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研究生: 蔡孟宇
Tsai, Meng-Yu
論文名稱: 層狀二硒化錸凡得瓦異質結構之光電調控
Optoelectronic Modulation of Layered ReSe2 van der Waals Heterostructures
指導教授: 邱博文
Chiu, Po-Wen
林彥甫
Lin, Yen-Fu
口試委員: 林佑明
Lin, Yu-Ming
鄭兆欽
Cheng, Chao-Ching
謝光宇
Hsieh, Kuang-Yu
學位類別: 博士
Doctor
系所名稱: 電機資訊學院 - 電子工程研究所
Institute of Electronics Engineering
論文出版年: 2024
畢業學年度: 112
語文別: 英文
論文頁數: 188
中文關鍵詞: 二維材料凡得瓦異質結構二硒化錸雙極性非揮發性記憶體懸浮閘極電荷捕捉光致摻雜可重新配置場效電晶體突觸可塑性赫本學習圖像辨識邏輯閘
外文關鍵詞: two-dimensional materials, van der Waals heterostructure, rhenium diselenide, ambipolar, non-volatile memory, floating gate, charge trap, photo-induced doping, reconfigurable FET, synaptic plasticity, Hebbian learning, image recognition, logic gate
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  • 隨著半導體業面臨摩爾定律之瓶頸,二維材料的探索變得越發重要。本論文深入研究二維之二硒化錸 (Rhenium diselenide; ReSe2) 凡德瓦異質結構的光電調變能力,旨在利用光來調控二維非揮發性記憶單元中的電荷傳輸並開發其應用。基於浮動閘極記憶體架構的光活性之浮動閘極記憶體 (Photoactive Floating-Gate Memory; P-FGM) 是本研究的核心之一。P-FGM結合光刺激與電刺激來模擬一系列的生物學上的神經元突觸行為,包含增強和抑制的生物特徵。P-FGM 利用尖峰時間依賴可塑性,表現出四種赫本學習規則的神經互動行為,並且在圖像識別的模擬中表現良好,使其成為生物模擬和視覺感知神經網絡應用的優異候選者。與此同時,本研究介紹了光致摻雜之可重構場效電晶體 (Photoinduced-Doping Reconfigurable Field-Effect Transistor; PD-RFET)。基於載子捕捉的記憶原理,PD-RFET利用在六方氮化硼/二氧化矽之界面進行光致電荷捕捉。其設計有利於可逆地切換於可編程的記憶模式和不可編程的晶體管模式之間。此外,受益於其特殊設計的雙柵極配置,PD-RFET可以通過調節光致摻雜之參數,摻雜成不同程度的n型或p型電晶體狀態,並依然保持其非揮發性和穩定的特性。基於這些多功能性,PD-RFET已被集成到各種邏輯閘配置以及神經突觸模擬中,並在這些應用中表現出高度的適應性。因此,本論文研究利用非揮發性ReSe2異質結構開發的獨特性質,揭示了光電調控方面的突破,有望在下一代電子學領域提供更廣泛的應用可能性。


    As the semiconductor industry faces the bottleneck of Moore’s Law, the exploration of two-dimensional (2D) materials becomes increasingly relevant. This dissertation delves into the optoelectronic modulation capabilities of 2D-based Rhenium diselenide (ReSe2) van der Waals heterostructures, with the aim of using light to modulate charge transport in 2D non-volatile memory cells and develop its applications.
    Photoactive Floating-Gate Memory (P-FGM), based on floating-gate memory architecture, is one of the cores in this research. P-FGM combines optical and electrical stimulation to simulate a series of synaptic behaviors, including biological characteristics of enhancement and inhibition. Utilizing the time-dependent plasticity of spikes, P-FGM exhibits neural interaction behavior of four Hebbian learning rules, and performs well in image recognition simulations, making it a good candidate for biological simulations and neural network applications of visual perception.
    In parallel, this study introduces the Photoinduced-Doping Reconfigurable Field-Effect Transistor (PD-RFET). Based on the principle of charge-trap memory, PD-RFET utilizes photoinduced charge-trapping at the interface of hexagonal boron nitride/silicon dioxide (h-BN/SiO2). Its design facilitates reversible switching between a programmable memory mode and an unprogrammable transistor mode. In addition, benefiting from its specially designed double-gate configuration, PD-RFET can be doped into n-type or p-type transistor states to different degrees by tuning photoinduced-doping parameters, and still maintain its non-volatile and stable characteristics. Based on these versatility, PD-RFETs have been integrated into various logic gate configurations and neurosynaptic simulations, showing high adaptability in various applications.
    Therefore, taking advantage of the unique properties of non-volatile ReSe2 heterostructures development, this study reveals a breakthrough in optoelectronic regulation, which is expected to provide wider application possibilities in the realm of next-generation electronics.

    Abstract (Chinese) i Abstract (English) ii Contents iv List of Figures vii Chapter 1 General Introduction 1 1.1 Classic 2D Materials for Next-Generation Electronics 3 1.1.1 Graphene (Gr) 7 1.1.2 Hexagonal Boron Nitride (h-BN) 10 1.1.3 Transition Metal Dichalcogenides (TMDs) 13 1.1.4 Ambipolar Materials Represented by ReSe2 16 1.2 Memory Strategies based on vdW Heterostructures 19 1.2.1 Embedded Layered Design of Floating-Gate (FG) Structures 23 1.2.2 Photoinduced Doping (PD) Enabled by Defect Engineering 29 1.3 Artificial Synapses Simulated by 2D Electronics 33 1.3.1 Synaptic Plasticity in Artificial Synapses 36 1.3.2 Metaplasticity in Artificial Synapses 41 1.4 Research Motivation and Thesis Layout 44 Chapter 2 Theoretical Background 48 2.1 Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET) 49 2.1.1 Introduction & Structure 49 2.1.2 Operating Principle 52 2.1.3 Electrical Parameters 61 2.2 Non-Volatile Memory (NVM) 67 2.2.1 NAND Flash 68 2.2.2 Silicon-Oxide-Nitride-Oxide-Silicon (SONOS) 71 Chapter 3 Experimental Section 74 3.1 Device Fabrication 74 3.2 Measurement Instruments 80 Chapter 4 Artificial Visual Synapse Based on ReSe2 Photoactive Floating-Gate Memory (P-FGM) 82 4.1 Introduction & Literature Review 82 4.2 Design & Motivation 88 4.3 Device Structure & Material Analysis 90 4.4 Electrical Properties & Mechanism 95 4.4.1 Typical Three-Terminal Floating-Gate Memory (FGM) 95 4.4.2 Two-Terminal Photoactive Floating-Gate Memory (P-FGM) 99 4.5 Demonstration of Synaptic Feature Emulation 104 4.5.1 Characteristics of Synaptic Plasticity: LTP/LTD 104 4.5.2 Display of STDP: Hebbian Learning Rule 111 Chapter 5 Transistor-Memory Transition Modes in ReSe2 Photoinduced-Doping Reconfigurable Field-Effect Transistor (PD-RFET) 118 5.1 Introduction & Literature Review 118 5.2 Prototype of PD-RFET 124 5.2.1 Prototype I: Photoinduced-Doping Field-Effect Transistor (PD-FET) 124 5.2.2 Prototype II: Reconfigurable Field-Effect Transistor (RFET) 135 5.3 Design & Functionality 140 5.4 Device structure & Material Analysis 143 5.5 Electrical Properties & Mechanism 146 5.5.1 PD Operations: Reversible Polarity Transitions 147 5.5.2 Differential Electrical Behaviors of PG & CG 151 5.5.3 PG-CG interplay & Mechanism of CG Operation 156 5.5.4 Doping Tunability & Device Robustness 161 5.6 Potential Applications 166 5.6.1 Static Transistor Mode: Layout of Inverter Logic Gate Circuit 166 5.6.2 Dynamic Memory Mode: Application of Artificial Synapses 169 Chapter 6 Conclusions 172 References 174 Publications 187

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