Unknown

Dataset Information

0

Synergy of Binary Substitutions for Improving the Cycle Performance in LiNiO2 Revealed by Ab Initio Materials Informatics.


ABSTRACT: We explore LiNiO2-based cathode materials with two-element substitutions by an ab initio simulation-based materials informatics (AIMI) approach. According to our previous study, a higher cycle performance strongly correlates with less structural change during the charge-discharge cycles; the latter can be used for evaluating the former. However, if we target the full substitution space, full simulations are infeasible even for all binary combinations. To circumvent such an exhaustive search, we rely on Bayesian optimization. Actually, by searching only 4% of all of the combinations, our AIMI approach discovered two promising combinations, Cr-Mg and Cr-Re, whereas each atom itself never improved the performance. We conclude that the synergy never emerges from a common strategy restricted to combinations of "good" elements that individually improve the performance. In addition, we propose a guideline for the binary substitutions by elucidating the mechanism of the crystal structure change.

SUBMITTER: Yoshida T 

PROVIDER: S-EPMC7288707 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

altmetric image

Publications

Synergy of Binary Substitutions for Improving the Cycle Performance in LiNiO<sub>2</sub> Revealed by Ab Initio Materials Informatics.

Yoshida Tomohiro T   Maezono Ryo R   Hongo Kenta K  

ACS omega 20200601 22


We explore LiNiO<sub>2</sub>-based cathode materials with two-element substitutions by an ab initio simulation-based materials informatics (AIMI) approach. According to our previous study, a higher cycle performance strongly correlates with less structural change during the charge-discharge cycles; the latter can be used for evaluating the former. However, if we target the full substitution space, full simulations are infeasible even for all binary combinations. To circumvent such an exhaustive  ...[more]

Similar Datasets

| S-EPMC4668360 | biostudies-literature
| S-EPMC5496472 | biostudies-literature
| S-EPMC4937409 | biostudies-literature
| S-EPMC4706572 | biostudies-literature
| S-EPMC7689883 | biostudies-literature
| S-EPMC3667492 | biostudies-literature
| S-EPMC7296020 | biostudies-literature
| S-EPMC9936577 | biostudies-literature
| S-EPMC3781394 | biostudies-literature
| S-EPMC5204207 | biostudies-literature