophisticated machine learning algorithms with X-ray tomography data to produce a detailed picture of how one battery component, the cathode, degrades with use.

The new study, published this month in Nature Communications, focused on how to better visualize what’s going on in cathodes made of nickel-manganese-cobalt, or NMC. In these cathodes, NMC particles are held together by a conductive carbon matrix, and researchers have speculated that one cause of performance decline could be particles breaking away from that matrix. The team’s goal was to combine cutting-edge capabilities at SLAC’s Stanford Synchrotron Radiation Lightsource (SSRL) and the European Synchrotron Radiation Facility (ESRF) to develop a comprehensive picture of how NMC particles break apart and break away from the matrix and how that might contribute to performance losses.

“Once a chip is designed, adding security after the fact or making changes to address newly discovered threats is nearly impossible,” explains a DARPA spokesperson.

In their latest analysis, first presented at a seminar in March, the LHCb physicists found that several measurements involving the decay of B mesons conflict slightly with the predictions of the standard model of particle physics—the reigning set of equations describing the subatomic world. Taken alone, each oddity looks like a statistical fluctuation, and they may all evaporate with additional data, as has happened before. But their collective drift suggests that the aberrations may be breadcrumbs leading beyond the standard model to a more complete theory.

“For the first time in certainly my working life, there are a confluence of different decays that are showing anomalies that match up,” said Mitesh Patel, a particle physicist at Imperial College London who is part of LHCb.

The B meson is so named because it contains a bottom quark, one of six fundamental quark particles that account for most of the universe’s visible matter. For unknown reasons, the quarks break down into three generations: heavy, medium, and light, each with quarks of opposite electric charge. Heavier quarks decay into their lighter variations, almost always switching their charge, too. For instance, when the negatively charged heavy bottom quark in a B meson drops a generation, it usually becomes a middleweight, positively charged “charm” quark.

Microsoft is laying off more than 50 journalists to replace them with AI for Microsoft News and MSN. It’s part of a bigger push to rely on AI for news curation on its homepages and Microsoft’s Edge browser.

Humans are on the one hand capable of mass genocide, and on the other hand, great self-sacrifice. Why are we capable of such extremes? We talked about this with Robert Sapolsky, professor of biology and neurology at Stanford University and recipient of a MacArthur Foundation genius grant.

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Launched in 2013, the Gaia satellite has been scanning the sky to measure the positions, distances and motions of more than one billion stars in our galaxy, the Milky Way. The goal of the mission is to create the most detailed galactic map ever made, in order to investigate the Milky Way’s past and future history like never before.

The animation below shows the satellite as it scans great circles around the sky. Eventually, the sky is unfolded to reveal the view of the Milky Way and neighboring galaxies, based on measurements of nearly 1.7 billion stars from the second Gaia data release. The map shows the total brightness and colour of stars observed by Gaia in each portion of the sky between July 2014 and May 2016. Brighter regions indicate denser concentrations of especially bright stars, while darker regions correspond to patches of the sky where fewer bright stars are observed. In the middle of the image, the Galactic center appears vivid and teeming with stars.

Continue reading “Gaia Satellite Scans the Sky to Measure Positions and Motions of 1.7 Billion Stars [Video]” »

Diamonds are remarkable. Most form deep within Earth, 62 miles or more beneath our feet and are brought to the surface in powerful explosive eruptions. Yet researchers looking at the 2012–13 eruption of Tolbachik on the Kamchatka Peninsula in Russia found tiny diamonds in the volcanic debris. This was not one of those powerful explosions but a massive series of lava flows. So why were there diamonds showing up unexpectedly?

The “easiest” way to form diamonds is taking carbon and exposing it to the immense pressure within Earth’s mantle. Then they get coughed up with other chunks of rock from the mantle in these giant explosive eruptions called kimberlites. They’re named after one of the world’s most famous and productive diamond mines in Kimberley, South Africa. The places where we find most diamonds today are from the rocks created by these eruptions, found in places like northern Canada and Arkansas. Sometimes, glaciers or rivers have moved the diamonds from their sources, but they can be traced back to their original volcano sources.

There hasn’t a kimberlite eruption in recent human history. The most recent known kimberlite eruption might have happened 10,000 to 20,000 years ago in Tanzania, and that is controversial. The last confirmed kimberlite erupted 30 million years ago in the Democratic Republic of the Congo. Both of those places (and the locations of most kimberlite eruptions) are old continental areas called “cratons,” away from active tectonic zones like volcanic arcs.

Electric VTOL air taxis are one of the great emerging technologies of our time, promising to unlock the skies as traffic-free, high-speed, 3D commuting routes. Much quieter and cheaper than helicopter travel, they’ll also run on zero-local-emission electric power, and many models suggest they’ll cost around the same per mile as a ride share.

Eventually, the market seems to agree, they’ll be pilotless automatons, even cheaper and more reliable than the earliest piloted versions. Should the onboard autopilot computers get confused, remote operators will take over and save the day as if they’re flying a Mavic drone, and every pilot gone will be an extra passenger seat in the sky.

Large numbers of eVTOL air taxis will change the way cities and lifestyles are designed. Skyports atop office buildings, train stations and last-mile transport depots will encourage multi-mode commuting. Real estate in scenic coastal areas might boom as people swap 45 minutes crawling along in suburban traffic for 45 minutes of 120 mph (200 km/h) air travel, and decide to live further from the office.

An increasingly likely catastrophe can cause major disruptions in space flight and our daily lives.