Engineering Compounds for the Recovery of Critical Elements from Slags: Melt Characteristics of Li 5 AlO 4 , LiAlO 2 , and LiAl 5 O 8 .

Engineered artificial minerals (EnAMs) are the core of a new concept of designing scavenger compounds for the recovery of critical elements from slags. It requires a fundamental understanding of solidification from complex oxide melts. Ion diffusivity and viscosity play vital roles in this process. In the melt, phase separations and ion transport give rise to gradients/increments in composition and, with it, to ion diffusivity, temperature, and viscosity. Due to this complexity, solidification phenomena are yet not well understood. If the melt is understood as increments of simple composition on a microscopic level, then the properties of these are more easily accessible from models and experiments. Here, we obtain these data for three stoichiometric lithium aluminum oxides. LiAlO 2 is a promising EnAM for the recovery of lithium from lithium-ion battery pyrometallurgical processing. It is obtained through the addition of aluminum to the recycling slag melt. The high temperature properties spanning from below to above the liquidus temperature of three stoichiometric Li-Al-Oxides: Li 5 AlO 4 , LiAlO 2 , and LiAl 5 O 8 are determined using molecular dynamic simulations. The compounds are also synthesized via the sol-gel route. The Li + ion exhibits the largest diffusivity. They are quite mobile already below the liquidus temperature, i.e., for LiAlO 2 at T = 1700 K, the diffusion coefficient of the lithium ion equals D = 3.0 × 10 -9 m 2 s -1 . The other ions Al 3+ and O 2- do not move considerably at that temperature. The diffusivity of Li + is largest in the lithium-rich compound Li 5 AlO 4 with D = 32 × 10 -9 m 2 s -1 at 2500 K. The lower the viscosity, the higher the lithium content. The Li 5 AlO 4 exhibits a viscosity of η = 2.2 mPa s at 1328 K which matches well with the experimentally determined 2.5 mPa s at this temperature. The viscosity of LiAlO 2 at 1800 K is more than two times higher. These data sets can help to describe the melts on a microscopic level and understand how the melt properties will change due to gradients in the Li/Al concentration.