MC16 2023 - Oral Book of abstracts

Improving lithium metal battery performance by pulsed current charging and discharging Katarina Cicvaric, Bojing Zhang, Fuzhan Rahmanian, Leon Merker, Helge Sören Stein Karlsruhe Institute of Technology, Helmholtz Institute Ulm, Germany Battery performance needs to improve whilst decreasing costs. One pathway is to simplify the design of a cell by using existing and cost-effective chemistries like anode free cells (Lithium Metal Batteries, LMB) with Lithiumironphosphate (LFP) as the cathode. This system offers a theoretically high energy density but dendrite formation, scrap production and cell failures during assembly and formation are major obstacles 1 .During charging in LMBs, lithium metal is electroplated onto a copper current collector, while during discharging lithium is intercalated into cathode material. Ensuring smooth electroplated lithium film on the copper current collector after charging is crucial as porous and irregular morphologies dubbed ‘dendrites’ lower capacity retention and safety.One method for suppressing dendrite growth is pulsed charging which is in contrast to conventionally used techniques for battery charging i.e. applying a constant current until a certain voltage is reached. As opposed to constant current or potential techniques, pulsed current technique comprises of short constant current periods interrupted by off-time where current is not flowing. During the off-time, concentration of metal ions at the electrode surface is believed to be replenished which is beneficial for growing smooth films, as depletion of ions enables growth of irregular features hence creating lithium dendrites 2 . Pulsed current technique has not only shown improvements in lithium electroplating while charging, but has also been shown as beneficial for intercalation of lithium ions into the electrode material 3 and electroplating of various metals 4 5 and semiconductors 6 . By applying pulsed current technique one can vary multiple parameters such as pulse height and duration of on- and off-times. Although more parameters tuning allows for more room for optimisation, it often takes a lot of experimentation to find the optimal parameters. In this work, we employ deep learning combined with robotic experimentation using the world’s first automatic coin cell assembly robot – AutoBASS 7 - to find the combination of pulsing parameters which would allow the best electrochemical performance under repeated cycling. References 1. Z. Xie, Z. Wu, X. An, X. Yue, J. Wang, A. Abudula and G. Guan, Energy Storage Mater , 2020, 32 , 386–401. 2. G. García, S. Dieckhöfer, W. Schuhmann and E. Ventosa, J Mater Chem A Mater , 2018, 6 , 4746–4751. 3. B. K. Purushothaman and U. Landau, J Electrochem Soc , 2006, 153 , A533-A542. 4. C. Y. Chen, M. Yoshiba, T. Nagoshi, T. F. M. Chang, D. Yamane, K. Machida, K. Masu and M. Sone, Electrochem commun , 2016, 67 , 51–54. 5. J. B. Marro, T. Darroudi, C. A. Okoro, Y. S. Obeng and K. C. Richardson, Thin Solid Films , 2017, 621 , 91–97. 6. K. Cicvarić, L. Meng, D. W. Newbrook, R. Huang, S. Ye, W. Zhang, A. L. Hector, G. Reid, P. N. Bartlett and C. H. K. de Groot, ACS Omega , 2020, 5 , 14679−14688. 7. B. Zhang, L. Merker, A. Sanin and H. S. Stein, Digital Discovery , 2022, 1 , 755–762.

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