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Tools and Applications of the Schrödinger Suite for Battery Materials Simulations
The design and manufacturing of safer, less expensive, and highly efficient energy storage devices is a critical challenge in a wide variety of industries including the automotive, aviation, and energy sectors. Atomistic-scale materials modeling for battery applications has become an essential tool for the development of novel device components - cathodes, anodes, and electrolytes - that support higher power density, capacity, rate capability, faster charging, and improved degradation resilience. In this presentation, we will review Schrödinger’s Materials Science software platform that provides a powerful atomistic-scale modeling solution for comprehensive analysis of battery materials. The review will include the latest examples in physics-based and machine-learning predictions of the key materials properties including, but not limited to, ion diffusion, mechanical response, and electrochemical response in electrodes and electrolytes, as well as dielectric properties of potential electrolyte compounds.


Jun 8, 2021 09:00 AM in Beijing, Shanghai

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Yuling An
Product Manager of Machine Learning and Informatics for Materials Science @Schrödinger