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Published on: April 12, 2019
Multiscale Investigation of the Diffusion Mechanism within the Solid-Electrolyte Interface Layer: Coupling Quantum
Amirmasoud Lanjan1, Zahra Moradi1, Seshasai Srinivasan1
1W Booth School of Engineering Practice and Technology, McMaster University, Hamilton, Ontario L8S 4L8, Canada.
This study introduces new equations to understand ion diffusion in the solid-electrolyte interface (SEI) layer of lithium-ion batteries (LIBs). This research aims to improve battery performance models by accounting for variable diffusion coefficients.
Area of Science:
- Materials Science
- Electrochemistry
- Computational Chemistry
Background:
- The solid-electrolyte interface (SEI) layer is crucial for lithium-ion battery (LIB) lifespan, yet its complex nature leads to significant capacity loss (over 50%) in commercial LIBs.
- Current mathematical models often oversimplify SEI layer behavior by using constant diffusion coefficients, failing to accurately predict capacity fading and SEI growth.
- Understanding diffusion mechanisms within the SEI layer is essential for improving battery longevity and performance.
Purpose of the Study:
- To develop a multiscale approach for investigating diffusion mechanisms within the SEI layer of LIBs.
- To derive equations for evaluating the energy barrier and diffusion coefficient in the inner SEI layer.
- To provide a more accurate basis for mathematical modeling of LIB performance.
Main Methods:
- Employed a multiscale investigation combining quantum mechanics, molecular dynamics, and macroscale mathematical modeling.
- Developed equations to calculate the energy barrier against diffusion and the diffusion coefficient.
- Evaluated these equations as a function of temperature and concentration for different SEI crystal structures.
Main Results:
- Presented novel equations to quantify diffusion barriers and coefficients within the SEI layer.
- Demonstrated the dependence of diffusion parameters on temperature, concentration, and SEI crystal structure.
- Established a foundation for more accurate modeling of SEI layer dynamics.
Conclusions:
- The derived equations offer a more precise method for studying SEI layer diffusion mechanisms in LIBs.
- These equations can be integrated into existing LIB models to enhance predictions of capacity fading and SEI growth.
- This work paves the way for improved design and performance of next-generation lithium-ion batteries.
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