(Invited) Designing Optimal Electrolytes and Interfaces in Li-S Batteries
Authors: Rajput Nav Nidhi , Atwi Rasha 
Published: July 2021

The inter- and intra-atomic interactions of molecular species in complex electrolyte solutions affect the solvation structure and dynamical in bulk solution and at electrode/electrolyte interface. A fundamental understanding of such intricate structure-property relationships in complex solutions will allow designing optimal materials for next generation energy storage devices. A major breakthrough in battery materials is required to meet the ever-increasing proliferation of portable electronic devices, electric vehicles and their variants, as well as the need for incorporating renewable energy resources into the main energy supply [1]. In this context, lithium-sulfur (Li-S) batteries attract attention owing to their very high energy density (2,600 Wh kg-1) and specific capacity (1,675 mAh g-1) and significantly lower weight and cost, compared to lithium-ion batteries (LIBs) [2]. Fully packaged, it is expected that future Li-S batteries can operate at close to 500 Wh kg-1, which is more than twice the energy density of LIBs (200 Wh kg-1) [3]. The problem of realizing the expected high energy density is defined by several issues including the dissolution of Li-Polysulfide (PS) species into the electrolyte, insulating properties of sulfur and Li-PS species, and volume change at the cathode [4]. Overcoming these challenges requires a fundamental understanding of the interplay between events scaling over wide spatial and temporal scales, and accurate prediction of electrode and electrolyte properties to obtain design metrics for new improved materials. In this talk, I will present how we are utilizing a multi-scale-data-driven approach to gain mechanistic insight into Li-S battery by combining density functional theory (DFT) with molecular dynamics (MD) simulations. I will describe our group’s newly developed computational workflow and analysis codes for generating data with high-throughput DFT and MD simulations within the framework of the Materials Project infrastructure [5]. I will discuss usage of these tools to mitigate dissolution of LiPS species by altering the atomistic interactions between electrode and electrolyte components through functionalizing the cathode material. This approach guides and accelerates our rational selection of functional groups that exhibit strong affinity with both the cathode material and LiPS moieties from a bigger set of available candidates through fully automated DFT calculations. We use the selected candidates in detailed MD studies to understand the effect of various electrolyte variables (components, PS chain length, salt concentration) on structural and dynamical properties at the functionalized interface [6, 7]. The approach allows for creating a database of well-characterized materials to be used in machine learning-based methods as well as for testing computationally identified structures in experiments. This work provides crucial information to alleviate the dissolution of PS species during cycling, which is the main reason for rapid capacity decay in Li-S batteries.
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