Simulating quadrupolar NMR dynamics in solid electrolyte Li 10 GeP 2 S 12

The Journal of Chemical Physics, vol. 164

Abstract

Quadrupolar solid-state nuclear magnetic resonance (NMR) spectroscopy is an excellent tool to trace lithium (Li) ion diffusion in solid electrolytes due to its sensitivity to dynamics over timescales from nanoseconds to seconds. However, the structural and dynamical complexity of battery materials limits the unambiguous interpretation of experimental data. Fast ionic motion can partially average experimentally observable quantities, leaving the underlying distribution of electric field gradients (EFGs) experimentally inaccessible and, therefore, the measured data hard to interpret. In contrast, atomic simulation approaches, while providing the structure-observable relationship, are often constrained to idealized models. Established methods such as density functional theory remain computationally expensive for realistic time and length scales. Here, we show how experimental complexity in the fast-ion conductor Li10GeP2S12 (LGPS) can be approached via a machine-learning (ML) assisted workflow. ML acceleration enables microsecond-scale molecular dynamics (MD) simulations and efficient predictions of EFG tensors via a tensorial model. By time averaging the EFG tensors from the MD trajectory, we compute the temperature dependence of 7Li NMR quadrupolar observables subject to motional narrowing. Our prediction of the quadrupolar coupling of 24 kHz for tetragonal LGPS is in excellent agreement with the experimental value of 23 kHz. Furthermore, we emulate a spin-alignment echo (SAE) experiment in silico and apply the inverse Laplace transform to extract correlation times for ionic motion of Li in different LGPS crystal structures. Finally, we assess whether SAE can differentiate inter-grain vs intra-grain ion dynamics via the orientational dependence of the EFG tensor.

Authors 6

1. Tabea Huss

   Fritz Haber Institute of the Max Planck Society

   Affiliation as printed

   Fritz-Haber Institute of the Max Planck Society 1 , Berlin (DE),

2. Federico Civaia

   Fritz Haber Institute of the Max Planck Society

   Affiliation as printed

   Fritz-Haber Institute of the Max Planck Society 1 , Berlin (DE),

3. S. Kocher

   Forschungszentrum Jülich · Fritz Haber Institute of the Max Planck Society

   Affiliation as printed

   Fritz-Haber Institute of the Max Planck Society 1 , Berlin (DE),

   Institute of Energy Technologies (IET-1), Forschungszentrum Jülich GmbH 2 , Jülich (DE),

4. Karsten Reuter

   Fritz Haber Institute of the Max Planck Society

   Affiliation as printed

   Fritz-Haber Institute of the Max Planck Society 1 , Berlin (DE),

5. Josef Granwehr Aachen Institute of Technical and Macromolecular Chemistry

   Forschungszentrum Jülich · RWTH Aachen University

   Affiliation as printed

   Institute of Energy Technologies (IET-1), Forschungszentrum Jülich GmbH 2 , Jülich (DE),

   Institute of Technical and Macromolecular Chemistry, RWTH Aachen University 3 , Aachen (DE),

6. Christoph Scheurer

   Forschungszentrum Jülich · Fritz Haber Institute of the Max Planck Society

   Affiliation as printed

   Fritz-Haber Institute of the Max Planck Society 1 , Berlin (DE),

   Institute of Energy Technologies (IET-1), Forschungszentrum Jülich GmbH 2 , Jülich (DE),