Available on-demand - F.EN04.26.20
Computational Investigation of Earth Abundant Electrolytes of the M3AlP2 (M = Li, Na) System
Arthur Youd1,Daniel Davies1,Christopher Savory1,David Scanlon1
University Collego London1
Earth abundant electrolytes are a vital paradigm in the realisation of truly sustainable solid-state rechargeable batteries. These materials must maintain a tight balancing act between chemical stability, ion mobility and earth abundance. Recent work has shown promising Li ion mobility in phosphidoaluminates owing to the favourable alignment of AlP4 tetrahedra.1 The final characterisation of this as well as the exact Li migration mechanism is not fully understood. The sodium analogue (Na3AlP2) shares significant structural features which may make it a possible candidate for sodium ion electrolytes.2
In this study, we have performed ab initio Density Functional Theory calculations on M3AlP2 (M = Li, Na) to predict and critically assess their ion transport properties. The methodology makes use of an array of python-based tools to generate structures (pymatgen)3, defective supercells (bsym)4 and create workflows (atomate)5 to perform high throughput calculations. Ab initio molecular dynamics (AIMD) and nudged elastic band (NEB) approaches are employed to examine the ion mobility and diffusion coefficients of M3AlP2 with a view to assessing its suitability as an electrolyte. The thermodynamic stability is window is calculated with electronic alignment relative to cathodes. Dynamic stability of these electrolytes is investigated with phonon analysis within the harmonic approximation.
While quantitative analysis of AIMD informs the extent of diffusion, qualitative directional analysis gives insights into the preferred route of diffusion as well as help propose specific mechanisms for ion diffusion. Through multiple AIMD runs we can extract temperature dependent behaviour and compare with microscopic activation barriers from NEB. These results allow us to elucidate the favourable mechanism in the phosphidoaluminates and thus draw conclusions on promising future developments for solid state electrolytes in both Li-ion and Na-ion batteries.
1. T. M. F. Restle, C. Sedlmeier, H. Kirchhain, W. Klein, G. Raudaschl-Sieber, V. L. Deringer, L. van Wüllen, H. A. Gasteiger, T. F. Fässler, Angew. Chem. Int. Ed. 2020 , 59 , 5665.
2. Somer, M., Carrillo-Cabrera, W., Peters, E.-M., Peters, K., & von Schnering, H. G. (1995). Crystal structure of trisodium catena-di-μ-phosphidoaluminate, Na3AlP2, Zeitschrift für Kristallographie - Crystalline Materials, 210(10), 777-777.
3. Shyue Ping Ong, William Davidson Richards, Anubhav Jain, Geoffroy Hautier, Michael Kocher, Shreyas Cholia, Dan Gunter, Vincent L. Chevrier, Kristin A. Persson, Gerbrand Ceder, Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis, Computational Materials Science, Volume 68, 2013, Pages 314-319.
4. Bsym: Morgan, (2017), bsym: A basic symmetry module, Journal of Open Source Software, 2(16), 370.
5. Mathew, K., Montoya, J. H., Faghaninia, A., Dwarakanath, S., Aykol, M.,Tang, H., Chu, I., Smidt, T., Bocklund, B., Horton, M., Dagdelen, J., Wood, B., Liu, Z.-K., Neaton, J., Ong, S. P., Persson, K., Jain, A., Atomate: A high-level interface to generate, execute, and analyse computational materials science workflows. Comput. Mater. Sci. 139, 140–152 (2017).