Electrochemical synthesis of ammonia through the nitrogen reduction reaction (NRR) has the possibility to revolutionize our production of ammonia and to save our planet from both emissions and large energy consumption. In this study, a perovskite structured lanthanum chromite catalyst (LaCrO 3 ) is synthesized, characterized as well as electrochemically evaluated for NRR. The highest ammonia yield is obtained at À 0.8 V vs. reversible hydrogen electrode with an ammonia formation rate of 24.8 μg h À 1 mg À 1 cat , and a Faradaic efficiency of 15 %. Material calculation further confirms the possible mechanism of ammonia formation with the aid of LaCrO 3 catalyst. The resulting conclusion offers a great alternative with the easily produced and low-cost perovskite structured electrocatalysts for ammonia production.

A reliable power grid system based on renewable energy sources is a crucial step to restrict the climate crisis. Stationary battery energy storage systems (BESS) offer a great potential to repel power fluctuations in the grid at different timescales. However, for a reliable operation and cost estimation, the degradation in the batteries needs to be understood. We present an accelerated battery degradation study, on single as well as multi-service applications, of NCM532/Gr lithium-ion battery cells. Frequency regulation (FR) was the least harmful for the battery, with an expected lifetime of 12 years, while peak shaving (PS) resulted in an expected lifetime of 8 years. The combined cycle (FRPS) accelerated the capacity loss, and degradation of the positive electrode was induced from the start of cycling, causing power limitations after only 870 equivalent full cycles (EFC). Tracking the 1C-rate discharge capacity was proven to be a good indication of the accelerated cell polarization, and it can serve as a useful method to evaluate the internal battery state of health (SOH).

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Degradation of lithium-ion batteries is the result of many complex phenomena occurring simultaneously at varying time and length scales. The underlying electrochemical and mechanical phenomena have received much attention from researchers [1]. Physics-based models of these effects support the mechanistic understanding of degradation modes and can thereby help reduce their severity. Few studies target changing electrochemical parameters such as diffusion coefficients or reaction rate constants that have a direct impact on model accuracy and manifest themselves in observable aging. Lyu et al. [2] used a simplified electrochemical model and monitored battery degradation by following changes in diffusion time constants, electrode balancing, reaction rate coefficients, and ohmic resistance. However, several of the parameters they attempted to track could only be identified with low accuracy as they used the same data-set to identify all parameters. In this study, we investigate parameters of a full order Newman-type model [3] over the course of a batteries lifetime under real-world load-cycles. To ensure parameter identifiability, optimally designed experiments are used for parameter estimation. In a previous study [4] the feasibility of optimal experiment design for parametrization of electrochemical battery models was demonstrated. We now extend this work and re-evaluate key parameters over the course of an aging study on commercial, nickel-rich 18650 lithium-ion batteries. We highlight how quantifying changes in physical battery parameters can extend standard performance metrics for a batteries state-of-health by, e.g., including degradation in rate-capability. Additionally, the importance of battery usage conditions such as C-rate or state-of-charge window on model parameter trajectories is investigated and their relationship with conventional performance metrics such as the bulk cell resistance or rate-capability determined. Quantifying how specific mechanisms contribute to apparent capacity or power fade is a major step towards battery lifetime optimization. This could enable designs more tailored for specific applications and significantly extend batteries useful lifetime. Furthermore, updating parameters is essential for electrochemical control strategies relying on accurate model predictions of battery states as illustrated in Figure 1. This re-calibration would make a battery management system aging-sensitive and enable more efficient utilization and a physics-informed state-of-health. Figure 1: The central plot shows how parameters change during aging. If this change is not considered, model performance deteriorates between beginning-of-life (BOL) and end-of-life (EOL) (in blue, right-hand side). This is normally handled by using conservative battery management systems and over-sizing systems. The proposed strategy (orange) achieves higher model accuracy during the entire useful life and the parameter estimates can be used to formulate an extended state-of-health. References: [1] J. Vetter, P. Novák, M.R. Wagner, C. Veit, K.C. Möller, J.O. Besenhard, M. Winter, M. Wohlfahrt-Mehrens, C. Vogler, A. Hammouche, Ageing mechanisms in lithium-ion batteries, J. Power Sources. 147 (2005) 269–281. https://doi.org/10.1016/j.jpowsour.2005.01.006. [2] C. Lyu, Y. Song, J. Zheng, W. Luo, G. Hinds, J. Li, L. Wang, In situ monitoring of lithium-ion battery degradation using an electrochemical model, Appl. Energy. 250 (2019) 685–696. https://doi.org/10.1016/j.apenergy.2019.05.038. [3] M. Doyle, T. Fuller, J. Newman, Modelling of the Galvanostatic Charge and Discharge of the Lithium/Polymer/Insertion Cell, J. Electrochem. Soc. 140 (1993) 1526–1533. https://doi.org/10.1149/1.2221597. [4] M. Streb, M. Ohrelius, M. Klett, G. Lindbergh, Improving Li-ion Battery Parameter Estimation by Global Optimal Experiment Design (Manuscript submitted), (2022). Figure 1