High-throughput computational screening of cathode materials for Li-O2 battery

Abstract

Despite the tremendous specific energy of Li-O2 energy storage technology in theory, the practically achieved values are still inferior to compete with conventional Li-ion batteries. A key limitation is the inability to use thick gas diffusion electrodes made of carbonaceous materials because of the passivation by discharge products. In this study, a computational methodology for searching alternative positive electrode (cathode) materials for Li-O2 batteries based on density functional theory is proposed. The methodology includes a three-stage screening with a sequential selection of the best candidates according to their stability, band gap (electronic conductivity), normalized surface energies (stability in a highly porous form), and oxygen adsorption energies (resistance towards oxidation and passivation). The methodology is applied for the AxBy series of binary compounds with A = Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Y, Zr, Nb, Mo, Ru, Ag, Mg, Al and B = B, C, N, O, Si, S and benchmarked with graphite. As a result, 33 potential compounds with low normalized surface energies are identified out of 2800 initial structures taken from the material database. It is shown that only several oxides can be stable towards surface oxidation among the selected compounds and thus considered as potential cathode materials.