December 1 - 6, 2024
Boston, Massachusetts
Symposium Supporters
2024 MRS Fall Meeting & Exhibit
EN08.04.04

Design Principles for Sodium Superionic Conductors

When and Where

Dec 3, 2024
3:00pm - 3:15pm
Hynes, Level 3, Ballroom C

Presenter(s)

Co-Author(s)

Shuo Wang1,2,Jiamin Fu3,Xueliang Sun3,2,Yifei Mo1

University of Maryland1,Eastern Institute of Technology, Ningbo2,University of Western Ontario3

Abstract

Shuo Wang1,2,Jiamin Fu3,Xueliang Sun3,2,Yifei Mo1

University of Maryland1,Eastern Institute of Technology, Ningbo2,University of Western Ontario3
Motivated by the high-performance solid-state lithium batteries empowered by lithium superionic conductors as solid electrolytes, sodium superionic conductor materials share great promises for enabling novel sodium batteries with high energy, low cost, and sustainability. Designing sodium superionic conductors with high ionic conductivities is a great challenge, hindered by the lack of appropriate design principles. Here, by studying the structures and diffusion mechanisms of Li-ion versus Na-ion in solids, we reveal that fast Na<sup>+</sup> Na-ion conductors exhibit the unique structural features of face-sharing high-coordination sites. By employing the new design principle based on this feature, we discover over a dozen of new families of fast Na-ion conductors in oxides, sulfides, and halides. Remarkably, a new chloride family of Na-ion conductors Na<sub>x</sub>M<sub>y</sub>Cl<sub>6</sub> (M = Lanthanide) with UCl<sub>3</sub>-type structure is discovered and experimentally confirmed with high Na ionic conductivities &gt; 1 mS/cm at room temperature. Our results not only guide the future development of fast Na-ion conductors for new sodium batteries, but also consolidate and generalize different design principles for fast ion conductors, which can be further extendable and applicable to develop other types of ion-conducting materials for many different energy applications.

Keywords

diffusion

Symposium Organizers

Kelsey Hatzell, Vanderbilt University
Ying Shirley Meng, The University of Chicago
Daniel Steingart, Columbia University
Kang Xu, SES AI Corp

Session Chairs

Miaofang Chi
Peter Nellist

In this Session