Computational Materials Group (CMG) lead by Prof. D. Aksyonov is developing new electrode materials for metal-ion batteries using computational methods. The supreme ingredient of success is a deep understanding of the material’ properties on the atomic and electronic level, which can be achieved with modeling. 

Main directions:

1. Computational design of solid/solid and solid/liquid interfaces for metal-ion batteries (Applied Surface Science 537 (2021) 147750)
2. Advanced study of defects in electrodes for metal-ion batteries (Inorg. Chem. 2021, 60, 5497−5506)
3. Understanding cation migration barriers in oxide and phosphate based cathode materials with DFT calculations (Computational Materials Science 154 (2018) 449–458)
4. Development of computational framework SIMAN for high-throughput DFT calculations (https://github.com/dimonaks/siman)

Current projects:

1. Development of advanced electrochemical energy storage systems with the help of directional design of local structure and microstructure of electrode materials.

2. Effect of the electrode/electrolyte interface structure on the charge transfer kinetics: сomputer simulation and experimental verification 

3. Improving the stability and ionic conductivity of all-solid-state batteries interfaces: computational modeling and experimental validation

Finished projects:

1. To advanced high capacity layered electrode materials for lithium-ion batteries through the understanding of oxidation-reduction processes at the atomic level
2. Atomic-level Understanding of Interface Structure Evolution and Engineering Guidelines for Next Li-ion Solid State Batteries
3. Search for new materials for gas electrodes of lithium- and sodium-oxygen current sources: predictive computer simulation and experimental testing

Figure 1. Easier formation of surface antisite defect in layered oxides discovered with DFT+U oxides. From Applied Surface Science 537 (2021) 147750

Figure 2. Combined DFT + X-Ray + Neutron diffraction refined hydrogen defects in LiFePO₄ cathode material. From Inorg. Chem. 2021, 60, 5497−5506

Figure 3. Li diffusion pathways for three classes of crystal structures: (a) spinel, (b) olivine, and (c) tavorite. From Computational Materials Science 154 (2018) 449–458

Figure 4. Change of charge density in Na₂FePO₄ after extraction of sodium (black spheres). From J. Am. Chem. Soc. 2018, 140, 3994−4003.