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Investigation of astrocytic Slitrk2 functions in regulation of synaptic properties
No full textAstrocytic adhesion molecule, Excitatory synapse properties, Slitrk2, Tripartite synapseⅠ. Introduction
1.1 Synapses are key regulatory sites of neuronal networks 1
1.2 Synaptic cell adhesion molecules (CAMs) regulate the development and characteristics of synapses 1
1.3 SLITRK family proteins regulate excitatory and inhibitory synapses 2
1.3.1 SLITRK related brain disorders 3
1.3.2 Slitrk2 regulates excitatory synapses through interaction with PTPσ 4
1.4 Astrocytes play an important role through interactions with neurons 4
1.4.1 Astrocyte play roles in regulation of synapse formation and synaptic activity 5
1.5 Tripartite synapse 6
1.5.1 Dysfunction of astrocytes can lead to both neurodevelopmental and neurodegenerative disorders 8
1.5.2 Astrocytic cell adhesion molecules 11
1.5.3 Aquaporin-4 (AQP4) plays a crucial role during neurotransmission 13
Ⅱ. Material and Methods
2.1 Expression vectors 15
2.2 Antibodies 15
2.3 Cell culture 16
2.4 Production of recombinant viruses 16
2.5 In situ hybridization 18
2.6 Primary neuron and mixed glia culture 18
2.7 Immunocytochemistry, and image acquisition and analysis 19
2.8 Immunohistochemistry, and image acquisition and analysis 20
2.9 Quantitative RT-PCR in cultured cells 20
2.10 Cultured neuron electrophysiology 21
2.11 Hippocampal CA1 pyramidal neuron electrophysiology 22
2.12 Animals 23
2.13 Stereotactic surgery 23
2.14 Data analysis 24
Ⅲ. Results
3.1 Verification of astrocytic Slitrk2 expression in vitro and in vivo 25
3.2 Astrocytic Slitrk2 deficiency affects excitatory synaptic transmission in hippocampal cultured neurons 29
3.3 Hippocampal CA1-specific astrocytic Slitrk2 deletion affects excitatory synaptic transmission 35
3.4 Hippocampal CA1-specific astrocytic Slitrk2 deletion affects excitatory synaptic formation 39
3.5 Astrocytic Slitrk2-cKO phenotype is abolished in PTPσ-cKO hippocampal cultured neurons 40
3.6 Astrocytic Slitrk2-cKO affects AQP4 expression upregulation in hippocampal CA1 42
Ⅳ. Discussion 46
Ⅴ. References 50
Ⅵ. 요약문 55
Figures
Figure 1. Identification of Slitrk1 and Slitrk2 mRNA level in WT mouse.
Figure 2. Identification of mRNA level in cultured neuron, astrocyte and microglia.
Figure 3. Generation of conditional Slitrk2 knockout mice.
Figure 4. Validation of astrocytic Slitrk2 KO in cultured astrocyte.
Figure 5. Excitatory synaptic transmission is enhanced in neurons co-cultured in with Slitrk2-deleted astrocytes.
Figure 6. Excitatory synaptic transmission is enhanced in neurons co-cultured with astrocytes derived from Aldh1l1-Slitrk2 mice.
Figure 7. No significant difference is observed in synaptic transmission by treatment of both Slitrk2 WT and KO ACM.
Figure 8. Verification of astrocyte-specific GfaABC1D promoter operation.
Figure 9. Excitatory synaptic transmission is enhanced in hippocampal CA1-specific astrocytic Slitrk2-cKO mice.
Figure 10. Evoked excitatory synaptic transmission is not affected in hippocampal CA1-specific astrocytic Slitrk2-cKO mice.
Figure 11. Excitatory synaptic formation is enhanced in hippocampal CA1-specific astrocytic Slitrk2-cKO mice.
Figure 12. The astrocytic Slitrk2-cKO phenotype is not observed in PTPσ-cKO co-cultured neurons.
Figure 13. AQP4 expression level is upregulated in hippocampal CA1-specific astrocytic Slitrk2-cKO mice.
Figure 14. Summary of astrocytic Slitrk2 functions in tripartite synapses.MasterdCollectio
RT-Swap: Addressing GPU Memory Bottlenecks for Real-Time Multi-DNN Inference
No full textThe increasing complexity and memory demands of Deep Neural Networks (DNNs) for real-Time systems pose new significant challenges, one of which is the GPU memory capacity bottleneck, where the limited physical memory inside GPUs impedes the deployment of sophisticated DNN models. This paper presents, to the best of our knowledge, the first study of addressing the GPU memory bottleneck issues, while simultaneously ensuring the timely inference of multiple DNN tasks. We propose RT-Swap, a real-Time memory management framework, that enables transparent and efficient swap scheduling of memory objects, employing the relatively larger CPU memory to extend the available GPU memory capacity, without compromising timing guarantees. We have implemented RT-Swap on top of representative machine-learning frameworks, demonstrating its effectiveness in making significantly more DNN task sets schedulable at least 72% over existing approaches even when the task sets demand up to 96.2% more memory than the GPU's physical capacity. © 2024 IEEE
Gate-tunable quantum pathways of massless Dirac fermions in high harmonic generation
No full textStrong laser fields induce extreme nonlinear optical phenomena in solids such as high harmonic generation (HHG). We resolved the quantum pathways of massless Dirac fermions in graphene for HHG by controlling chemical potentials electrostatically. © 2024 The Author(s
길버트 셀 기반 능동 피드백을 활용한 크로스 포인트 상변화 메모리 기반 전압 모드 메모리 내 연산 매크로
No full textProcessing-in-memory, MAC operation, PRAM, OTS selector, Gilbert cellThis thesis introduces a phase change RAM (PRAM)-based voltage-mode processing-in-memory (PIM) macro, addressing two major challenges: low MAC accuracy due to device-to-device variation in resistive memory cells and limitations in sensing multiply-accumulate (MAC) results, and overhead associated with the analog-to-digital converter (ADC). The macro enhances the reliability of PRAM cell data through an iterative write verification that adjusts the write pulses. Additionally, this thesis proposes a new approach to voltage- mode sensing MAC operations. This method integrates the Gilbert cell into the bit-line (BL) decoder to dynamically regulate the resistance of the transmission gate, thereby enhancing the accuracy of the readout BL voltage (V.RBL), which represents the MAC results. This adjustment enhances the minimum sensing margin of V.RBL by 2.66 times. The implementation of an input-aware successive approximation register ADC (SAR ADC) reduces the average latency of a 6-bit SAR ADC from 6 clock cycles to 4.5 cycles. Additionally, the symmetric structure of the bit-lines and word-lines in this macro supports bidirectional MAC operations in a one selector-one resistor cross-point array, facilitating transpose matrix-vector multiplication. This research significantly enhances the performance and efficiency of AI applications and contributes to the development of emerging non-volatile memory-based PIM systems. Keywords: Processing-in-memory, MAC operation, PRAM, OTS selector, Gilbert cell|본 논문은 상변화 메모리 기반 전압 모드 메모리 내 연산 매크로를 소개하며, 저항성 메모리 셀의 장치 간 변동과, 누적-연산 결과 감지의 한계에 의한 낮은 곱셈-누산 정확도 및 아날로그-디지털 변환기와 관련된 오버헤드와 같은 문제를 해결합니다. 이 매크로는 쓰기 펄스를 조정하는 반복적 쓰기 검증 과정을 통해 상변화 메모리 셀 데이터의 신뢰성과 안정성을 향상시킵니다. 또한, 전압 모드 감지 곱셈-누적 연산에 대한 새로운 접근 방식을 제안합니다. 이 방법은 길버트 셀을 비트라인 디코더에 통합하여 전송 게이트 저항을 동적으로 조절함으로써 곱셈-누적 결과를 나타내는 판독 비트라인 전압의 정확도를 향상시킵니다. 이 조정은 판독 비트라인 전압의 최소 감지 여유를 2.66 배 향상시킵니다. 입력 인식형 연속 근사 레지스터 아날로그-디지털 변환기의 구현은 6 비트 연속 근사 레지스터 아날로그-디지털 변환기의 평균 지연 시간을 6 클록 사이클에서 4.5 사이클로 줄입니다. 또한, 이 매크로의 비트라인과 워드라인의 대칭 구조는 하나의 선택기-하나의 저항 교차점 배열에서 양방향 곱셈-누적 연산을 지원하여 전치 행렬-벡터 곱셈을 용이하게 합니다. 이 연구는 인공지능 응용 프로그램의 성능과 효율성을 크게 향상시키며, 차세대 비휘발성 메모리 기반 메모리 내 연산 시스템의 발전에 기여할 것입니다.I. Introduction 1
II. Background 4
2.1 Processing-in-memory with various memory technologies 4
2.2 Electrical properties of PRAM 8
2.3 PRAM-OTS-based 1S1R cross-point array 10
2.4 Bias schemes in a cross-point array 12
III. Proposed PRAM-based PIM macro 15
3.1 Overall architecture of the proposed PRAM-based PIM macro 15
3.2 Write pulse generator and the iterative write verification 16
3.3 Proposed voltage-mode MAC operation 19
3.4 Input-aware SAR ADC 23
3.5 Implementation of the 1/3 Bias Scheme and Decoder 24
IV. Simulation results and layout 25
V. Conclusion 30MasterdCollectio
Exploring Intervention Techniques to Alleviate Negative Emotions during Video Content Moderation Tasks as a Worker-centered Task Design
No full textVideos are dynamic and multi-modal compared to other types of content, making automatic fltering difcult, which is why content moderators play a crucial role. However, video content moderators are exposed to more profound emotional labor because videos contain rich visual information, sometimes including even harmful content, such as violent or terrifying scenes. In this work, we explore the efect of six intervention techniques on alleviating negative emotions during video content moderation tasks. We conducted one online crowdsourcing experiment and two controlled user studies to fnd out that (i) interleaving with positive videos or (ii) cartoonization could signifcantly reduce negative emotions in the moderators. Participants reported that the advantages of these approaches are in helping reduce negative emotions at the time of moderation while existing approaches focus on post-task activities (e.g., relaxation, talking with others, or getting a hobby). We discuss the applicability of our fndings to broader tasks, including improvement in intervention techniques. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM
Temporal Patterns of Angular Displacement of Endosomes: Insights into Motor Protein Exchange Dynamics
Get PDFThe material transport system, facilitated by motor proteins, plays a vital role in maintaining a non-equilibrium cellular state. However, understanding the temporal coordination of motor protein activity requires an advanced imaging technique capable of measuring 3D angular displacement in real-time. In this study, a Fourier transform-based plasmonic dark-field microscope has been developed using anisotropic nanoparticles, enabling the prolonged and simultaneous observation of endosomal lateral and rotational motion. A sequence of discontinuous 3D angular displacements has been observed during the pause and run phases of transport. Notably, a serially correlated temporal pattern in the intermittent rotational events has been demonstrated during the tug-of-war mechanism, indicating Markovian switching between the exploitational and explorational modes of motor protein exchange prior to resuming movement. Alterations in transition frequency and the exploitation-to-exploration ratio upon dynein inhibitor treatment highlight the relationship between disrupted motor coordination and reduced endosomal transport efficiency. Collectively, these results suggest the importance of orchestrated temporal motor protein patterns for efficient cellular transport. © 2024 The Authors. Advanced Science published by Wiley-VCH GmbH.TRUEsciescopu
강유전체 기반 뉴로모픽 시스템
No full textFerroelectric, Field-Effect Transistors (FET), Low-power system, Neuromorphic computing본 논문은 현대 컴퓨팅 시스템이 직면한 폰 노이만 구조의 병목현상을 해결하고자 강유전체 재료를 사용한 신경 모방 시스템의 설계 및 구현에 중점을 둡니다. 데이터 중심 애플리케이션은 빠른 접근 시간, 스케일링 호환성, 저전력, 저비용, AI 작업 실행 능력을 요구하며, 빅데이터의 급격한 증가는 알고리즘 및 아키텍처의 복잡성을 증대시켜 에너지 소비를 크게 증가시키고 있습니다. 이러한 기술적 요구사항을 충족시키기 위해 뇌의 병렬 처리를 모방하는 신경 모방 컴퓨팅 아키텍처에 대한 연구로, CMOS 기술을 사용한 기존의 신경 모방 시스템이 등장하였습니다. 하지만, CMOS 기술 기반의 시냅스 회로는 매우 복잡하여 넓은 면적과 제작 비용 상승을 요구하는 단점이 있습니다. 이러한 단점으로, CMOS 회로 기반 시냅스는 실제 인간 뇌를 모방하기에 부적절 합니다. 이러한 한계를 단일 시냅스 소자를 통해 해결하고자 합니다.
단일 시냅스 소자의 대표적인 강유전체 재료는 전력 없이도 데이터를 유지할 수 있는 능력으로 인해 신경 모방 애플리케이션에 매우 유망합니다. 이 재료들은 반복적인 데이터 읽기 및 쓰기를 지원하며, 다중 수준 저장과 빠른 스위칭을 가능하게 하여 복잡한 계산과 실시간 처리에 적합합니다. 그러나 이 재료들은 극성 특성을 위한 고온 처리 요구로 인해 현재 제조 공정 및 CMOS 기술과의 호환성 문제에 직면하고 있습니다. 본 논문은 다양한 재료와 구조를 사용하여 강유전체 메모리를 활용한 시스템을 구축하는 것에 중점을 두며, 이를 통해 뇌에서 영감을 받은 뉴로모픽 컴퓨팅 기능을 구현합니다. 다양한 강유전체인PVDF, PZT, HZO 등 재료의 특성을 비교 분석하며, 각 재료가 신경 모방 장치에 적합한지에 대한 평가를 진행합니다. 최적화된 강유전체 공정을 가지고 CMOS 기술과의 호환성 및 스케일링 가능성을 평가하고, 이를 통해 신경 모방 아키텍처의 효율성을 검증합니다. 추가적으로, 다양한 재료들의 전기-기계적 특성 및 처리 호환성을 상세히 검토하여, 신경 모방 장치에서의 최적화 사용 방안을 제시합니다.
실리콘 채널 기반 FeFET 및 산화물 채널 기반 Fe-TFT의 개선을 통해 신경 모방 시스템의 효율성과 신뢰성을 높이는 방안을 탐구합니다. 퍼니스, 빠른 열처리 및 레이저 어닐링 기술을 사용하여 다양한 물질이 사용되는 복합 공정에서의 재료 특성을 최적화하고, 이를 통해 메모리 장치의 성능을 향상시키는 방안을 모색합니다. 이러한 기술을 통해 논문에서는 현대 컴퓨팅 시스템의 진화에 따른 주요 도전과제를 다루며, 이를 극복하기 위한 강유전체 메모리 기술의 접근법과 다양한 강유전체 기반 트랜지스터 구조를 탐구합니다. 첫번째로, 실리콘 채널 기반 FeFET의 열처리 과정에서 오는 확산 문제를 제어하기 위하여 기능성 확산 차단막을 활용한 메모리를 제시합니다. 더 나아가, 근본적인 확산 문제를 해결 하기 위해 산화물 채널 기반 bottom gate Fe-TFT를 통해 메모리 기능을 검증합니다. 마지막으로, 시스템 통합 과정에서 엄격한 열 에너지 관리를 위해 레이저 어닐링 기술을 적용한 Fe-TFT 소자를 검증합니다. 본 연구는 강유전체 재료를 사용한 신경 모방 시스템의 성능과 신뢰성을 향상시킬 새로운 방법을 제시하며, 향후 지능형 컴퓨팅 솔루션으로의 가능성을 모색합니다.
|In the semiconductor industry, data processing performances are growing exponentially under Moore's Law. Despite these advancements, current computing architectures still face increasing technical demands for speed, efficiency, and adaptability. The conventional von Neumann architecture has reached a technical performance limit, because of the serial processing bottleneck between memory and the processor. This paper addresses a technology that emulate the synapse-processing capabilities, which are necessary for exploring neuromorphic computing. Neuromorphic computing promises to overcome significant limitations of current technology by leveraging parallel processing and energy efficiency similar to biological systems, making this exploration critically important. This research focuses on ferroelectric material based transistors employing Lead Zirconate Titanate (PZT) and Hafnium Zirconium Oxide (HZO), which is one of appropriate candidates for developing neuromorphic systems that can effectively emulate cognitive functions such as memory retention and sensory processing without the need for continuous power supply. The materials are particularly advantageous due to their outstanding polarization capabilities, which are essential for multi-level characteristics that excellently mimic the synaptic weights of the human brain, leading to lower power operation. However, typical high temperature annealing processes (above 550°C) may affect the channels and electrodes, limiting their use in various system. Therefore, this study precisely investigated the fabrication, functionalization, and application of these ferroelectric materials within various semiconductor devices, focusing particularly on their integration into ferroelectric field-Effect transistors (FeFETs) and ferroelectric thin-film transistors (FeTFTs). Initially, processes were optimized and the electrical properties of various ferroelectric materials such as PVDF, PZT, and HZO were analyzed. Through the analysis of parameters including dielectric constant, materials suitable for low-power operation and neuromorphic applications were explored. A design engineering with various ferroelectric materials approach was taken to integrate P-Si and HZO ferroelectrics. Instead of adding a simple sub-layer, which is required generally to protect Si diffusion to ferroelectric gate oxide, whereas it causes power consumption and depolarization, we added a functional layer to improve the memory effect compared to the existing one. The proposed device has an in situ HZO/HfO2/Al2O3 stacked film structure, which is compatible for Si with the metal–oxide–semiconductor (MOS) process based on all atomic layer deposition. Since the appropriate bandgap difference between Al2O3 and HfO2, stable charge trap operation was achieved. High-quality ferroelectric HZO film characteristics were shown by minimizing defects and Si diffusion through the sub-layer of Al2O3/HfO2. Therefore, HZO as a blocking layer enhances the memory performance of the charge trap structure due to its specific polarization effect. The proposed device had the high polarization characteristics of HZO (2Pr > 20 μC/cm2) along with a MOS-cap window (> 4 V), good retention capability (> 10 years), fast program/erase response operation times ( 105 cycles) while operating as a form of single level cell. By comparing Al2O3 and ferroelectric HZO as a blocking layer of the charge trap device, we confirmed that the HZO/HfO2/Al2O3 multi-layer structure had excellent characteristics according to various memory performance indicators. Our proposed high-performance charge trap flash memory can be employed in various applications, including Si-based three-dimensional structures with artificial intelligence systems. Additionally, in FeTFT, neuromorphic devices using PZT and HZO materials were investigated. An indium gallium zinc oxide (IGZO) channel back-gate TFT structure was chosen to address the diffusion of the channel material during the annealing process for crystallization of PZT and HZO. By annealing PZT, post- deposition process using IGZO as channel structure, the co-diffusion of bonding material and oxygen can be minimized, resulting in high and stable performance of FeTFT. During the production of the oxide-based multi- layer structure, the partial pressure conditions of the system were strictly investigated to minimize diffusion and defect phenomena. The basic operations of synaptic short-term memory (STM) and long-term memory (LTM) were also analyzed to confirm the applicability of neuromorphic devices. Due to the high dielectric constant and polarization properties of PZT, the power consumption of the spike signal used for spike-dependent plasticity changes can be reduced to 10 pJ. Additionally, a wide dynamic range of Gmax/Gmin≅ 1000 was obtained, and the channel conductance was maintained for more than 40000 s. The optimized pulse achieved multi-level states (> 32), making the learning process efficient. To solve the more fundamental thermal problem, HZO integrated IGZO TFT as a neuromorphic device through laser process engineering. For selective annealing of hafnia-based FeFETs, a nanosecond pulsed laser was used to precisely control the depth of heat penetration within the thin film. Sufficient thermal energy was transferred to the IGZO oxide channel and HZO ferroelectric gate oxide without causing thermal damage to the bottom layer, which has a low transition temperature ( 106, retention > 106 s) were achieved in ferroelectric HZO films. The resulting FeFET exhibited a wide memory window (> 1.7 V) along with a high on/off ratio (> 105). It also showed appropriate ferroelectricity (2·Pr, 14.7μC/cm2). Due to its high multi-level state processing and power efficiency, PZT TFT shows recognition accuracy of up to 84.72% in neuromorphic benchmarking systems. On the other hand, HZO FeFET manufactured using laser annealing has a fast response time and excellent stability, making it suitable for real-time processing and various structural configurations, and achieving a recognition rate of over 88.83%. Both structures are promising for neuromorphic systems with high recognition accuracy. These advances highlight the critical role of ferroelectric devices in enhancing cognitive abilities and transforming neuromorphic computing with high accuracy and efficiency. The proposed neuromorphic frameworks improve structural integration and operational efficiency, enhancing density and energy efficiency. Advanced material characterization and device architectures drive next-generation computing technologies. These innovations create efficient, robust systems capable of handling complex computational demands. This work sets a benchmark for future research and the integration of neuromorphic technologies. Keywords: Ferroelectric, Field-Effect Transistors (FET), Low-power system, Neuromorphic computingList of Contents
Abstract i
List of contents ii
List of tables iii
List of figures vi
Ⅰ. Introduction
1.1 Overview 1
1.2 Background 2
1.3 Motivation 13
Ⅱ. Various ferroelectric materials for neuromorphic applications
2.1Introduction 22
2.2 Study of PVDF Ferroelectric Materials 23
2.2.1 Theoretical background of PVDF 23
2.2.2 Fabrication of M/F/M structure 27
2.2.3 Electrical and mechanical characteristics of PVDF 31
2.3 Study of PZT ferroelectric materials 31
2.3.1 Theoretical background of PZT 33
2.3.2 Fabrication process of PZT films 37
2.3.3 Electrical and mechanical characteristics of PZT films 39
2.4 Study of HZO ferroelectric materials 44
2.4.1 Fabrication parameter of HZO 44
2.4.2 Optimization of HZO Films 49
2.4.3 Electrical and mechanical characteristics of HZO films 51
2.5 Comparative analysis of various ferroelectric materials 52
Ⅲ. Silicon channel based FeFET for neuromorphic systems
3.1 Introduction 55
3.2 ALD process with Si-based channel device 59
3.3 Operational characteristics of HZO-blocking layer charge trap devices 60
3.3.1 Electrical characteristics HZO film with sub-layer 65
3.3.2 Optimization multi-layer structure 67
3.4 Advanced applications and reliability analysis 70
3.4.1 Analysis of memory window 70
3.4.2 Endurance and reliability in memory performance 72
3.5 Electrical characteristics of FeFET with silicon channels 73
3.6 Conclusion 74
Ⅳ. Design and fabrication for oxide channel-based Fe-TFT
4.1 Introduction 76
4.2 Characteristics of PZT Fe-TFT with conventional thermal annealing 77
4.2.1 Electrical and mechanical characteristics of PZT Fe-TFT 77
4.2.2 Memory operation of PZT Fe-TFT 80
4.3 Characteristics of HZO Fe-TFT with conventional thermal annealing 85
4.3.1 Depolarization effect of HZO on Fe-TFT device 85
4.4 Advanced annealing techniques 86
4.4.1 Background of laser annealing system 86
4.5 Device fabrication for 3D stack structure 91
4.5.1 Mechanical, electrical, and chemical characteristics 91
4.5.2 Fabrication of laser annealing HZO Fe-TFT 94
4.6 Optimization characteristics of HZO Fe-TFT 95
4.6.1 HZO Films for memorable TFT 95
4.6.2 Oxide channel for Fe-TFT 103
4.6.3 Electric characteristic of HZO Fe-TFT 106
4.7 Application of laser annealing process 109
4.7.1 Fabrication of flexible HZO-IGZO Fe-TFT 109
4.7.2 Electric characteristics of flexible HZO-IGZO Fe-TFT 111
4.8 Conclusion 112
Ⅴ. Various of ferroelectric-based neuromorphic systems
5.1 Introduction 114
5.1.1 Neuromorphic hardware design parameters 115
5.1.2 Digital and analog based of neuromorphic hardware 117
5.2 Power consumption comparison of various neuromorphic systems 118
5.2.1 Neural network and circuit systems 121
5.2.2 Linear function fitting 123
5.3 Performance comparison of ferroelectric based neuromorphic devices 125
5.3.1 HZO Fe-FET based neuromorphic device 125
5.3.2 Characteristics of Fe-TFT through pulse engineering 126
5.3.3 Conductance modulation of various ferroelectric based devices 130
5.3.4 Accuracy comparison in multi-parallel systems 132
5.4 Conclusion 133
Ⅵ. CONCLUSIONDoctordCollectio
고체 전해질 배터리에서 Li¬4SiS4의 다형체 결정 구조 분석 및 이온 전도성 향상을 위한 Sb 치환
No full textall-solid-state batteries|sulfide solid electrolyte, polymorph, superionic conductor, aliovalent substitution, thio-silicate유기 기반 액체 전해질의 안전 문제로 인해 리튬 이온 배터리에서 리튬 이온 전도체에 대한 연구가 활발히 진행되었습니다. 비용 효율성에도 불구하고, 티오-실리케이트 Li4SiS4는 결정 구조 정보의 불명확성으로 인해 주목받지 못했습니다. 본 연구에서는 두 가지 Li4SiS4 다형체와 그들의 다가 치환 시리즈인 Li4–xSi1–xSbxS4의 결정 구조와 전기화학적 특성을 규명했습니다. 연구 결과, 다형체들은 주로 SiS4 사면체의 적층 구성에서 차이가 있으며, 고온 상이 저온 상보다 더 질서 정연하지만, 이들은 유사한 이온 전도 특성을 보여줍니다. 리튬의 밀집된 배치는 이온 이동을 제한하여, Sb5+의 다가 치환을 통해 리튬 공공을 생성함으로써 리튬 이동성을 향상시킬 필요가 있습니다. x = 0.15인 치환 시리즈 Li4–xSi1–xSbxS4는 전도성이 10배 증가했으며, 이는 리튬 공공이 이온 전도에 미치는 영향을 보여줍니다. 주기적 전압 측정법을 통해 Li3.85Si0.85Sb0.15S4가 고체 전해질 배터리에 적합함이 확인되었습니다. 본 연구는 Li4SiS4의 이온 전도성이 SiS4 사면체 적층보다는 리튬 이온 농도에 더 의존함을 제시하며, 고성능 고체 배터리 소재 개발을 위한 전략적 통찰력을 제공합니다.|Safety concerns regarding organic-based liquid electrolytes in Li-ion batteries have led to extensive research on lithium-ion conductors. Despite cost-effectiveness, thio-silicate Li4SiS4 has been overlooked owing to unclear crystallographic information. This study clarifies the crystal structures and electrochemical properties of two Li4SiS4 polymorphs and their aliovalent substitution series, i.e., Li4–xSi1–xSbxS4. Our findings indicate that the polymorphs differ primarily in their SiS4 tetrahedra stacking configurations, with the high-temperature phase being more orderly than the low-temperature phase. However, they exhibit similar ionic-transport properties, indicating that the tetrahedra stacking minimally affects Li-ion mobility. We found that the dense packing of Li in these structures restricts ion movement, necessitating the creation of Li vacancies through the aliovalent substitution of Sb5+ for Si4+ to enhance Li mobility. The substitution series Li4–xSi1–xSbxS4 with x = 0.15 exhibited a tenfold conductivity increase, signifying the influence of Li vacancies on ionic transport. Cyclic voltammetry confirmed the suitability of Li3.85Si0.85Sb0.15S4 as a solid electrolyte for all-solid-state batteries. This study suggests that the ionic conductivity in Li4SiS4 depends more on Li-ion concentration than on SiS4 tetrahedra stacking, providing strategic insights for developing more efficient solid-state battery materials.Abstract ⅰ
List of contents ⅱ
List of figures ⅲ
List of tables ⅴ
List of supporting data ⅵ
Ⅰ. Introduction 1
Ⅱ. Experimental Section
2.1 Synthesis 5
2.2 Structural analysis 6
2.3 Electrochemical Analysis 10
2.4 Bond Valence Sum Calculations 12
Ⅲ. Results and Discussion
3.1 Structural analysis 14
3.2 Ionic-Transport Properties 22
3.3 Aliovalent Substitution Effect on LT-Li4SiS4 25
3.4 Electrochemical Performance of Li3.85Si0.85Sb0.15S4 32
Ⅳ. Conclusion 35
Ⅴ. Supporting data 36
Ⅵ. Reference 58MasterdCollectio
Efficient visible light-induced H2 production by g-C3N4/NiFe Prussian blue composites
No full textHydrogen (H2) produced via photocatalytic water splitting shows great potential as a renewable alternative to fossil fuels, as it uses clean and renewable resources (water and solar light). However, low efficiency remains a significant challenge for this technology. In this study, we synthesized novel graphitic carbon nitride (GCN)–Prussian blue analog (PBA) heterostructure composites using suitable PBAs for photocatalytic reactions, and explored their application in visible-light-induced H2 production. GCN-PBA heterostructure composites were synthesized using PBAs containing Ni, Co, and Fe, and their photocatalytic activities under visible light irradiation were compared. The visible-light absorption characteristics and H2 production efficiency of the GCN-PBA composites were characterized. The GCN-NiFe heterostructure composite showed excellent visible-light-induced H2 production efficiency, indicating effective charge separation and transfer characteristics that enhanced the photocatalytic activity of GCN. These findings contribute to the development of efficient photocatalytic materials for solar H2 production, thereby contributing to the advancement of renewable energy technologies. © 2024 Elsevier LtdFALSEsciescopu
