Automotive applications require a battery life-time of more than 10 years. However, the life-time of Li-ion cells is limited by various aging effects. In order to improve battery life-time, these aging mechanisms have to be well characterized and understood. Post-Mortem analysis provides insights into various aging mechanisms by complimentary methods.
Here, we give an overview on glow discharge optical emission spectroscopy (GD-OES) which we adapted for analysis of Li-ion batteries in the last six years [1–4]. GD-OES is able to record depth profiles of anodes from the surface to the current collector within few hours (single sided coating up to 100 µm thickness). GD-OES can detect all elements relevant for Post-Mortem analysis of Li-ion cells. Specifically, over the years we established calibrations for Li, C, P, O, Si, and Cu [1–4]. The results were critically cross-checked by complementary methods such as SEM, EDX, ICP-OES, and Raman spectroscopy.
It turns out that different aging mechanisms affect mostly the anode surface as evident by surface peaks, where cyclable Li is irreversibly bound. For example, in the case of Li deposition, the surface peak is well in accordance with simulations by Hein and Latz .
Valuable insights by GD-OES on following aging mechanisms will be presented:
(i) SEI growth on graphite anodes 
(ii) Li deposition/plating and their inhomogeneities on graphite anodes 
(iii) Si dissolution from Si/C composite anodes 
(iv) Cu dissolution and re-deposition on graphite anodes after over-discharge to 0V .
 T. Waldmann et al., J. Electrochem. Soc. 162 (2015) A1500, https://dx.doi.org/10.1149/2.0411508jes.
 N. Ghanbari et al., J. Phys. Chem. C. 120 (2016) 22225, https://dx.doi.org/10.1021/acs.jpcc.6b07117.
 K. Richter et al., J. Phys. Chem. C. 123 (2019) 18795, https://dx.doi.org/10.1021/acs.jpcc.9b03873.
 M. Flügel et al., ChemPhysChem 21 (2020), 2047, https://dx.doi.org/10.1002/cphc.202000333.
 S. Hein, A. Latz, Electrochimica Acta. 201 (2016) 354. https://dx.doi.org/10.1016/j.electacta.2016.01.220.
The research leading to these results has been performed within the projects ReLiOn (BMBF, 03X4619C), MAT4BAT (EU/FP7, Grant Agreement no 608931), LIB.DE (BMWi, 03ET6081A) and TEESMAT (EU/ Horizon 2020, Grant Agreement 814106, http://teesmat.eu).