Exploring the Reversibility of Phase Transformations in Aluminum Anodes through Operando Light Microscopy and Stress Analysis

Tianye Zheng, Dominik Kramer, Mohammad H. Tahmasebi, Reiner Mönig, Steven T. Boles

Research output: Journal article publicationJournal articleAcademic researchpeer-review

18 Citations (Scopus)

Abstract

Aluminum is well-known to possess attractive properties for possible use as an anode material in Li-ion batteries (LIBs), but effort is still needed to understand how and why it degrades. Herein, investigations of the delithiation and the re-lithiation processes in Al thin films using an established operando light microscopic platform are pursued. Operando videos highlight that the extraction of Li from the β phase (LiAl) is accompanied by fracture and crack formation leading to the detachment of the α phase (Al) from the rest of the electrode. The evolution of mechanical stress in Al thin film electrodes is tracked and shows severe stress asymmetry as phase transformations progress. Combining with the observations from light and electron microscopy, the mechanical stress during dealloying can be explained by Li solubility with the β phase, formation of cracks and of a highly porous Al nanostructure. Although the results pave a difficult path for utilization of the Al/LiAl/Al (α/β/α) phase transformations in future LIBs, they also suggest excellent opportunities when structural changes can be prevented, which otherwise impact the stability of Al-based electrodes.

Original languageEnglish
Pages (from-to)5910-5920
Number of pages11
JournalChemSusChem
Volume13
Issue number22
DOIs
Publication statusPublished - 20 Nov 2020

Keywords

  • aluminum
  • batteries
  • electrode materials
  • lithium
  • stress

ASJC Scopus subject areas

  • Environmental Chemistry
  • General Chemical Engineering
  • General Materials Science
  • General Energy

Fingerprint

Dive into the research topics of 'Exploring the Reversibility of Phase Transformations in Aluminum Anodes through Operando Light Microscopy and Stress Analysis'. Together they form a unique fingerprint.

Cite this