원자층 제어를 통한 산화물 박막 및 계면 특성 응용 투명 태양전지, 3진법 소자 및 시냅스 소 자 연구 = Atomic Layer Engineering of Oxide Films and Interfaces for Applications in Transparent Solar Cells, Ternary Value Logic Devices, and Synaptic Devices

국문 초록 (Abstract)

4차 산업혁명 이후, 반도체 시장의 규모는 매년 확장되고 있으며, 인공지능, 전기차 등의 발전으로 그 수요가 증가될 것으로 예상된다. 한편, 시스템 반도체 업계에서는 소자의 성능과 효율을 개선하기 위해 반도체 미세화 공정을 개발을 하고 있으며, 이러한 기술들은 최첨단 칩을 요구하는 인공지능(AI), 자율주행차용 칩 등에 활용하기 위한 방향으로 주력하고 있다. 원자층 증착법(ALD)은 이러한 나노 공정의 필수적인 박막 증착 기술이다. 본 논문에서는 ALD 공정 엔지니어링을 통해 다양한 분야에 접목시켜 연구를 수행하였다. 먼저 ALD의 super-cycle 공정을 이용하여 새로운 물질인 AlxTiyO 박막을 제조하였으며, 박막을 구성하는 Al과 Ti의 조성비를 조절함으로써 반도체 물성인 유전율을 제어하는 연구를 수행하였다. 이렇게 제조한 산화물 박막을 창호형 투명 태양전지에 적용하여 시야성 확보, 다양한 색상 구현, 외부 환경으로부터 태양전지를 보호할 수 있는 봉지막으로 활용하였다. 투명 태양전지의 투과도 저하 없이 태양전지 효율을 기존 태양전지 대비 12% 증가했으며, 수증기 투과도는 1.96 ×10-3 g/m2 ‐day로 우수한 봉지막 성능을 확보하였다. 또한, ALD 공정 엔지니어링을 통해 AlxTiyO의 굴절률과 Al2O3의 두께를 조절함으로써 광학적 물성을 조절하여 8가지의 다양한 색상을 구현하는 결과를 보였다. 이러한 결과들은 창호형 투명 태양전지로써 요구사항들을 충족할 수 있는 결과이다. 다음으로는 3진법 반도체 소자를 개발하기 위해 ALD로 제조한 산화물 박막을 이용하였다. 3진법 소자는 차세대 대체 고효율 소자로 주목받는 연구 분야이며, 3개의 상태를 갖는 반도체 소자로 동일한 면적에서 고집적도, 고효율 동작이 가능한 소자이다. 본 연구에서 고안한 3진법 소자는 기존 트랜지스터 구조에 게이트 절연막으로 ALD로 제조한 5 nm의 초박막 Al2O3를 사용하여 고전압에서 발생하는 Fowler-Nordheim 터널링을 활용하여 3가지 상태를 구현한 소자이다. 본 소자의 소스 전극에 저항을 연결하여 VIN 대비 VOUT을 측정하였을 때 3가지 상태가 나타났으며, 특히 안정적인 중간 상태의 구현이 가능하다. 3진법 소자의 특성이 동확률 동작(equiprobable behavior)을 잘 나타냈으며, 200번의 동작에서도 내구성이 우수한 소자를 제작했다. 마지막으로 새로운 미래형 반도체인 시냅스 소자를 개발하여 현재 봉착한 컴퓨터 구조의 한계를 타계할 방안을 고안하였다. 오늘날 사용하는 기존의 폰노이만 컴퓨터 구조는 인공지능 활용에 있어 방대한 양의 데이터 처리할 때 생기는 속도 및 소비 전력 측면에서의 한계를 극복하기 위한 대체가능한 차세대 반도체 소자 개발이 필요하다. 뉴로모픽 컴퓨팅은 뉴런과 시냅스의 연결로 이루어진 인간의 뇌의 병렬적인 정보 처리를 모사하여 저전력, 고효율 컴퓨팅이 가능하다. 시냅스 소자는 뇌를 구성하는 시냅스 동작을 모방한 반도체 소자로 뉴런으로부터 전달된 신호를 통해 학습하고 저장하는 소자이다. 선행 연구된 채널의 계면 전하 트랩을 활용하는 TiO2 기반의 메모리 소자에 ALD 공정을 통한 계면 처리와 박막 조성제어를 통해 전하 트랩을 컨트롤하여 광시냅스 소자를 구현하는 방법을 고안하였다. 이때, 소자의 전력 효율을 높이기 위하여 기존의 메모리 소자 구조에 고유전 절연체 박막인 HfO2 박막을 적용하기 위한 최적화된 ALD 공정을 수립하였으며, 듀얼 게이트 절연막 구조의 광시냅스 소자를 제작했다. 본 연구에서 제작한 HfO2 박막은 HAC3라는 새로운 전구체를 활용하여 별도의 어닐링 공정 없이도 14.3의 고유전 박막을 제조할 수 있었다. 결과적으로, HfO2를 적용하였을 때 게이트 동작 전압을 1/4로 획기적으로 줄일 수 있었다. 광반응성을 가지는 TiO2 박막에 365 nm 파장에 대한 광자극을 인가하여 시냅스의 대표적인 특성인 STP, PPF, LTP 동작을 모방할 수 있었다. 추가적으로, 다양한 파장의 광자극에 대하여 광시냅스 소자의 트랩된 전하의 lifetime이 달라지는 것을 확인함으로써, 다양한 파장을 활용한 고성능 광시냅스 소자의 개발 가능성을 제시하였다. 또한, 인간의 두뇌 활동을 모사하는 하드웨어의 필요성으로 시각 정보 인식과 기억의 장기화에 대한 뇌 활동 매커니즘을 모사하는 시냅스 소자를 개발하기 위한 연구를 진행했다. ALD 공정을 통해 산화물 박막을 제조할 때 조성을 제어하여 산소 과잉의 SiOx 박막을 활용했다. SiOx는 채널과의 계면 트랩 자리에 전하를 제공하는 역할로 채널층인 TiO2와 접하는 구조를 가지며 전기 자극에 대한 시냅스 동작이 가능해진다. 광자극에 의해 트랩되는 전하는 shallow trap으로 트랩된 전하의 lifetime이 짧아 시각의 정보 인지 기능을 모사한다. 반면, 전기자극에 의해 트랩된 전하는 deep trap으로 lifetime이 길어 정보 기억 기능을 모사할 수 있다. 특히, 정보 기억 동작에서 게이트에 전압에 인가되는 읽기 전압에 따라 기억의 장기화 정도가 달라지는데 이는 인간의 주의력에 따른 기억의 유지정도를 조절할 수 있음을 모사할 수 있다. 본 연구에서는 ALD 공정을 통해 조성을 정밀하게 제어한 박막들을 활용하여 태양전지, 3진법 소자, 시냅스 소자 분야에 성공적으로 응용할 수 있었다. 향후, 차세대 메모리 소자 및 인공지능 하드웨어 구현에 있어 중요한 자료로 활용되길 기대한다. 주요단어(Key words): 원자층 증착, 산화물 반도체, 박막 엔지니어링, 시냅스 소자, 3진법 소자

다국어 초록 (Multilingual Abstract)

Since the 4th industrial revolution, the semiconductor market has been expanding annually, and the demand is expected to increase with advancements in artificial intelligence (AI) and electric vehicles. In the system semiconductor industry, miniaturization processes are being developed to enhance the performance and efficiency of devices. These technologies focus on applications in advanced chips for AI and autonomous driving vehicles. Atomic layer deposition (ALD) is an essential thin-film deposition technique for such nano- processes. This thesis explores the application of ALD process engineering in various fields. Firstly, a novel material, AlxTiyO thin film, was fabricated using the super- cycle process of ALD. By controlling the composition ratio of Al and Ti in the thin film, research was conducted to adjust the dielectric constant, a semiconductor property. The fabricated oxide thin film was applied to window-type transparent solar cells, serving as a passivation layer that enhances visibility, implements various colors, and protects the solar cell from external environments. This application increased the efficiency of transparent solar cells by 12% compared to conventional solar cells without reducing transparency, and the moisture barrier performance was excellent with a water vapor transmission rate of 1.96 ×10-3 g/m2- day. Additionally, by adjusting the refractive index of AlxTiyO and the thickness of Al2O3 through ALD process engineering, optical properties were controlled to achieve eight different colors. These results meet the requirements for window- type transparent solar cells. Secondly, oxide thin films fabricated using ALD were utilized to develop ternary semiconductor devices. Ternary devices are a research area gaining attention as a next-generation high-efficiency alternative, allowing high-density and high-efficiency operation within the same area due to their three-state configuration. The ternary device designed in this study uses a 5 nm ultra-thin and uniform Al2O3 gate insulator manufactured via ALD, employing Fowler- Nordheim tunneling at high voltages to implement three states. When measuring VOUT versus VIN with a resistor connected to the source electrode, three distinct states were observed, demonstrating the ability to implement a stable intermediate state. The ternary device's characteristics showed equiprobable behavior, and it remained durable after 200 cycles. Lastly, the study aimed to overcome the current limitations of computer architecture by developing synaptic devices, a new type of future semiconductor. The von Neumann architecture currently in use faces challenges in speed and power consumption when processing vast amounts of data for AI applications. Neuromorphic computing, which mimics the parallel information processing of the human brain through neurons and synapses, offers low-power, high-efficiency computing. Synaptic devices simulate the functions of biological synapses by learning and storing information from signals transmitted by neurons. This study devised a method to implement optical synaptic devices by controlling charge traps through ALD process interface treatment and thin-film composition in TiO2-based memory devices utilizing interfacial charge traps. To enhance the device's power efficiency, an optimized ALD process was established for applying a high-k dielectric HfO2 thin film to the existing memory device structure, resulting in a dual-gate insulator optical synaptic device. The HfO2 thin film, using the new precursor HAC3, achieved a high-k value of 14.3 without additional annealing processes. Consequently, the application of HfO2 significantly reduced the gate operating voltage to one-fourth of its original value. The TiO2 thin film, which is photo responsive, mimicked the synaptic functions of STP, PPF, and LTP under 365 nm light stimulation. Additionally, by confirming that the trapped charge lifetime of the optical synaptic device varies with different wavelengths of light stimulation, the potential for developing high-performance optical synaptic devices utilizing various wavelengths was demonstrated. Furthermore, research was conducted to develop synaptic devices that simulate brain activity mechanisms for visual information recognition and memory retention, emphasizing the need for hardware that mimics human brain functions. Oxygen-excess SiOx thin films, with precisely controlled composition through ALD, were used. SiOx interfaces with the channel, providing charge traps and enabling synaptic operations with the TiO2 channel layer. Charges trapped by light stimulation are shallow traps, modeling visual information recognition with a short lifetime. In contrast, charges trapped by electrical stimulation are deep traps, modeling memory retention with a longer lifetime. The degree of memory retention varied with the read voltage applied to the gate during memory operation, simulating the modulation of memory retention based on human attention. This study successfully applied thin films with precisely controlled composition through ALD processes to fields such as solar cells, ternary devices, and synaptic devices. It is anticipated that the results will serve as important data for the implementation of next-generation memory devices and AI hardware. Key words: Atomic layer deposition, Oxide semiconductor, Materials engineering, Synaptic devices, Ternary value logic devices

목차 (Table of Contents)

• 1. Introduction 1
• 1.1. Motivation 1
• 1.1.1. Development of Artificial Intelligence Technology ·· 1
• 1.1.2. Limitation of complementary hardware ·· 1
• 1.2. Future trends in Semiconductor Research ·· 3
• 1.2.1. Ternary Value Logic devices ·· 3
• 1.2.2. Synaptic devices ·· 3
• 1.3. Atomic Layer Deposition ·· 5
• 1.3.1. Novel Films by super-cycle of ALD ·· 6
• 1.3.2. Materials Engineering by ALD ·· 7
• 2. Employment of AlxTiyO films for Transparent Solar Cells ·· 9
• 2.1. Introduction ·· 9
• 2.2. Experimental Procedures ·· 13
• 2.2.1. Fabrication of Transparent solar cells ·· 13
• 2.2.2. Preparations of Back Passivation Layers ·· 15
• 2.2.3. Characterization Techniques ·· 16
• 2.3. Results and Discussion ·· 17
• 2.3.1. WVTR of Al2O3, TiO2, and ATO(3,1) Films and Stability of Transparent a-Si:H Solar Cells ·· 17
• 2.3.2. Electrical Characteristics of Solar Cells employing BPLs of various Al2O3 thicknesses ·· 19
• 2.3.3. Electrical Characteristics of Solar Cells employing BPLs with various ATO composition rates ·· 21
• 2.3.4. Color Realization for Transparent a-Si:H Solar Cells ·· 23
• 2.4. Summary ·· 26
• 3. Ternary Value Logic devices ·· 27
• 3.1. Introduction ·· 27
• 3.2. Experimental Procedures ·· 30
• 3.2.1. Fabrication of TVL Devices ·· 30
• 3.2.2. Analysis of the Characteristics of the TVL Devices ·· 30
• 3.3. Results and Discussion ·· 31
• 3.4. Summary ·· 42
• 4. Photo-synaptic devices ·· 43
• 4.1. Introduction ·· 43
• 4.2. Experimental Procedures ·· 46
• 4.2.1. Optimization of high- κ HfO2 films in ALD ·· 46
• 4.2.2. Fabrication of the photo-synaptic devices ·· 49
• 4.2.3. Characterization Techniques ·· 49
• 4.3 Results and Discussion ·· 50
• 4.3.1. Characteristics of PEALD-HfO2 Films ·· 50
• 4.3.2. Photo-synaptic Transistors with Dual Gate Dielectrics ·· 55
• 4.4 Summary ·· 62
• 5. Vision-Memory simulations synaptic devices ·· 64
• 5.1 Introduction ·· 64
• 5.1.1. Human’s Visual System and Memory ·· 64
• 5.1.2. Optical and Electrical Synaptic Devices for Vision-Memory simulations ·· 68
• 5.2 Experimental Procedures ·· 71
• 5.2.1 Fabrication of the Synaptic Devices ·· 71
• 5.2.2 Analysis of the Characterization of the Devices ·· 71
• 5.2.3 Neural Network Simulations ·· 71
• 5.3 Results and Discussion ·· 73
• 5.3.1. Thin Film Characteristics of Synaptic Devices ·· 73
• 5.3.2. Performance as Transistors in Synaptic Devices ·· 75
• 5.3.3 Characteristics of Synaptic Devices under Optical and Electrical Stimulation ·· 79
• 5.3.4. Neural Network Simulation of the Synaptic Devices ·· 90
• 4.4 Summary ·· 93
• 6. Conclusion and Future Works ·· 95
• Bibliography ·· 97
• List of Publications ·· 121

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