鋰電池是目前最廣為應用的能源儲放裝置之一，自小型的隨身攜帶型電子裝置，乃至於電動車的發展，鋰電池都扮演不可或缺的角色。許多機構急迫需要針對鋰電池內部的材料，像是陰極、電解質、和陽極等各方面做性能上的改進。因鋰離子電池本身受限於比電容量大小的限制，故有學者提出了鋰空氣電池的概念與雛形。本論文研究，欲針對鋰空氣電池最關鍵的空氣極氧還原作用，以及鋰離子在電解質內部的傳輸作用作探討。在鋰離子電池部分，則針對電池內部(陽極/電解質/陰極)的電解離子傳輸、應力應變、有效擴散係數、離子電導度、與整體性能表現作詳細的研究。
首先，以量子化學針對鋰空氣電池空氣極部分，研究以奈米碳管吸附與參雜白金的方式，比較兩種不同形式的白金催化方式，說明白金搭配奈米碳管在鋰空氣電池空氣極的氧還原作用機制。研究結果說明，白金參雜或吸附奈米碳管材料，與純粹的奈米碳管相比，皆能有效降低能隙大小，有助於空氣極電子傳導與電子雲分佈的催化作用，而白金吸附與參雜的催化作用比較上，利用白金參雜奈米碳管材料，其與氧分子的吸附能大小更優於白金吸附奈米碳管材料。因而進一步研究利用參雜氮原子方式以取代昂貴白金原子，希望能有效降低製造成本，且達到有效的氧還原作用。研究結果發現，以氮參雜奈米碳管材料，與純粹的奈米碳管比較，能有效降低能隙大小，雖然與白金參雜奈米碳管材料相比，氮參雜奈米碳管材料的吸附能沒有白金參雜奈米碳管來的好，但其承受的電池放電過程所產生的熱效應，以及製作成本來說，仍可作為日後研究鋰空氣電池空氣極材料。
其次，在分子尺度研究上，因鋰離子電池在充放電過程，會產生電解質的穿刺破壞作用，因此本文針對鋰離子電池內的電解質材料，以分子動力學方法，設計聚氧化乙烯(PEO)分子構造提供離子傳導通道，另結合聚苯乙烯(PS)以提供結構強度，做最佳化的分析與設計。本文提出4種不同的PS質量分率(0%、30%、50%、70%)，探討鋰離子電池電解質材料的離子傳導與楊氏係數關係。由離子傳導作用結果說明，當PS的質量分率增加，則離子傳導率則會隨著下降，因鋰離子在電解質內部的傳輸作用遞減的緣故所引起，此可由鋰離子與氧原子的徑分佈函數（RDF）看出。另一方面，不同PS質量分率造成電解質材料的楊氏係數會隨著PS的質量分率增加也隨著增加的趨勢，此乃因於材料內部的凡得瓦力與原子勢能上升的緣故。由以上分析，考慮離子傳導與結構強度間需要做一PEO與PS比例間的取捨，由優化結果顯示，大概介於PS質量分率40~50%的參雜比例下，不但可兼顧離子傳導性，亦可考量到鋰離子電池在多次充放電下，楊氏係數佳的材料所承受的損壞情況也可降低。
最後，在巨觀尺度分析上，本論文研究鋰離子電池整體的性能表現，針對電池放電過程，自陽極、電解質、乃至陰極做固態與液態情況下，材料、離子與電流平衡分析，研究著重可能影響電池充放電過程的各項參數分析，如操作溫度、電解質濃度、放電率大小以及陰極材料等，做詳細分析與研究，最終再做參數優化與整體性能提昇設計建議。

Lithium batteries are one of the most popular energy storage devices presently. From portable electronics to electric vehicles, lithium batteries play the key role as the major power source. Because of the fundamentally low electric capacity limit in lithium-ion batteries (LIBs), brand new lithium-air batteries (LABs) with embryonic forms are proposed as a substitute for future batteries. This research intends to set up the general model to study the ionic conductivity, effective diffusion coefficient, stress-strain analysis and to predict the overall performance of lithium batteries.
First of all, the quantum scale analysis was conducted to study the oxygen reduction reaction (ORR) mechanism at the air cathode of LABs. The results indicate that both Pt-adsorbed carbon nanotubes (CNTs) and Pt-doped CNTs are more effective in lowering the band gap than the pristine CNT. The phenomena are contributive to the electric conduction and the electron cloud distribution at the air cathode. For this reason, an N-doped CNT is proposed as a substitute for the Pt-doped CNT to lower down the band gap and also the production cost significantly. The simulation results reveal that the N-doped CNT obviously lowers the energy gap than the pure CNT, but still shows a slight poor performance than the Pt-doped CNT. However, the N-doped CNT shows a better specific thermal capacity than the Pt-doped CNT to reinforce the thermal effect during the charge-discharge processes.
Secondly, from the molecular aspect, this research focuses on reinforcement of the poly electrolyte to reduce the dendrite phenomena during the charge-discharge processes of lithium ion batteries. Molecular dynamics simulations are employed to design the optimal ratio between the polyethylene oxide (PEO), which provides the ionic conductivity, and the polystyrene (PS), which provides mechanical strength in the polymeric electrolyte. Four variations of PS weight ratios (0%, 30%, 50%, 70%) are studied to predict the ionic conductivities and their Young’s modulus. The results indicate that the ionic conductivities are enhanced with the decrease of the PS weight ratio, resulting from the weakening oxygen transport effect in the internal electrolyte. On the other hand, the Young’s modulus increases with the rise of PS weight ratio, resulting from enhancing the internal Van der Waal’s force and the inter-molecular potential. For this reason, a clear prediction of an optimal PEO-PS weight ratio can be determined to design the optimal electrolyte for the LIBs. The result indicates that if the PS weight ratio is chosen between range of 40% and 50%, the electrolytic material can avoid dendrite defects without compromising the ionic conductivity significantly for lithium-ion batteries.
Finally, a macro-scale performance study was conducted to predict the overall performance for the lithium-ion batteries. The anode, the electrolyte, and the cathode material effects are taken into consideration. This part combines the microscopic molecular dynamics (MD) simulation with the traditional macroscopic computational mass transfer (CMT) to predict the performance of various lithium battery designs. Molecular simulations are employed to predict the diffusion coefficients and ionic conductivities of Li ions in the porous anode, cathode and electrolytes under different salt concentrations and operation temperatures. The MD results are input to the CMT code, which is based on the balance equations of current, charge and materials, with the Bulter-Volmer equation to predict the battery performance. Two kinds of cathode materials, LiMn2O4 and LiFePO4, three kinds of electrolytes, e.g., PEO, PS-PEO and EMI-TFSI ionic liquid, and three discharging conditions: 0.5C, 1C, and 2C, are chosen to carry out parametric studies. The results show that the performance can be optimized by trading-off the above parameters using this multi-scale simulation technique.

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