Manufacturing
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Our expertise in this area focuses on optimizing the wide array of manufacturing parameters that go into maximizing the performance of full cells. Our capabilities focus on using high throughput parallel testing of full cells to navigate massive optimization parameter spaces such as electrolyte composition, formation protocols, and active material composition. Through high throughput testing, machine learning, and data-driven optimization of experiments, we rapidly optimize for specific performance metrics such as fast charging, cycle life, and calendar life.
Faculty
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Associate Professor of Materials Science and Engineering, of Energy Science and Engineering, of Photon Science, and Senior Fellow at the Precourt Institute for Energy
