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MM: Fachverband Metall- und Materialphysik
MM 56: Materials for Storage and Conversion of Energy VI (joint session MM/KFM)
MM 56.5: Talk
Thursday, March 21, 2024, 12:45–13:00, C 264
Anharmonic Lattice Dynamics of Solid-State Ion Conductors from Machine-Learning Molecular Dynamics — •Takeru Miyagawa, Manuel Grumet, Namita Krishnan, Waldemar Kaiser, and David A. Egger — Physics Department, TUM School of Natural Sciences, Technical University of Munich, Germany
Solid-state ionic conductors (SSICs) are playing an important role in electrification of transport and energy industries. Recent studies suggested that the host lattice dynamics play a critical role in the ionic conduction mechanisms [1]. Several SSICs exhibit anharmonic lattice vibrations taking mobile ions into anharmonic regions of their potential energy surface [2, 3]. Here, we investigate the role of anharmonic host lattice vibrations and their impact on the conduction of mobile cations in SSICs by using machine-learning molecular dynamics (MLMD). Particularly, we focus on different classes of superionic conductors that all exhibit anharmonicities: AgI, a strongly disordered Ag-conductor [2]; Na3PS4, a Na vacancy conductor [3]; and Li10GeP2S12, showing concerted Li migration [4]. Our results demonstrate the potential of MLMDs in understanding coupled host lattice-mobile ion dynamics and show guidelines for the design of novel SSICs with higher ionic conductivities.
[1] Zhang; Nazar Nat. Rev. Mater. 7, 389-405 (2022). [2] Brenner et al. Phys. Rev. Mater. 4, 115402 (2020). [3] Brenner et al J. Phys. Chem. Lett. 13, 25, 5938-5945 (2022). [4] Fang; Jena, Nat. Comm. 13, 2078 (2022)
Keywords: Solid-state ionic conductor; Molecular dynamics; Anharmonicity; Machine learning force field