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In a leap for battery research, machine learning gets scientific smarts

Scientists have taken a major step forward in harnessing machine learning to accelerate the design for better batteries: Instead of using it just to speed up scientific analysis by looking for patterns in data, as researchers generally do, they combined it with knowledge gained from experiments and equations guided by physics to discover and explain a process that shortens the lifetimes of fast-charging lithium-ion batteries.

It was the first time this approach, known as “scientific machine learning,” has been applied to cycling, said Will Chueh, an associate professor at Stanford University and investigator with the Department of Energy’s SLAC National Accelerator Laboratory who led the study. He said the results overturn long-held assumptions about how lithium-ion batteries charge and discharge and give researchers a new set of rules for engineering longer-lasting batteries.

The research, reported today in Nature Materials, is the latest result from a collaboration between Stanford, SLAC, the Massachusetts Institute of Technology and Toyota Research Institute (TRI). The goal is to bring together foundational research and industry know-how to develop a long-lived electric vehicle battery that can be charged in 10 minutes.

Israeli 5-minute battery charge aims to fire up electric cars

From flat battery to full charge in just five minutes—an Israeli start-up has developed technology it says could eliminate the “range anxiety” associated with electric cars.

Ultra-fast recharge specialists StoreDot have developed a first-generation lithium-ion that can rival the filling time of a standard car at the pump.

“We are changing the entire experience of the driver, the problem of ‘range anxiety’… that you might get stuck on the highway without energy,” StoreDot founder Doron Myersdorf said.

A new type of supply-chain attack with serious consequences is flourishing

A new type of supply chain attack unveiled last month is targeting more and more companies, with new rounds this week taking aim at Microsoft, Amazon, Slack, Lyft, Zillow, and an unknown number of others. In weeks past, Apple, Microsoft, Tesla, and 32 other companies were targeted by a similar attack that allowed a security researcher to execute unauthorized code inside their networks.

The latest attack against Microsoft was also carried out as a proof-of-concept by a researcher. Attacks targeting Amazon, Slack, Lyft, and Zillow, by contrast, were malicious, but it’s not clear if they succeeded in executing the malware inside their networks. The npm and PyPi open source code repositories, meanwhile, have been flooded with more than 5000 proof-of-concept packages, according to Sonatype, a firm that helps customers secure the applications they develop.

“Given the daily volume of suspicious npm packages being picked up by Sonatype’s automated malware detection systems, we only expect this trend to increase, with adversaries abusing dependency confusion to conduct even more sinister activities,” Sonatype researcher Ax Sharma wrote earlier this week.

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