High accuracy computational methods for lithium ion battery materials

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Materials Science and Engineering, May, 2020Cataloged from the official PDF of thesis.Includes bibliographical references (pages 101-114).The ongoing research to improve the performance of Lithium-ion batteries has required the study of increasingly complex physical and chemical phenomena. In this context, the use of computational tools to quantitatively assess these phenomena has proven crucial for advancing the Lithium-ion battery technology. However, recent areas of research, ranging from studying the diædiffusion of Lithium ions across solid polymer or ionic salt electrolytes, to the calculation of the voltage curve and discharge rate for complex transition metal oxide electrodes, has pushed Lithium-ion battery research beyond the framework of common computational methods, compromising the accuracy of these tools. Thus, there is an increasing need to use more accurate computational tools, or develop new ones, that could still be used in practice to design battery materials. This project presents how more accurate methods can be used to compute voltage curves for Lithium-ion cathode materials, determine the voltage stability of organic electrolyte, or predict the conductivity of diædifferent electrolyte materials. The motivation for the use of higher accuracy methods is emphasized for each application by showing the limitations of commonly used methods. In particular, the achieved accuracy enables an enhanced understanding of the specific, complex physical and chemical phenomena at the heart of Lithium-ion battery limitations, which is crucial to the design of better battery materials.by Eric R. Fadel.Ph. D.Ph.D. Massachusetts Institute of Technology, Department of Materials Science and Engineerin