Advancing Solid-State Battery R&D: Insights into Conductivity with QuantistryLab Simulations

Calculating the density of states of a material can provide valuable insights into its electronic, thermal and ion transport properties, especially conductivity, playing an important role in the development and optimization of novel compositions.

Optimizing electrolyte formulations is essential for the development of high-performance batteries. This use case explores how the QuantistryLab platform enables users to simulate and predict the viscosity of an electrolyte formulation.

The interaction of the lubricant components with metallic or oxidized surfaces plays a fundamental role in the formation of a protective film. Atomistic simulations provide in-depth insights into the adsorption of additives on the surfaces, their binding mode and binding strength.

The energy density of a battery cell largely depends on the materials used, making the search for optimal material compositions an important aspect of battery R&D.

If the charging rate of batteries shall be improved, it is worth taking a look at the mobility and intercalation processes of lithium ions within the battery components.

The quantum nanoreactor simulates and predicts the results of chemical reactions using metadynamics simulations. In this use case, the QuantistryLab platform is used to study the activation reaction of the anticancer drug cisplatin.