A Semi-Empirical Descriptor for Open Circuit Voltage

TL;DR

This paper introduces a semi-empirical method to predict the open-circuit voltage of layered transition metal oxides in batteries by decomposing internal energy into measurable contributions, enabling efficient voltage profile calculations.

Contribution

It proposes a novel semi-empirical framework that combines theoretical decomposition with experimental data to predict OCV more efficiently than traditional methods.

Findings

Accurately predicts OCV using decomposed energy contributions

Reduces reliance on computationally intensive DFT calculations

Provides a practical tool for designing better battery cathodes

Abstract

Layered transition metal oxides (TMO) are widely used as cathode materials in Na/Li batteries. The open-circuit voltage (OCV), which determines the energy density (together with capacity), is among the key physical and chemical factors influencing the performance of cathodes. The shape of the voltage profile is also influenced by the formation energy of intermediate phases during cycling. From a theoretical perspective, the formation energy (and voltage) are defined as internal energy differences between phases. Therefore, an accurate prediction of internal energy is crucial for the calculation of OCV. In this work, we present a theoretical framework that decomposes the internal energy of a given TMO into distinct contributions with clear physical significance. Specifically, we break down the energy into parameters that can be more easily calculated (compared to DFT) and obtained from experimental databases. From these parameters, we define a potential term that can be calculated for different compositions, and can be used for calculation of voltage profile