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Combined ab-initio and topological approach for prediction of new materials for energy storage

Scientific organization
Samara University
Academic degree
Candidate of science
scientific researcher
Scientific discipline
New materials, Manufacturing technologies & Processes
Combined ab-initio and topological approach for prediction of new materials for energy storage
Modern technologies demand high-efficiency portable electric energy sources. The development of new materials for energy storage is very urgent task (taking into account the lack of lithium for large-scale application). We apply combined topological and ab-initio approach to predict new functional materials for solid state batteries. Here we present our recent results of DFT and topological calculations of different types of ion-conductive materials. The combination of topological and quantum-mechanical investigations allows to achieve the most comprehensive results.
Solid State Physics, Material Modelling, Solid State Batteries, DFT, Ionic conductivity.

The existing technologies demand to portable energy sources. Such sources should be safe, cheap, effective, compact and environment-friendly. During past two decades lithium-ion batteries provide impressive advances in mobile electronics and electric vehicles [1,2]. This technology’s jump was possible due to remarkable properties of lithium-conductive materials, especially high energy density. At the same time, the researchers have been exploring a lot of new materials  for energy-storage applications and a routes to increase solid-state battery performance (specific energy, cyclability etc.) [3-8]. From the other side, battery safety stays a cornerstone for designing of new materials. One more reason affected on the searching is a lack of lithium for large-scale applications (for example, grid-based energy storage system for renewable energy sources) [9]. This leads to active exploring of sodium, potassium, aluminium-conducting materials as a promising candidates for replace Li-conducting ones.

The modern computational methods provide an excellent opportunity for numerical investigation of materials. Density functional theory – based methods (also called as first-principles, or ab-initio methods) are able to predict a key properties of materials, including ion mobility, electronic structure, cell voltage, thermal stability and voltage profiles [10]. DFT-based calculations open so called «high-throughput» searching when a lot of materials are explored computationally without resource-consuming experiments. But, instead of resource-consuming experiments, some DFT calculations demands processor time-consuming calculations. To minimize such calculations, we divide analysis of conductivity on two steps: i) initially we perform fast topological analysis of selected structures to determine the possibility of migration and, ii) we perform DFT calculations for the structures which have the appropriate channels for migration, according to step (i).

Here we used Vienna Ab-initio Simulation Package (VASP) [11] as the basic code for DFT calculations. To compute activation energy barriers, nudged elastic band (NEB) method [12] was used as it is implemented in VASP package. Topological analysis of possible migration channels was performed by using the ToposPro geometrical tiling analysis [13].

The following compounds were investigated using combined topological and DFT-based approaches: LiCoO2, Li2CoPO4F, LiVPO4F, KFeO2, NaFePO4, NaMnAsO4, NaFeVF7, Al2(WO4)3, AlFe2O4 and some others. The migration maps, activation energy barriers and electronic bands were computed. Usually structures have a few possible migration pathways and we calculated the activation energies for each of them. An examples of such calculations are presented at Figures 1 and 2.

Figure 1. Curved trajectories for Li ion migration in Li2CoPO4F according to NEB calculations. (a),(b),(c),(d) and (e) panels corresponds to five non-equivalent paths. Panel (f) represent all five channels in the supercell.




Figure 2. Curved trajectories for K ion migration in KFeO2 according to NEB calculations. Top panel represents all non-equivalent paths (marked by different colors). Bottom panel represent DFT results for activation energy values for each path.



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