銀、銅電極與氧化鈦、氧化鉿固態電解質在化學電解金屬化電阻式記憶體中是很常見且性能優良的材料選擇。但是當元件縮小化時，元件的可靠度和易變度就會有很大的影響，因為元件內的導電燈絲是隨機形成與熔斷的，因此如果可以控制離子的注入將可以改善元件的可靠度和易變度。在這個研究中我們考量兩個方向，一個是不同的電極與氧化物的組合有著不同的擴散係數，將影響離子的注入與低阻持久性。第二是探究夾在電極與固態電解質之間的氧化鋁奈米柱狀結構，當調整氧化鋁覆蓋率時，奈米柱的間距將可從十奈米調整至三十奈米，這層氧化鋁將會扮演著限制銀與銅擴散的角色，這層結構的設計將改善元件的持久性與多階儲存功能。實驗的最後也將提供一個指引，告訴讀者不同的電極與固態電解質組合與奈米擴散阻障層結合後在電性表現與在類神經應用的潛力。

Ag and Cu based electrodes with TiOx and HfOx based electrolytes electrochemical metallization (ECM) random access memory is a promising candidate for nonvolatile memory applications due to its simple structure and excellent performances. However, several challenges are needed to solve as the cell area is scaled down, especially for the device reliability and variability. Since the formation and rupture of the conductive filaments is stochastic, the injection of cations plays a critical role in improving the reliability and variability. In this study, two directions are considered, First, the combinations of different electrode/electrolyte cause the diffusivity differences, result in different degrees of cation injections and LRS retention failure times. Second, an Al2O3 layer with nano-pillar array architecture inserted between the electrode and switching layer is demonstrated. The width between the nano-pillar is tunable from 10 nm to 30 nm by changing the coverage of Al2O3 layer. The Al2O3 layer is served as the barrier that restrained the Ag and Cu atoms to diffuse into the electrolyte. With this architecture design, the resistive switching behaviors not only improve different degree of retention performances but also the multi-level storage potential. In the end of research, we will provide a roadmap in regards to the electrical performance and the potential in neuromorphic application with different electrode/electrolyte selection and nano-pillar array architecture.

CHAPTER 1 1
1.1 Research Background 1
1.2 Introduction of Memory 3
1.2.1 Volatile Memory 3
1.2.2 Non-Volatile Memory 6
1.3 New generation non-volatile memory 8
1.3.1 FeRAM 8
1.3.2 MRAM 10
1.3.3 PCRAM 12
1.3.4 RRAM 14
1.4 Switching behavior of RRAM 16
1.5 Classification of RRAM 18
1.5.1 Thermochemical Switching 18
1.5.2 Electrostatic Switching 18
1.5.3 Valence Change Memory (VCM) 19
1.5.4 Electrochemical Metallization Memory (ECM) 19
1.6 Neuromorphic Application 20
CHAPTER 2 24
2.1 Research Motivation 24
2.2 Fabrication Process 27
2.2.1 Glancing Angle e-Beam Evaporation 27
2.2.2 Process Flow 29
2.2.3 Material Characterizations 31
2.2.4 Electrical Characterizations 32
CHAPTER 3 33
3.1 Results and Discussions 33
3.1.1 Diffusion Barrier Layer 33
3.1.2 Electrical Performance 35
3.1.3 TEM Analysis 37
3.1.4 Stability of Conduction Filaments 40
3.1.5 Endurance Performance 43
3.1.6 Relationship between SET voltage and LRS 45
3.1.7 Neuromorphic Application 47
3.1.8 Comparison Table 49
CHAPTER 4 51
Conclusions 51
CHAPTER 5 52
References 52

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