Boosting Li-Ion Transport in Transition-Metal-Doped Li2SnO3

Theoretical approaches to defect mechanisms and transport properties of compounds used for electrodes and solid-state electrolytes in alkali-ion batteries

The transition from fossil fuels to cleaner energies employing different renewable sources constitutes one of the primary worldwide challenges. The search for appropriate solutions is becoming more urgent in view of the severe consequences of climate change. As for a perspective, stationary energy storage, alkali-ion batteries and hybrid supercapacitors are, among others, considered as efficient and affordable solutions. Alkali-ion batteries have proved to be the most investigated products in the past decade including optimizations for cost, energy density and safety. In this Perspective, a computational approach and its applicability in the inverse material design are presented. This approach includes density functional theory calculations, force field-based determinations and both static and molecular dynamics simulations. As for an illustration, the main properties of a selected series of battery materials, including oxides and sulfides Li2SiO3, Li2SnO3, SrSnO3, and A2B6X13 (A = Li+, Na+, K+; B = Ti4+, Sn4+; X = O2-, S2-), and mixed halide antiperovskite A3OX (A = Li+, Na+; X = Cl-, Br-) are explored in depth using these theoretical approaches. Doping strategies, new dopant incorporation mechanism, treatment with alkali insertion/de-insertion cycle in electrodes, transport properties, as well as thermodynamic stability, are discussed. Theoretical approaches reveal that the oxygen-sulfur exchange in alkali hexatitanates and hexastannates induces remarkable improvement of the required properties for electrode and electrolyte materials. In addition, doping of Li2SiO3 with low Na-concentration enhances the room temperature Li-diffusivity by a reduction of the activation energy. The effects of transition-metal and divalent dopants on the defect chemistry and transport properties of Li2SnO3 are also disclosed. The interstitial trivalent doping mechanism is a friendly synthesis strategy to improve the large-scale diffusion in Li2SnO3. The potential of SrSnO3 as an anode in alkali-ion batteries, and the influence of a particular grain boundary in nanocrystalline antiperovskite A3OX are also revealed by using advanced atomistic simulations. The computational approaches described here provide us with a convenient tool for the determination of the properties of battery materials with high accuracy and for the prediction of characteristics of a new generation of alkali battery materials that could be used in improved technologies.

Correlated factors for Li-ion migration in ionic conductors with the fcc anion sublattice

The development of solid-state electrolytes (SSEs) with high lithium ionic conductivities is critical for the realization of all-solid-state Li-ion batteries. Crystal structure distortions, Li polyhedron volumes, and anion charges in SSEs are reported to affect the energy landscapes, and it is paramount to investigate their correlations. Our works uncover the cooperative effect of lithium site distortions, anion charges, and lattice volumes on Li-ion migration energy barrier in superionic conductors of LiMS2 (M = Sc, Ti, V, Cr, Mn, Fe, Co, and Ni) and Li2MO3 (M = Sc, Ti, V, Cr, Mn, Fe, Co, and Ni). Combined with the Least Absolute Shrinkage and Selection Operator analyses, the volume and Continuous symmetrical methods (CSMs) of Li tetrahedral (Tet) sites appear to have a larger effect on the manipulation of Ea for Li migration, compared to that of Li octahedral (Oct) sites, which is further confirmed by the results from the face-centered cubic (fcc) anion lattice model. For the Tet-Oct-Tet Li migration path, the CSM (the volume of Li site) has a negative (positive) correlation with Ea, while for the Oct-Tet-Oct Li migration paths, opposite correlations have been observed. The understanding of the correlation between site preference, anion charge, lattice volume, and structural distortion as well as the prediction model of Ea in terms of these three factors, namely, C-V-D model, could be useful for the design of solid-state electrolytes with lower activation energy.

John PC. Upper-Bound Energy Minimization to Search for Stable Functional Materials with Graph Neural Networks

The discovery of new materials in unexplored chemical spaces necessitates quick and accurate prediction of thermodynamic stability, often assessed using density functional theory (DFT), and efficient search strategies. Here, we develop a new approach to finding stable inorganic functional materials. We start by defining an upper bound to the fully relaxed energy obtained via DFT as the energy resulting from a constrained optimization over only cell volume. Because the fractional atomic coordinates for these calculations are known a priori, this upper bound energy can be quickly and accurately predicted with a scale-invariant graph neural network (GNN). We generate new structures via ionic substitution of known prototypes, and train our GNN on a new database of 128 000 DFT calculations comprising both fully relaxed and volume-only relaxed structures. By minimizing the predicted upper-bound energy, we discover new stable structures with over 99% accuracy (versus DFT). We demonstrate the method by finding promising new candidates for solid-state battery (SSB) electrolytes that not only possess the required stability, but also additional functional properties such as large electrochemical stability windows and high conduction ion fraction. We expect this proposed framework to be directly applicable to a wide range of design challenges in materials science.

Defects, diffusion and dopants in Li8SnO6

Octalithium tin (IV) oxide (Li₈SnO₆) is an important electrode material considered for lithium ion batteries (LIBs) because of its high lithium content. We employed atomistic simulations to examine the intrinsic defects, diffusion of Li-ions together with their migration energies and solution of potential dopants in Li₈SnO₆. The most thermodynamically favourable intrinsic defect is the Li Frenkel which increases the concentration of Li vacancies needed for the vacancy mediated diffusion of Li-ions in Li₈SnO₆. The calculated activation energy of migration of Li-ions (0.21eV) shows that the Li-ion conductivity in this material can be very fast. Promising isovalent dopants on the Li and Sn sites are Na and Ti, respectively. Doping of Ga on the Sn site can facilitate the formation of Li interstitials as well as oxygen vacancies in Li₈SnO₆. While the concentration of Li interstitials can enhance the capacity of this material, oxygen vacancies together with Li interstitials can lead to the loss of Li₂O in Li₈SnO₆.

Enhanced Li-ion transport in divalent metal-doped Li2SnO3

The improvement of Li-ion transport properties and doping engineering in Li-ion batteries are currently active research topics in the search for next-generation energy storage devices. In this theoretical work, the intrinsic defect formation and transport properties of divalent metal-doped Li2SnO3, which is being considered as an electrode and coating electrode material, are explored using atomistic simulations. Defect formation simulations reveal that all divalent dopants (Zn, Sc, Cd and Eu) occupy the Li site with charge compensation through Li vacancies. Molecular dynamics simulations show that the divalent dopants significantly reduce the activation energy for ionic diffusion and conduction compared to the undoped sample. The effects of both grains and grain boundaries on the Li-ion transport properties are investigated. Our calculated results demonstrate a marked improvement in the properties of Li2SnO3 that can be achieved either in current commercial and next-generation Li-ion battery technologies through divalent doping in mono- and polycrystalline Li2SnO3 samples.