Lithium ion batteries (LIBs) with a high energy density or specific energy are desirable, as this is important for the range of electric cars, among others. The energy density of a battery cell largely depends on the materials used. Therefore, the search for optimal material compositions is an important aspect of battery R&D. In addition, the use of rare and expensive elements should also be avoided if possible, and the stability of the materials has to be taken into account.

Starting Point

To improve the energy density, it is worth taking a look at the open circuit voltage (OCV). The OCV is the voltage across the electrodes when the battery is in equilibrium and no external load is connected. During discharge of an LIB, lithium ions are transported from the anode to the cathode, where they are inserted into the cathode material, while the electric energy can be used in the external circuit. The energy change during the reaction between cathode and anode determines the voltage – and quantum chemical simulations are ideally suited to determine this. The simulations can be carried out depending on the state of charge (SOC), i.e., as a function of the lithium content of the electrode materials, and thus the voltage profile can be calculated. A suitable cathode material should exhibit a high voltage, whereas an anode material should have a low voltage with respect to metallic lithium. As for the voltage profile, it is usually desirable that the voltage changes only slightly during the charge-discharge cycles (flat profile). The goal of our simulations is to predict the OCVs of potentially promising materials using the Quantistry Lab and to identify optimal candidates for LIBs.

Simulation Approach

We have selected two exemplary cathode materials for this use case: lithium cobalt(III) oxide (LiCoO₂) and the Li-rich lithium manganese(IV) oxide (Li₂MnO₃). Quantum chemical simulations of the materials were performed with the Quantistry Lab in order to determine the OCV as a function of the battery state of charge, i.e., depending on the number x of inserted lithium ions (Li_xCoO₂, Li_xMnO₃). Following this, the voltages were determined with respect to a Li⁺/Li reference anode.

Key Results

Lithium cobalt(III) oxide

Figure 1 shows the simulated voltage profile of the LiCoO₂ cathode. First, the 3D structures of the material are obtained at different states of charge. Two of these structures, with a high and a low lithium content (Li_xCoO₂ with x = 1 and x = 0.25), are depicted in Fig. 1 (lithium ions are shown in light purple). A voltage of about 4 V vs. Li⁺/Li is reached. It can also be seen that the voltage increases with decreasing lithium content (i.e., during charging) from 3.7 V (LiCoO₂) to over 4.2 V (Li_xCoO₂ with x < 0.3). This observation as well as the predicted voltages are in excellent agreement with experimental values [1].

In addition, the simulations provide information about the change in charge distribution within the electrode material depending on its state of charge. For example, Figure 2 – the Quantistry Lab results view – illustrates the charges on the atoms in LiCoO₂ (red: negative charge; blue: positive charge). By comparing different states of charge, it is possible to see how the charge transfer behaves during discharge, for example: in this case, mainly the negative charge of oxygen increases, i.e., oxygen is reduced when lithium is inserted into Li_xCoO₂.

Quantistry Lab results view: charge distribution in LiCoO₂. | QUANTISTRY LAB 2022

‍Lithium manganese(IV) oxide

Lithium manganese oxides are also of interest as cathode materials for LIBs. Besides their properties, the abundance of manganese makes these materials attractive candidates. The simulated voltage profile of the lithium-rich Li₂MnO₃ as a function of the state of charge is shown in Figure 3 (Li_xMnO₃ with x = 2 to 1; see the structures in the inset of Fig. 3). Li₂MnO₃ exhibits a higher voltage than LiCoO₂ (ca. 4.5 V vs. Li⁺/Li), which furthermore remains rather constant over different states of charge.

Summary

Quantum chemical simulations of different electrode materials can be performed easily and quickly with the Quantistry Lab, e.g., as high-thoughput-screening. In this use case, the OCVs of LiCoO₂ and Li₂MnO₃ cathode materials were simulated in dependence on their state of charge. The voltages can be determined for various material compositions, dopants, etc. in order to identify electrodes with optimal OCVs. Our approach is particularly interesting in the form of an automated screening of new materials. The choice of elements and their atomic positions in a material is a deciding factor for the voltage profile. In addition, the influence of defects or oxygen loss in the cathode material on the voltages can be investigated. The volume change of the electrodes upon lithium insertion is another important factor for the stability of a battery cell during charge-discharge cycles, which can also be evaluated with our simulations. Optimizing the electrode materials is in turn an essential aspect that can contribute to a better energy density of a battery cell. Of course, such an optimization can also be carried out with a focus on the availability and sustainability of the elements used.

[1] T. Okumura, Y. Yamaguchi, M. Shikano, and H. Kobayashi, Correlation of lithium ion distribution and X-ray absorption near-edge structure in O3- and O2-lithium cobalt oxides from first-principle calculation, J. Mater. Chem. 22, 17340 (2012).