Li-ion Battery Materials Theory and Computation to Guide and Interpret Experiments
Abstract
Li-ion batteries are enabling electrification; cell energy densities, lifetimes and cost
render grid energy storage solutions and personal and commercial electric modes of
transportation economically and practically feasible. However, exponential market
growth demands cheaper, longer lasting, more energy dense, and safer Li-ion cells.
The work presented in this thesis rests at the intersection of theory, computation, and
experiment; properties of Li-ion battery positive electrode materials were computed
from first-principles and compared to experimental results, phenomenological equations
were fit to measurement, and software was developed to analyze experimental
data.
The first part of this thesis shows that within the GGA+U formalism, the calculated
structural, electronic, and electrochemical properties of relevant materials for
state-of-the-art positive electrodes, depend on the choice of U to a greater extent than
previously recognized. In some cases, an incorrect electronic structure is predicted.
These findings suggest that U should be chosen with care, and in some cases the
GGA+U formalism may not be appropriate.
The second part of this thesis demonstrates how individual substituents influence
electrochemical and thermal properties of Ni-rich positive electrode materials.
Furthermore, a reinvented approach for Li chemical diffusion measurements, bridging
theory and measurement, is developed and used to show how omitting Co altogether
from Ni-rich positive electrode materials worsens rate capability. These results highlight
intrinsic challenges in Li-ion battery material optimization and offer practical
considerations for designing high energy-density positive electrode materials.
The final part of this thesis presents analysis software developed for experimental
data. Two software suites were developed; the first enables automated yet interactive
analyses of Li chemical diffusion measurements, providing users with export and
fitting flexibility, and the second provides a user-interface for exploring data collected
from different cyclers and automatically fitting differential capacity curves to reference
data. These tools have saved many days of otherwise manual analysis.