Bulletin of the American Physical Society
2023 APS March Meeting
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session K28: Computational Design, Understanding and Discovery of Novel Materials III
3:00 PM–6:00 PM,
Tuesday, March 7, 2023
Room: Room 220
Sponsoring
Unit:
DMP
Chair: Mauro Del Ben, LBNL; Rodrigo Freitas, MIT
Abstract: K28.00010 : Li vs. Na-based Solid-State Batteries: a Multiscale Modeling methodology in link to experiments*
5:12 PM–5:24 PM
Presenter:
Mahmoud ATTIA
(French Atomic Energy and Alternative Energies Commission)
Authors:
Mahmoud ATTIA
(French Atomic Energy and Alternative Energies Commission)
Jean-Paul CROCOMBETTE
(CEA, DEN, SRMP, Gif-sur-Yvette, France)
Said Yagoubi
(Paris-Saclay University, CEA, CNRS, NIMBE, 91191 Gif-sur-Yvette Cedex, France)
Thibault Charpentier
(Paris-Saclay University, CEA, CNRS, NIMBE, 91191 Gif-sur-Yvette Cedex, France)
backs, liquid organic-based electrolytes are the ones most commonly used in commercial batteries. They are not only dangerous and less efficient but also degrade faster which decreases their lifetime for long-term applications. Hence the necessity for a safer and longer-lived alternative for batteries is a must. To this end, SSEs are now at the forefront of all materials, as they combine factors of safety (non-flammable), high energy density, efficiency, lower cost, and ease of fabrication. Among them, doped – Lithium Lanthanum Zirconium Oxide (LLZO) is considered of the most promising ceramics serving this purpose. Herein, we aim to model Lithium diffusion mechanisms and its respective spectroscopic properties (NMR and Electrochemical Impedance Spectroscopy (EIS)) using multiscale simulation approaches by harnessing both (i) short-time and length scales (from DFT and ab-initio Molecular Dynamics) and (ii) long-time and length scales (from classical MD and Kinetic Monte Carlo) to define a multi-scale methodology for understanding the impact of doping have on Li+1 mobility in LLZO by linking the simulations data to the microscopic diffusion measurements from experiments (NMR and EIS). Our aim is to develop a Kinetic Monte Carlo model, parameterized with inputs from MD simulations (both classical and ab-initio) capable of predicting NMR properties such as 7Li NMR lineshapes and nuclear relaxation times. Jump analysis and density-based clustering approaches are employed to analyze Li-ion trajectories. Additionally, standard DFT-GIPAW calculations are performed for predictions of Magic-Angle Spinning-NMR spectra of 27Al in LLAZO (Al-doped LLZO). By adopting the same methodology, Sodium diffusion in Na Super Ionic CONductors (NASICON) and Sc+3 – doped NASICON have been investigated.
*ATTIA, M. is supported by the CEA NUMERICS program, which has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 800945.
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