Li batteries In Silico: the role of interfaces

PAZ, SERGIO A.; P. V. SARAVIA; GUILLERMINA LUQUE; M. GAVILAN; DANIEL BARRACO; PATRICIO VÉLEZ; J. VELAZCO; EZEQUIEL PEDRO MARCOS LEIVA

Antofagasta

Workshop; 7th International Workshop on Lithium, Industrial Minerals and Energy.; 2020

Lithium batteries are nowadays the most commonly used rechargeable batteries due to their high specific capacity, small size and varied shapes, with high performance and reliability, specially adapted to the applications of the consumers of electronic industry. At first sight, it could appear that the most important properties to consider by these energy accumulation systems are the bulky ones, since Li storage is achieved in many cases in massive materials. However, this phenomenon involves always the transfer of ions and electrons across interfases, and in many cases, kinetic issues are critical to achieve effective energy storage.In the present talk we address by means of computer simulations different materials that can be found in lithium batteries as electrodes, and discuss the interactions of lithium with the interphases showing that these types of studies are essential to understand and achieve and efficient performance of these materials. The figure below illustrates different systems containing Li where interface effects are important: core-shell formation in anodic materials (a), the occurrence of phase boundaries in graphite (b) and the adsorption of polysulfides on a doped graphene surface. Figure: Illustration of Li-ion storage systems where surfaces play a role: (a) formation of a core-shell structure simulated by kinetic Monte Carlo(KMC). Blue: Li+ diffusing ions, yellow: deposited Li+ ions, white: metallic contact (b) occurrence of a phase boundary for Li+ insertion in graphite, as simulated by KMC. Green spheres denote Li+ ions (c) Adsorption of a L2S6 polysulfide on a graphene surface doped with a B atom. Keywords: lithium batteries, computational simulations, interactionsAcknowledgments: G. Luque thanks grants PIP CONICET 11220150100624CO, PUE/2017 CONICET, FONCYT PICT-2015-1605, and SECyT of the Universidad Nacional de Córdoba. Support byCCAD-UNC and GPGPU Computing Group, Y-TEC, and an IPACgrant from SNCAD-MinCyT, Argentina, are also gratefully appreciated.