journal article·2025-12Open access

Tailored Ordering Enables High‐Capacity Cathode Materials

Tzu‐chen Liu, Adolfo Salgado‐Casanova, So Yubuchi, Bianca Baldassarri, Muratahan Aykol, Jun Yoshida, Hisatsugu Yamasaki, Yizhou Zhu, Steven B. Torrisi, Chris Wolverton

Advanced Energy Materials· Volume 15· Issue 47

Abstract

Abstract Novel Li‐ion battery cathode materials with high capacity and greater compositional flexibility are essential for the growing electric vehicle market. Cathode structures with cation disorder were once considered suboptimal, but recent demonstrations have highlighted their potential in Li 1 + x M 1 − x O 2 chemistries with a wide range of metal combinations M. By relaxing requirements of maintaining ordered Li diffusion pathways, countless multi‐metal compositions in LiMO 2 may become viable, aiding the quest for high‐capacity cobalt‐free cathodes. A challenge presented by this freedom in composition space is designing compositions that possess specific, tailored types of both long‐ and short‐range orderings, which can ensure both phase stability and Li diffusion. Ordering design frameworks are proposed based on computational ordering descriptors, which in tandem with low‐cost heuristics and elemental statistics can be used to simultaneously achieve compositions that possess favorable phase stability as well as configurations amenable to Li diffusion. Utilizing this computational framework, accompanied by illustrative synthesis and characterization experiments, we not only demonstrate the design of LiCr 0.75 Fe 0.25 O 2 , showcasing initial charge capacity of 234 and 320 mAhg −1 in its 20% Li‐excess variant Li 1.2 Cr 0.6 Fe 0.2 O 2 , but also present the elemental ordering statistics for 32 elements, informed by one of the most extensive first‐principles studies of ordering tendencies.
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Research context

OpenAlex topics: Advancements in Battery Materials · Semiconductor materials and devices · Machine Learning in Materials Science

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Materials Science and Engineering Northwestern University Evanston IL USA

Battery Research Division Toyota Motor Corporation Susono Shizuoka Japan

Energy & Materials Division Toyota Research Institute Los Altos CA USA

Advanced Materials Engineering Division Toyota Motor Corporation Susono Shizuoka Japan

Department of Materials Science and Engineering Westlake University

Funding

Toyota Research Institute · National Energy Research Scientific Computing Center · Quest High Performance Computing

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