Project Description

Researchers will use high-throughput computational screening combined with in-depth ab initio dynamics simulations to discover and optimize new classes of Li-ion solid inorganic electrolytes to enable safe high-energy batteries. The project will advance the computational technology for predicting and analyzing new inorganic Li-ion conductors. By computationally screening a large subspace of inorganic materials, researchers will identify a list of promising candidates that will be synthesized and characterized by experimental partners. The effort will advance the state of the art of intensive computational discovery and understanding of new classes of electrolyte materials, with potential relevance to battery systems, fuel cells, and sensors.Batteries are critical for enabling the widespread introduction of hybrid and electric vehicles, as well as compact stationary storage of energy from renewable source. There are several factors that prevent wide commercialization of large Li-ion batteries: their high cost, insufficient energy density, and poor safety. In the last few years significant interest has appeared in Li-sulfur and Li-air batteries, which promise far higher energy densities than Li-ion batteries, but also require Li metal anodes and consequently protection layers. There is great need for a solid layer to protect the Li metal surface to allow development of safe high-energy batteries, which is where new solid inorganic Li-ion conductors can have a tremendous impact on energy storage technology.

Allocation History

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