Robots and AI Could Optimize Lithium-Ion Batteries

New automated system could quickly find new battery chemistries much faster than with brute-force human testing

2 min read
battery icon with lightning bolts on sides
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Cutting-edge electronics, including electric vehicles and the latest smartphones, all depend on batteries whose chemistries are still largely developed manually by trial and error. Now, a new study reveals that artificial intelligence can direct robots in rapidly finding advanced new battery formulations. A team of scientists detailed their findings online 27 September in the journal Nature Communications.

The conventional techniques for developing new batteries can take years because researchers have to experiment with many possible components. This is complicated by the need to achieve multiple competing goals, such as longer life, greater capacity, faster charging, and improved safety.

“The kind of lithium-ion battery you might find in a Tesla EV may have one primary salt—typically lithium hexafluorophosphate—as well as two or three liquid solvents in which the salt is dissolved and one or two additives that are secret,” says Jay Whitacre, an energy technologist at Carnegie Mellon University who was co-senior author of the Nature Communications paper. “There are many compelling potential combinations of all these components, potentially with multiple salts, five or six or more solvents, multiple additives, which can be incredibly complicated to rifle through.”

In the new study, researchers sought to accelerate battery development by coupling a robotics platform named Clio with an AI called Dragonfly in order to find the best combination of battery components in an autonomous manner.

“It’s like putting peanut butter and chocolate together,” Whitacre says. “I’m the experimentalist who has always wanted to find a way to mix up chemicals for batteries in an automated way,” whereas study co-senior author Venkat Viswanathan “is the computer-modeling machine-learning person who wanted to take people out of the loop.”

In the new study, the system autonomously experimented with lithium hexafluorophosphate salt and the solvents ethylene carbonate, ethyl-methyl carbonate, and dimethyl carbonate. (In a lithium-ion battery, a salt dissolves in one or more solvents to form a liquid electrolyte. Lithium ions move from one electrolyte to another to carry electric charge.)

The robotic system used pumps to inject various combinations of solvents into pouches with a lithium nickel manganese cobalt oxide cathode and a graphite anode. “There wasn’t a person telling the system what to do; the system decided what to do,” Whitacre says.

In 42 experiments over two working days, the system autonomously identified six electrolytes that enable faster charging than a conventional electrolyte composition. This approach hit upon the new chemistry six times as fast as it would likely have taken to discover it via a random search.

The researchers note their system likely performs more experimental measurements per day than an average human operator and uses about 30 percent as many lab materials. In the future, they suggest their system may prove 20 to 1,000 times as efficient as people doing this work.

The sole goal of these experiments was a faster-charging battery. However, the scientists note this system can also pursue multiple objectives simultaneously.

“As we dive more and more into this project, we’re aiming at true exploration and discovery with more complicated possible combinations of electrolytes placed into many test cells to see what does and does not work,” Whitacre says.

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Will AI Steal Submarines’ Stealth?

Better detection will make the oceans transparent—and perhaps doom mutually assured destruction

11 min read
A photo of a submarine in the water under a partly cloudy sky.

The Virginia-class fast attack submarine USS Virginia cruises through the Mediterranean in 2010. Back then, it could effectively disappear just by diving.

U.S. Navy

Submarines are valued primarily for their ability to hide. The assurance that submarines would likely survive the first missile strike in a nuclear war and thus be able to respond by launching missiles in a second strike is key to the strategy of deterrence known as mutually assured destruction. Any new technology that might render the oceans effectively transparent, making it trivial to spot lurking submarines, could thus undermine the peace of the world. For nearly a century, naval engineers have striven to develop ever-faster, ever-quieter submarines. But they have worked just as hard at advancing a wide array of radar, sonar, and other technologies designed to detect, target, and eliminate enemy submarines.

The balance seemed to turn with the emergence of nuclear-powered submarines in the early 1960s. In a 2015 study for the Center for Strategic and Budgetary Assessment, Bryan Clark, a naval specialist now at the Hudson Institute, noted that the ability of these boats to remain submerged for long periods of time made them “nearly impossible to find with radar and active sonar.” But even these stealthy submarines produce subtle, very-low-frequency noises that can be picked up from far away by networks of acoustic hydrophone arrays mounted to the seafloor.

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