Phonon study of Jahn-Teller distortion and phase stability in NaMnO$_2$ for sodium-ion batteries
Haeyoon Jung, Jiyeon Kim, Sooran Kim

TL;DR
This study uses first-principles phonon calculations to analyze the structural stability and phase transitions of layered NaMnO$_2$ cathode materials, emphasizing the role of Jahn-Teller distortion in sodium-ion batteries.
Contribution
It provides new insights into the phonon stability and Jahn-Teller effects in NaMnO$_2$, highlighting the importance of phonon analysis for understanding cathode material transitions.
Findings
O'3 and P'2 structures with Jahn-Teller distortion are dynamically stable.
Undistorted O3 and P2 structures exhibit imaginary phonon frequencies indicating instability.
Jahn-Teller distortion causes orbital redistribution and band splitting.
Abstract
Cathode materials undergo various phase transitions during the charge/discharge process, and the structural transitions significantly affect the battery performance. Although phonon properties can provide a direct clue for structural stability and transitions, it has been less explored in sodium cathode materials. Here, using the first-principles calculations, we investigate phonon and electronic properties of various layered NaMnO materials, especially focusing on the dependency of the Jahn-Teller distortion of Mn. The phonon dispersion curves show that the O3 and P2 structures with the Jahn-Teller distortion are dynamically stable in contrast to undistorted O3 and P2 structures. The structural instability of O3 and P2 structures is directly observed from the imaginary phonon frequencies, as so-called phonon soft modes, whose corresponding displacements are from O…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvancements in Battery Materials · Machine Learning in Materials Science · Surface and Thin Film Phenomena
