Searching for Active Sites in Organic Electrode Materials

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Predicting the location of ion sites in soft electrode materials, such as molecular crystals, is challenging due to their intrinsic structural flexibility and large free volumes. Experimental techniques, such as X-ray diffraction, often struggle to accurately determine the position of active ions, including lithium-ion positions, especially given the occurrence of phase transitions or structural changes during electrochemical reactions. Accurately identifying ion locations at different state-of-charge remains crucial for understanding fundamental electrochemical reactions in electroactive materials, such as those in rechargeable batteries. We will discuss a computational strategy integrating experimentally determined organic lattice structures from diffraction experiments with first-principles calculations. Inspired by methodologies established in inorganic materials, 1–3 we utilize the electrostatic potential and charge density information obtained from first-principles methods to locate suitable for stable ion insertion within organic lattices. We will introduce two algorithms: (i) ElectRostatic InsertioN (ERIN), which sparsely inserts ions into electrostatically favorable sites based on the electrostatic local potential. (ii) ExtRema Averaged loCal potENTial and chaRge dEnsity (RECENTRE), which identifies electrostatically stable sites by locating local extrema in the local potential and charge density fields. These algorithms enable efficient and accurate predictions of potential ion insertion sites. In this talk, we will also showcase examples that validate these methodologies. References: Rong, Z., Kitchaev, D., Canepa, P., Huang, W. & Ceder, G. An efficient algorithm for finding the minimum energy path for cation migration in ionic materials. J. Chem. Phys. 145 , 074112 (2016). Shen, J.-X., Horton, M. & Persson, K. A. A charge-density-based general cation insertion algorithm for generating new Li-ion cathode materials. Npj Comput. Mater. 6 , 161 (2020). Zimmermann, N. E. R. et al. Electrostatic Estimation of Intercalant Jump-Diffusion Barriers Using Finite-Size Ion Models. J. Phys. Chem. Lett. 9 , 628–634 (2018).

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