(Invited) Computational Design of Electrolytes for Lithium-Ion Batteries

Wednesday, October 14, 2015: 08:00
101-B (Phoenix Convention Center)
S. P. Ong, Z. Deng (University of California, San Diego), B. Radhakrishnan (University of California, San Diego), L. Cheng (Argonne National Lab), X. Qu (Joint Center for Energy Storage Research (JCESR)), R. Assary (Materials Science Division, Argonne National Laboratory), A. Jain (Lawrence Berkeley National Laboratory), N. N. Rajput (Joint Center for Energy Storage Research), K. A. Persson (Joint Center for Energy Storage Research (JCESR)), and L. Curtiss (Materials Science Division, Argonne National Laboratory)
The electrolyte has today become a critical bottleneck in the drive toward high performance rechargeable lithium-ion batteries. Comprising organic solvents and LiPF6, current commercial electrolytes are flammable and have limited electrochemical windows of up to 4.5V. In this talk, we will discuss recent efforts in the application of first principles calculations to design novel solid and liquid electrolytes for lithium-ion batteries. We will show how first principles techniques can be used to predict important electrolyte design requirements such as ionic conductivity, electrochemical stability and phase stability. Such predictive capabilities may be used to guide the experimental realization of better performing electrolytes, for instance, by suggesting potential chemistry modifications or composition tuning strategies. The automation of these techniques in high-throughput leads to the development of multi-property electrolyte databases, which can then be screened for novel electrolyte candidates as well as mined for electrolyte design rules using machine learning techniques. Specific chemistries discussed will include the thiophosphate and anti-perovskite solid electrolytes, and quinoxaline-based molecules.