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Large Organic Polar Molecules Tailored Electrode Interfaces for Stable Lithium Metal Battery.

  • Published In: Angewandte Chemie, 2024, v. 136, n. 19. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Li, Zhendong; Chen, Zhenlian; Sun, Nannan; Wang, Deyu; Yao, Xiayin; Peng, Zhe 3 of 3

Abstract

Lithium (Li) metal batteries (LMBs) are deemed as ones of the most promising energy storage devices for next electrification applications. However, the uneven Li electroplating process caused by the diffusion‐limited Li+ transportation at the Li metal surface inherently promotes the formation of dendritic morphology and instable Li interphase, while the sluggish Li+ transfer kinetic can also cause lithiation‐induced stress on the cathode materials suffering from serious structural stability. Herein, a novel electrolyte designing strategy is proposed to accelerate the Li+ transfer by introducing a trace of large organic polar molecules of lithium phytate (LP) without significantly altering the electrolyte structure. The LP molecules can afford a competitive solvent attraction mechanism against the solvated Li+, enhancing both the bulk and interfacial Li+ transfer kinetic, and creating better anode/cathode interfaces to suppress the side reactions, resulting in much improved cycling efficiency of LMBs. Using LP‐based electrolyte, the performance of LMB pouch cell with a practical capacity of ~1.5 Ah can be improved greatly. This strategy opens up a novel electrolyte designing route for reliable LMBs. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Angewandte Chemie. 2024/05, Vol. 136, Issue 19, p1
  • Document Type:Article
  • Subject Area:Science
  • Publication Date:2024
  • ISSN:0044-8249
  • DOI:10.1002/ange.202400876
  • Accession Number:176988832
  • Copyright Statement:Copyright of Angewandte Chemie is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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