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The present poster contribution aims at optimization of electrochemical properties of titania (N doped anatase TiO2 / N) and Li-Ti ternary oxides (Li4Ti5O12, LTO) with respect to their performance as anode materials in Li-ion battery by using mechanochemical effects.

The present poster contribution aims at optimization of electrochemical properties of titania (N doped anatase TiO2 / N) and Li-Ti ternary oxides (Li4Ti5O12, LTO) with respect to their performance as anode materials in Li-ion battery by using mechanochemical effects.

Electrode microstructure directly affects ion and electron transport and, in turn, has a strong correlation to battery performance. Understanding the separate yet complementary effects of ionic and electronic transport in cell behavior is a challenge. This work provides through a combination of experiments and modeling a better understanding of the relationship between three aspects of the cell: ion transport within the electrode, electrode uniformity, and cell degradation. The first part of this work compares two experimental methods that determine ion transport in terms of tortuosity, a dimensionless geometric factor. The polarization-interrupt and blocking-electrolyte methods measure effective diffusivity and conductivity, respectively. The tortuosity of several commercial-quality electrodes was measured using both methods, producing reasonable agreement between the two methods in most cases. Next, the effect of cell cycling on ionic and electronic transport of electrodes was investigated. Using the blocking electrolyte method, the tortuosity of electrode films at varying extents of cycling was determined. Variations in electronic resistivity were quantified by micro-scale measurements using a previously developed micro-four-line probe. The changes in tortuosity and electronic resistivity were investigated for a graphite anode and several cathode chemistries including LiCoO2, LiNixCoyMnzO2, LiFePO4, and blends of transition metal oxides. Clear evidence of changes in tortuosity and electronic resistivity was observed during cell formation and cycling. The magnitude of the changes strongly depended on the chemistry of electrodes and cycling conditions. The results indicate that, under normal cycling conditions, electronic resistivity increases while tortuosity unexpectedly decreases. However, accelerated cycling conditions (i.e. elevated temperature) can lead to both electronic resistivity and tortuosity increase. Finally, the interplay of electrode tortuosity heterogeneity and Li-plating was investigated. The Li-plating reaction was incorporated into a Newman-type model and validated using the voltage profile and capacity-loss data from experiments. The simulation result shows that a heterogeneous anode can cause non-uniform Li plating while cathode heterogeneity did not have a significant effect. The Li-plating profile across the thickness of the anode with cell cycling showed that Li tends to plate at the high tortuosity region near the separator. Unexpectedly, Li plating tends to shift to the current collector side upon a sufficient increase in porosity close to the separator. Simulated capacity loss vs. cycling data indicates that there is a feedback mechanism with cycling: as cycling continues the rate of Li plating for the high-tortuosity region decreases at the separator side and the other two regions will eventually catch up in terms of plating.

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京都大学 / 0048 / 新制・課程博士 / 博士(エネルギー科学) / 甲第17912号 / エネ博第284号 / 新制||エネ||59(附属図書館) / 30732 / 京都大学大学院エネルギー科学研究科エネルギー基礎科学専攻 / (主査)教授 八尾 健, 教授 森井 孝, 教授 佐川 尚 / 学位規則第4条第1項該当 / Doctor of Energy Science / Kyoto University / DGAM

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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. / Thesis / Doctor of Philosophy (PhD) / The limited lifespan of expensive batteries is the main obstacle to electrification of the transport sector, despite its necessity for addressing the current environmental issues. Li+/electrolyte reduction on the electrode surface is responsible for more than 50% of capacity loss and the consequent ageing is a complex and fast-occurring phenomenon (few ns) that cannot be easily resolved using conventional experimental and computational techniques. This thesis presents the development of some computational frameworks and demonstrates their employment to investigate this phenomenon from a multi-scale perspective, i.e., from a few electrons to an entire battery length scale, with the operating cycles ranging from a few ps to several months, employing Quantum Mechanics, Molecular Dynamics, and Macro-Scale Modeling. The frameworks have been successfully validated with respect to experimental data from the literature and have been applied successfully to highlight the parameters that impact ageing in batteries. The findings presented in this thesis can be used as the base for further research on next-gen durable batteries with liquid and solid-state electrolytes.

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