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研究生: 賴畊睿
Lai, Keng-Jui
論文名稱: 不同鉀離子濃度於角蛋白記憶體應用之研究
Investigation of Varying Potassium Ion Concentrations Applied in Keratin-Based Resistive Memory
指導教授: 張御琦
Chang, Yu-Chi
學位類別: 碩士
Master
系所名稱: 工學院 - 工程科學系
Department of Engineering Science
論文出版年: 2026
畢業學年度: 114
語文別: 英文
論文頁數: 70
中文關鍵詞: 可變電阻式記憶體角蛋白鉀離子摻雜多階儲存生物可降解
外文關鍵詞: RRAM, Keratin, Potassium-ion doping, Multi-level cell (MLC), Biodegradable
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  • 隨著物聯網(IoT)與大數據技術快速發展,開發低功耗、高整合度之非揮發性記憶體(NVM)已成必然趨勢。為降低傳統無機半導體所帶來的電子廢棄物環境負荷,具備生物降解性與相容性之綠色電子元件備受矚目。本研究成功自廢棄人類毛髮中萃取出具備優異成膜性之天然角蛋白(Keratin),並將其作為阻變主動層,結合鉀離子(K+)摻雜策略,構築出具備Al/Keratin+K+/ITO三明治結構之新型綠色可變電阻式記憶體(RRAM)。
    然而,本徵角蛋白(Pristine Keratin)薄膜因電場驅動下電荷傳輸路徑隨機,面臨寫入(SET)電壓高、阻態切換隨機性大及循環穩定性不佳等嚴峻挑戰。為此,本研究系統性探討「不同鉀離子摻雜濃度」對元件電場誘導電荷傳輸行為之調控機制。結果證實,角蛋白基質內豐富的極性官能基(如羥基、胺基與羧基)可提供高效能之本徵電荷捕捉位點,而適量外源鉀離子的引入,能與大分子網絡產生強烈配位交互作用,有效調控薄膜內部之離子遷移率並優化電場分佈,藉由約束導電絲(Conductive Filaments)沿特定路徑進行高度重現性之形成與斷裂,大幅優化元件之電導調變動力學。
    在最佳化摻雜參數(1M KNO3 搭配4.5 wt% 角蛋白)下,該記憶體元件展現出高度穩健之雙極性阻變切換(Bipolar resistive switching)特性。高、低阻態之電流變異係數(CV)大幅收斂,成功克服了生物有機介質中固有的電學波動。此外,該元件具備高達4.2x105 的超高開關比(ON/OFF ratio)、優異的非揮發性資料保持力(Retention > 104 秒)、可靠的多階儲存(MLC)能力,並在高溫(80 °C)熱應力下仍能維持穩健的操作與記憶窗口。最關鍵的是,此鉀離子調控策略將元件良率(Yield)自本徵角蛋白的30%-45% 顯著提升至55%-65% 。本研究深入揭示了鹼金屬陽離子改性蛋白質薄膜的微觀物理機制,為次世代綠色突觸與神經形態運算硬體之開發奠定了關鍵的材料基礎

    With the rapid expansion of the Internet of Things (IoT) and big data, the demand for low-power, high-density non-volatile memory (NVM) has escalated tremendously. Concurrently, developing biodegradable green electronics has emerged as an imperative paradigm to mitigate the ecological burden of electronic waste. This study reports the successful extraction of natural keratin from discarded human hair as the active switching layer to fabricate a sustainable resistive random-access memory (RRAM) with an Al/Keratin+K⁺/ITO sandwich configuration.
    Previously, undoped pristine keratin films suffered from high operating (SET) voltages and severe electrical fluctuations, originating from the highly stochastic growth of conductive transport pathways under an applied electric field. To address this fundamental bottleneck, this work systematically investigates the physical modulation effects of "varying potassium-ion doping concentrations" on the electric-field-induced carrier transport kinetics of the devices. Experimental results reveal that while the abundant polar functional groups (e.g., –OH, –NH₂, and –COOH) within the keratin matrix serve as intrinsic charge-trapping sites, the introduction of an optimal amount of K⁺ ions establishes strong coordination interactions with the macromolecular network. This synergistic interaction effectively modulates local ion mobility and optimizes the electric field distribution, thereby confining the filamentary growth and rupture along precise, reproducible pathways, which significantly optimizes the conductance modulation dynamics of the device.
    Under the optimized parameters (1M KNO₃ in 4.5 wt% keratin), the memory device exhibits exceptionally robust bipolar resistive switching characteristics. The coefficient of variation (CV) for both high- and low-resistance states is dramatically minimized, successfully suppressing the electrical fluctuations inherent to bio-organic media. Notably, the optimized device delivers an outstanding ON/OFF ratio of up to 4.2 × 10⁵, exceptional non-volatile data retention exceeding 10⁴ seconds, reliable multi-level cell (MLC) storage capability, and robust thermal durability, maintaining a stable memory window even under a harsh thermal stress of 80 °C. Most importantly, this K⁺ doping strategy fundamentally elevates the overall device yield from 30%–45% of the pristine keratin to a remarkable 55%–65%. In conclusion, this study profoundly elucidates the microstructural physics of alkali-cation-modulated biopolymeric films, laying a crucial material foundation for the development of next-generation green synaptic and neuromorphic computing hardware.

    摘要 iii Abstract v 誌謝 vi Chapter 1 Introduction 1 1.1 Non-Volatile Memory 1 1.1.1 Magnetoresistive Random Access Memory, MRAM 1 1.1.2 Ferroelectric Random Access Memory, FeRAM 2 1.1.3 Phase-Change Random Access Memory, PCRAM 3 1.1.4 Resistive Random Access Memory, RRAM 4 1.2 The Integration of Biomaterials with Sustainable Memory Devices 6 1.3 Introduction to Keratin Materials 7 1.4 Keratin Extraction Methodology 8 1.5 Potassium-Ion Doping Strategy 9 1.1.2 Research Motivation 9 Chapter 2 Experiment details 10 2.1 Preparation of K⁺-Doped Keratin Solution 11 2.3 Device Fabrication Process 12 2.4 Device Fabrication and Measurement Equipment 13 2.4.1 Electronic Analytical Balance 13 2.4.2 Digital Hotplate Magnetic Stirrer 14 2.4.3 Constant Temperature Blast Drying Oven 15 2.4.4 Spin Coater 15 2.4.5 Ultrasonic Cleaner 16 2.4.6 Dual-Mode High Vacuum Magnetron Sputtering System 17 2.4.7 Power Supply ,Keithley 2636B 18 2.4.8 Ultra-High Resolution Scanning Electron Microscope and Energy-Dispersive X-ray Spectroscopy (UHR-SEM & EDS) 19 2.4.9 Atomic Force Microscope (AFM) 20 2.4.10 Fourier Transform Infrared Spectroscopy (FTIR) 21 2.4.11 X-ray Photoelectron Spectroscopy (XPS) 21 Chapter 3 Results and Discussion 22 3.1 Material Characterization and Device Structural Analysis 22 3.1.1 Surface Morphology Analysis of Keratin Thin Films 23 3.1.2 Cross-Sectional Structural Characterization by Transmission Electron Microscopy (TEM) 25 3.1.3 Chemical Structure Analysis by Fourier Transform Infrared Spectroscopy (FTIR) 27 3.1.4 Surface Morphology and Microscopic Elemental Distribution Analysis of K⁺-Doped Keratin Films (SEM & EDS) 28 3.1.5 Surface Elemental Composition and Chemical Bonding State Analysis via X-ray Photoelectron Spectroscopy (XPS) 31 3.2 Parameter Optimization and Fundamental Electrical Properties of K⁺-Doped Keratin Memory 33 3.2.1 Electrical Properties of Undoped and Low-Concentration K⁺-Doped Devices 33 3.2.2 Electrical Properties of Low-Concentration (0.5M) and Optimized (1M) K⁺-Doped Devices 35 3.2.3 Electrical Properties of Optimized (1M) and High-Concentration (2M) K⁺-Doped Devices 37 3.2.4 Control Study of Anion Effects Using Potassium Chloride (KCl) as a Dopant 39 3.2.5 Conduction Mechanism Analysis of Optimized K⁺-Doped Memory Devices 41 3.3 Reliability and Mass Production Potential Analysis of the Optimized Memory Devices 42 3.3.1 Temperature-Dependent Conduction Mechanism and Thermal Stability Analysis 42 3.3.2 Memory Retention and Data Storage Reliability 44 3.3.3 Improvement of Device Yield via Potassium-Ion Doping 46 Chapter 4 Conclusions 48 Chapter 5 Future Work 50 References 51

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