Lithium-ion batteries have become the gold standard across numerous industries around the globe due to their high energy density and long-lasting battery life. However, the demand for batteries with better capacity, durability, and charging speed has been soaring in recent years. A key driver for this demand is the automobile industry; as electric vehicles gain popularity, there is a higher need for batteries with very high energy density to allow electric vehicles to go for longer without charging.  

In addition to the growing demand for high-performance battery materials, there is an urgent need for more sustainable alternatives to traditional battery materials. The manufacturing of these materials currently requires mining rare metals such as lithium and cobalt, causing devastating environmental damage across the world including deforestation and drought.  

To meet this rapidly growing demand for batteries with improved performance, R&D efforts are focusing on identifying new battery materials that can deliver enhanced properties to batteries. However, the traditional trial-and-error model where multiple iterations of candidate materials are individually tested can be costly, both in terms of time and resources. Chemical simulations based on quantum chemistry have emerged as a powerful tool to accelerate R&D processes and significantly reduce costs.  

Use case: Open circuit voltage of lithium cobalt oxide

The open circuit voltage (OCV) is a key property of a battery's electrodes that can significantly influence the energy density of a battery cell. The OCV is defined as the difference of electrical potential across the electrodes when there is no external electric current flowing through the battery. Ideally, the cathode material within a battery should have a higher voltage while the anode material should have a low voltage.  

One of the challenges of taking experimental measurements of an electrode material’s OCV is that it requires multiple measurements for each candidate material, making the process time-consuming. Because the OCV depends on the battery’s state of charge, it becomes necessary to take measurements at multiple different points in time in order to calculate the full OCV profile of any electrode material.  

With just a few clicks, the QuantistryLab platform allows the user to run simulations of chemical systems to model and predict many of their properties, including the OCV. To measure the OCV of electrode materials for lithium-ion batteries, the voltage is calculated using density functional theory (DFT) calculation of the energy difference between the electrode in its fully-lithiated state and a partially delithiated state. These simulations can be carried out at different states of charge, as a function of the lithium content in the electrode, to calculate the full OCV profile of the material of choice.  

Lithium cobalt oxide was the electrode material chosen for this use case. This was one of the first cathode materials used in lithium-ion batteries, and is still widely used in smartphones, laptops and cameras. Due to its popularity, lithium cobalt oxide has been extensively studied, enabling the comparison of simulation results with peer-reviewed experimental data.  

The first step to calculate the OCV of lithium cobalt oxide is to create a model of the cathode material. This can be done easily with QuantistryLab, by simply selecting the desired material from the compound library or adding it manually from a compound file.  

As a battery gets discharged, lithium ions move from the anode to the cathode. During this process, lithium ions get intercalated among the layers of lithium cobalt oxide. To calculate the full OCV profile of lithium cobalt oxide, multiple simulations are run simultaneously with different concentrations of lithium in the cathode material.

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The simulations yield a graph with the results of the OCV calculations, showing the voltage for the lithium cobalt oxide at different levels of lithium content. The results show that the OCV stays within the range of 4-6V and decreases as the amount of lithium in the cathode increases. The OCV value when the battery is fully discharged is predicted to be 4.35V, which is consistent with the charge cut-off voltage reported for batteries with lithium cobalt oxide cathodes in peer-reviewed literature, which is in the range of 4.2-4.45V.

This use case demonstrates how computational simulations can be employed to calculate the OCV profile of a known cathode material using the QuantistryLab platform. The workflow described above can be replicated to obtain the OCV profile of any other electrode materials, providing valuable insights for the development of novel battery materials.  

Simulations are a powerful tool for battery R&D that can significantly cut down on the amount of time and resources spent on R&D workflows. This technology can be employed to predict the properties of novel materials and select the most promising candidates for experimental tests, massively reducing the number of experiments required to develop a new high-performance material.

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