Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

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, Christopher Wolverton

TL;DR

The paper addresses the challenge of designing high-capacity, cobalt-free LiMO$_2$ cathodes by embracing cation disorder and developing a computational framework that links short- and long-range ordering tendencies to Li diffusion. It builds a large HT-DFT database across 6,182 compositions and four Li-orderings, introduces phase-stability and SRO descriptors, and calibrates thresholds with experimental validation to predict favorable combinations. A proof-of-concept in the Li-Cr-Fe-O system demonstrates that disorder engineering plus Li-excess can yield high initial capacities up to $320\ \text{mAhg}^{-1}$, with 234 mAhg$^{-1}$ achievable without Li excess, highlighting the practical potential of descriptor-guided design for scalable, cobalt-free cathodes. The work offers a scalable path to screen thousands of multicomponent chemistries, enabling rapid discovery of high-capacity, diffusion-friendly ordering in LiMO$_2$ cathodes with potentially lower cost and broader material availability.

Abstract

Newly designed Li-ion battery cathode materials with high capacity and greater flexibility in chemical composition will be critical for the growing electric vehicles 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 the strict 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 which possess specific, tailored types of both long- and short-range orderings, which can ensure both phase stability and Li diffusion. However, the combinatorial complexity associated with local cation environments impedes the development of general design guidelines for favorable orderings. Here we propose ordering design frameworks from 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, validated through multiple successful 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 mAhg$^{-1}$ 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 known to us.

Tailored ordering enables high-capacity cathode materials

TL;DR

The paper addresses the challenge of designing high-capacity, cobalt-free LiMO cathodes by embracing cation disorder and developing a computational framework that links short- and long-range ordering tendencies to Li diffusion. It builds a large HT-DFT database across 6,182 compositions and four Li-orderings, introduces phase-stability and SRO descriptors, and calibrates thresholds with experimental validation to predict favorable combinations. A proof-of-concept in the Li-Cr-Fe-O system demonstrates that disorder engineering plus Li-excess can yield high initial capacities up to , with 234 mAhg achievable without Li excess, highlighting the practical potential of descriptor-guided design for scalable, cobalt-free cathodes. The work offers a scalable path to screen thousands of multicomponent chemistries, enabling rapid discovery of high-capacity, diffusion-friendly ordering in LiMO cathodes with potentially lower cost and broader material availability.

Abstract

Newly designed Li-ion battery cathode materials with high capacity and greater flexibility in chemical composition will be critical for the growing electric vehicles market. Cathode structures with cation disorder were once considered suboptimal, but recent demonstrations have highlighted their potential in LiMO chemistries with a wide range of metal combinations M. By relaxing the strict requirements of maintaining ordered Li diffusion pathways, countless multi-metal compositions in LiMO may become viable, aiding the quest for high-capacity cobalt-free cathodes. A challenge presented by this freedom in composition space is designing compositions which possess specific, tailored types of both long- and short-range orderings, which can ensure both phase stability and Li diffusion. However, the combinatorial complexity associated with local cation environments impedes the development of general design guidelines for favorable orderings. Here we propose ordering design frameworks from 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, validated through multiple successful synthesis and characterization experiments, we not only demonstrate the design of LiCrFeO, showcasing initial charge capacity of 234 mAhg and 320 mAhg in its 20% Li-excess variant LiCrFeO, but also present the elemental ordering statistics for 32 elements, informed by one of the most extensive first-principles studies of ordering tendencies known to us.

Paper Structure

This paper contains 19 sections, 1 equation, 17 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Computational Ordering Design Framework
  3. Methods
  4. Composition Design
  5. Special Quasirandom Structures
  6. High-throughput Density-Functional Theory (HT-DFT) Calculations
  7. Synthesis
  8. Electrochemical Evaluation
  9. XRD Measurement
  10. Results and Discussion
  11. Phase stability descriptors
  12. Li diffusion and SRO descriptors
  13. High-capacity cathode design
  14. Conclusion
  15. Supporting Note 1 : Plotting distribution curves
  16. ...and 4 more sections

Figures (17)

  • Figure 1: Li-M ordering arrangements in rocksalt-type structures and computational ordering descriptors. a. Common Li-M ordering arrangementsurban2014configurationalwolverton1998cationhewston1987survey in rocksalt-type structures with M=M$^1_{0.5}$M$^2_{0.25}$M$^3_{0.25}$ compositions, which serve as the four structural configurations used for deriving our phase stability and SRO descriptors. b. Composition stabilities on each arrangement predicted by phase stability descriptors F, compared to OQMD convex hulls (E = 0 reference.) The availability of Li diffusion is predicted by the SRO descriptor, which is defined by the energy difference between Spinel-like and $\gamma$-LiFeO$_2$ Li-M ordering arrangements with M=M$^1_{0.5}$M$^2_{0.25}$M$^3_{0.25}$ sublattice disordering. For more information on the correspondence between the SRO descriptor and Li diffusion, see Figure \ref{['fig:DRX_SROD']} and its corresponding section.
  • Figure 2: Phase stability descriptors F and elemental statistics for stable DRX and Layered phases. a. F$_{\mathrm{DRX}}$ and b. F$_{\mathrm{Layered}}$ distributions of 6,182 compositions from the database. The black curve represents the F distribution of all compositions. (Continued on next page.)
  • Figure 3: (cont.) Individual curves for each element depict distributions calculated from compositions containing that specific element, demonstrated with examples of Fe, Ni, Ti, and Mn. Gray dotted vertical lines are threshold values of F$_{\mathrm{DRX}}$ and F$_{\mathrm{Layered}}$ empirically derived from synthesized compounds shown in subfigures d and e, with the compositions in the shaded area classified as stable in DRX/Layered when synthesized at 1273K. Additional details on F value distributions for all 32 elements are provided in the Supporting Information. c. Periodic-table-style heat map for the percentages classified as stable DRX (upper right triangle) and Layered (bottom left triangle) phases, illustrating the influence of each element on stabilizing target phases. The color bar is configured to drastically change around the value of stable percentage from “All” compositions, 2.0% for DRX and 2.1% for Layered phases. d. XRD spectra of synthesized compositions. Peaks corresponding to the DRX phases (space group Fm-3m) are labeled with blue lines and plane indices displayed nearby. Similarly, peaks associated with Layered phases (space group R-3m) are indicated with orange lines and their corresponding plane indices. Other peaks identified as impurity phases are not labeled to maintain clarity. e. F$_{\mathrm{DRX}}$ and F$_{\mathrm{Layered}}$ values of synthesized compositions, with icons indicating their experimentally observed phases as determined by XRD analysis in subfigure d. Blue circles indicate the DRX phase, orange diamonds represent the Layered phase, and red crosses represent impurity phases. The compositions are categorized into distinct regions based on empirically derived threshold values, 7 meV/atom for F$_{\mathrm{DRX}}$ and -11 meV/atom for F$_{\mathrm{Layered}}$. The F values in this plot are calculated using higher-fidelity E$_{\mathrm{hull}}$ examined by additional fine ionic relaxations specifically for candidate materials to further enhance structural optimizations. More details of this fine ionic relaxation examination on E$_{\mathrm{hull}}$ are discussed in the Supporting Information.
  • Figure 4: Scattering plots of F$_{\mathrm{Layered}}$ and F$_{\mathrm{Spinel\text{-}like}}$ values of all 6,182 compositions. The lower blue dotted line is the F$_{\mathrm{Layered}}$ = F$_{\mathrm{Spinel\text{-}like}}$ and the upper red dotted line is from linear regression. In the cluster description, Layered and Spinel-like orderings exhibit identical pair and three-body correlations, diverging only starting from four-body correlations wolverton1998cation. With this similarity, it is expected that the energies of these two phases are highly correlated. Still, 68.4% of the compositions are above the blue dot line, and the average F$_{\mathrm{Layered}}$ values are lower than F$_{\mathrm{Spinel\text{-}like}}$ by 5.1 meV/atom. This energy difference is closely related to four-body interactions in cluster expansions.
  • Figure 5: SRO descriptor and value distributions. a. Distributions of local $\mathrm{Li}_{x}\mathrm{M}_{4-x}$ configurations in four Li-M arrangements. (Continued on next page.)
  • ...and 12 more figures