, a materials scientist at PNNL. So researchers have to test many different molecules and their solubility to find out which would best work in a flow battery.
Investigating each molecule and its many different variations is costly and time-consuming, so PNNL researchers are working on a solution called the digital twin battery—a machine-learning model that can simulate a battery’s behavior so researchers can plug in digital versions of the molecules to test. With a digital model that uses artificial intelligence, scientists can test the characteristics of a targeted organic molecule at an accelerated speed and reduced cost.
“We’re really just at the tip of the iceberg of seeing what opportunities we can offer. We want to bring people to GSL and help educate them on all aspects of battery life, whether they manufacture batteries or not,” Paiss said.At GSL, researchers like Reed and Wang and safety advisors like Paiss will be able to collaborate on understanding emerging battery technologies to help accelerate a decarbonized future.
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