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Metal-organic framework formation by [Fe4S4] clusters offers promising electrochemical performance.
- Source :
-
Computational Materials Science . Jan2025, Vol. 247, pN.PAG-N.PAG. 1p. - Publication Year :
- 2025
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Abstract
- [Display omitted] • Application of [Fe 4 S 4 ] to metal-ion batteries is studied using DFT calculations. • Embedding [Fe 4 S 4 ]2+ clusters in metal–organic frameworks generates high voltage. • The electrochemical performance is based on an intercalation mechanism. • Among the screened material pairs, Zn2+-BMOF shows the highest efficiency. [Fe 4 S 4 ] clusters have served as molecular batteries and charge transfer centers in many biosystems. However, their potential as electrode materials has been overlooked amidst the ever-increasing studies on various materials in the search for efficient battery compositions. To evaluate their electrochemical efficiency as electrode materials, we focused on the use of two important oxidation states, [Fe 4 S 4 ]2+ and [Fe 4 S 4 ]⁰, in a series of Li-, Na-, K-, Mg-, Ca-, and Zn-ion batteries. We also assessed the effect of metal–organic framework (MOF) formation on their performance by studying [Fe 4 S 4 ]2+-1,4-benzenedithiolate MOF (BMOF) and its carboxylate-based counterpart (CMOF). Our model-based Density Functional Theory (DFT) calculations indicated that oxidation of the cluster to [Fe 4 S 4 ]2+ and MOF formation significantly improve the electrochemical efficiency of the cluster. Among the studied electrode materials and metals, the BMOF combination with Mg0 and Zn2+ presented the best electrochemical performance. Notably, our periodic calculations indicated an open circuit voltage of 4.32 V for the Zn2+-BMOF system, suggesting a promising performance for BMOF compared to other cathode/negative electrode materials. Our atomic and electronic structure analyses indicated that intercalation is the underlying electrochemical mechanism. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09270256
- Volume :
- 247
- Database :
- Academic Search Index
- Journal :
- Computational Materials Science
- Publication Type :
- Academic Journal
- Accession number :
- 181444894
- Full Text :
- https://doi.org/10.1016/j.commatsci.2024.113551