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http://hdl.handle.net/11375/28659
Title: | Study Ageing in Battery Cells: From a Quantum Mechanics, Molecular Dynamics, and Macro-Scale Perspective |
Authors: | Lanjan, Amirmasoud |
Advisor: | Seshasai, Srinivasan |
Department: | Mechanical Engineering |
Keywords: | Li-Ion Batteries; SEI Layer; NanoMaterials;Quantum Mechanics; Molecular Dynamics; Mathematical Modeling; Multiscale Modeling |
Publication Date: | 2023 |
Abstract: | When an anode electrode potential is larger than the lowest unoccupied molecular orbital (LUMO) of the electrolyte, Li-ions and electrolyte molecules will participate in reduction reactions on the anode surface and form a solid electrolyte interface (SEI) layer. Active Li-ion consumption in the formation reactions is the main source of capacity loss (>50) and ageing in Li-ion batteries (LIBs). Due to the fast-occurring and complex nature of the electrochemical processes, conventional experimental techniques are not a feasible approach for capturing and characterizing the SEI formation phenomenon. The lack of experimental data and consequently the absence of potential parameters for crystal structures in this layer makes molecular dynamics~(MD) simulations inapplicable to it. Also, due to the multi-component multi-layer structure of the SEI, the smallest system representing an SEI layer is too large for employing the principles of quantum mechanics~(QM), that traditionally work with much smaller system sizes. Addressing this, this thesis presents a novel computational framework for coupling QM and MD calculations to simulate a system with the size limits of MD simulations independent of the experimental data. The QM evaluates sub-atomic properties such as energy barriers against diffusion and employs seven new algorithms to estimate potential parameters as the input of the MD simulations. Then MD simulations forecast SEI's properties including density, Young's Modules, Poisson's Ratio, thermal conductivity, and diffusion coefficient mechanisms. The output of the QM and MD calculations are employed to develop two macro-scale mathematical models for predicting battery ageing and battery performance, incorporating the impact of the SEI layer in addition to the cathode, anode, and separator parts. Finally, the results obtained have been validated with respect to the experimental data in different operational conditions. |
URI: | http://hdl.handle.net/11375/28659 |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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Lanjan_Amirmasoud_2023May_PhD.pdf | 16.25 MB | Adobe PDF | View/Open |
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