Electrolytes for Enabling Rechargeable Lithium Metal Batteries

There is a growing need to develop cheap and efficient means of energy storage for electrification of transportation and harnessing solar and wind energy associated

with intermittency in order to meet the goal of decarbonization. Among the various energy storage options, lithium (Li) batteries have revolutionized portable electronics

and emerged as the frontrunner for transportation and grid storage. The high energy density, long life and stringent safety requirements of transportation and grid storage

have made it challenging to use the current state of the art Li-ion batteries. In this regard, two major directions have been explored: optimization of the current Li-ion

battery and development of batteries based on new materials (beyond Li-ion). The slow pace of growth of energy density of current Li-ion batteries (7-8% per year) has made

it necessary to follow the second direction and develop new materials for batteries. Among the different approaches towards increasing the energy density, replacing the

currently used anode (graphite) with Li metal is crucial for obtaining energy densities > 500 kWh/kg. Enabling the Li metal batteries has proved challenging due to a

variety of reasons. The first is the uneven electrodeposition of Li on the metal anode with conventional liquid electrolytes during charging which may cause the growth of

dendrites leading to short circuit. The growth of dendrites causes more fresh Li surface to be exposed to the electrolyte resulting in the consumption of electrolyte and Li in side reactions. Further, the electrodeposition of Li results in volume expansion at the anode which requires careful management of interfacial stresses to prevent cracking

and degradation of active material. In this thesis, I explore the role of electrolytes in tackling various challenges associated with Li metal batteries. I develop design rules for solid electrolytes and organic liquid crystalline electrolytes for suppressing dendrite growth in Li metal batteries. Solid

electrolytes have been explored as viable candidates for enabling Li metal batteries in the context of mechanically blocking dendrite growth. In addition to the previously

discovered region of pressure-driven stability which requires high shear modulus materials for dendrite suppression, I find the existence of a density-driven stability region where dendrite suppression can happen through soft solid electrolytes. The conditions for stability are reversed from organic polymer to inorganic solid electrolytes due to a

vast change in the molar volume of Li ions in these electrolytes. Using these design rules, I perform a screening of several thousand inorganic solids using machine learning

as candidates for solid electrolytes and find over twenty interfaces involving six solid electrolytes that can be used for dendrite-free Li metal batteries. Liquid crystalline

electrolytes are a class of liquid electrolytes exhibiting the orientational order of the molecules. Most molecules of this class have a rod-like anisotropic shape which causes

them to point along the same direction in case of nematic liquid crystals. I study the growth of a Li metal anode surface under electrodeposition with a liquid crystalline electrolyte using a phase-field model. I find that molecules with sufficient anchoring energy can suppress dendrite growth as demonstrated by the suppression metrics. I then investigate multiphase inorganic solids: the components of the elusive solid electrolyte interphase and their role in ion transport of Li. These are common even in liquid electrolytes and single solid electrolyte batteries due to the formation of several

decomposition products at the interfaces with the electrodes. The key phenomena explored are the role of the interface in ion conduction and defect stability. Finally, isotope effects due to the presence of two stable Li isotopes Li⁶ and Li⁷ in any natural sample containing Li are explored. The equilibrium isotope fractionations and kinetic isotope effects are calculated using ab initio methods.