@article{34821,
  author = {Partha Paul and Eric J McShane and Eric M Colclasure and Nitash P Balsara and David E Brown and Chuntian Cao and Bor-Rong Chen and Parameswara R Chinnam and Yi Cui and Eric J Dufek and Donal P Finegan and Samuel Gillard and Wenxiao Huang and Zachary M Konz and Robert Kostecki and Fang Liu and Sean D Lubner and Ravi S Prasher and Molleigh B Preefer and Ji Qian and Marco-Tulio Fonseca Rodrigues and Manuel Schnabel and Seoung‐Bum Son and Venkat Srinivasan and Hans-Georg Steinrück and Tanvir R Tanim and Michael F Toney and Wei Tong and Francois Usseglio‐Viretta and Jiayu Wan and Maha Yusuf and Bryan D McCloskey and Johanna Nelson Weker},
  title = {A Review of Existing and Emerging Methods for Lithium Detection and Characterization in Li‐Ion and Li‐Metal Batteries},
  abstract = {<p><span>Whether attempting to eliminate parasitic Li metal plating on graphite (and other Li-ion anodes) or enabling stable, uniform Li metal formation in ‘anode-free’ Li battery configurations, the detection and characterization (morphology, microstructure, chemistry) of Li that cannot be reversibly cycled is essential to understand the behavior and degradation of rechargeable batteries. In this review, various approaches used to detect and characterize the formation of Li in batteries are discussed. Each technique has its unique set of advantages and limitations, and works towards solving only part of the full puzzle of battery degradation. Going forward, multimodal characterization holds the most promise towards addressing two pressing concerns in the implementation of the next generation of batteries in the transportation sector (viz. reducing recharging times and increasing the available capacity per recharge without sacrificing cycle life). Such characterizations involve combining several techniques (experimental- and/or modeling-based) in order to exploit their respective advantages and allow a more comprehensive view of cell degradation and the role of Li metal formation in it. It is also discussed which individual techniques, or combinations thereof, can be implemented in real-world battery management systems on-board electric vehicles for early detection of potential battery degradation that would lead to failure.</span></p>},
  year = {2021},
  journal = {Advanced Energy Materials},
  volume = {11},
  pages = {2100372},
  month = {03/2021},
  issn = {1614-6832},
  doi = {10.1002/aenm.202100372},
  language = {eng},
}