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Super elastic and negative triboelectric polymer matrix for high performance mechanoluminescent platforms
Full text linkMechanoluminescence platforms, combining phosphors with elastic polymer matrix, have emerged in smart wearable technology due to their superior elasticity and mechanically driven luminescent properties. However, their luminescence performance often deteriorates under extreme elastic conditions owing to a misinterpretation of polymer matrix behavior. Here, we unveil the role of the polymer matrices in mechanoluminescence through an interface-triboelectric effect driven by elasticity, achieving both high elasticity and brightness. By investigating interactions between elastic polymers and copper doped zinc sulfide microparticles, we reveal that elasticity significantly governed triboelectric effects for mechanoluminescence. In particular, high negative triboelectricity emerged as the key to overcoming poor triboelectric effect in extreme elastic conditions. This led to the discovery of polybutylene adipate-co-terephthalate silane and polycarbonate silane, achieving remarkable elasticity over 100% and a brightness of 139 cd/m2. These findings offer fundamental insights to select the optimal polymer matrix based on systematic parameters for various smart wearable applications. © 2025. The Author(s).TRUEsciescopu
Capacitor-type security element manufacturing method and capacitor-type security element manufactured using the same
No full textEutectic Liquid-Derived Carbon Materials: From Glassy Carbon and Graphene Synthesis to High-Performance Membrane Filtration and Photothermal Applications
No full textEL, graphene, glassy carbon, glassy graphene, COFs, CNPs, membrane, pollutant removal, DCMD, photothermal, salt desalinationList of Contents
Abstract i
List of contents ii
List of figures vi
Ⅰ. Introduction
1.1 Demand of Carbon Materials 1
1.2 Precursor for Carbon Material Synthesis 3
1.3 Types of Carbon Materials 4
1.4 Objective of The Study 5
1.5 References 6
IⅠ. From One Precursor to Multifunctional Carbon Materials: Synthesis of
Glassy Carbon, Glassy Graphene, and Graphene with Optimized
Mechanical and Electrical Properties
2.1 Introduction 12
2.2 Materials 14
2.3 Experimental Methods 14
2.3.1 Synthesis of Eutectic Liquid (EL) 14
2.3.2 Synthesis of Glassy Carbon (GC), Glassy Carbon (GG) and
Graphene 14
2.3.3 Glassy Carbon Flexibility Test 14
2.3.4 Characterization 15
2.4 Result and Discussion 15
2.4.1 Supramolecular Eutectic Liquid as Precursor for Glassy Carbon
Synthesis; Characterization and Properties 15
2.4.2 Glassy Graphene (GG) and Graphene Formation from
Supramolecular Eutectic Liquid 25
2.4.3 Multidimensional Glassy Carbon Coating with Eutectic Liquid as
the Precursor 29
2.5 Conclusion 32
2.6 References 33
ⅠII. Efficient Organic Pollutant Removal from Water Using Highly Dispersible
Carbon Nanoparticles Decorated with Covalent Organic Frameworks
3.1 Introduction 38
3.2 Materials 40
3.3 Experimental Methods 41
3.3.1 Synthesis of Eutectic Liquid (EL) 41
3.3.2 Synthesis of EL Soot Particles (ESP) 41
3.3.3 Synthesis of Oxidized ESP (ESPOX) 41
3.3.4 Synthesis of 1,3,5-triformylphloroglucinol 41
3.3.5 Synthesis of Covalent Organic Frameworks (COFs) 42
3.3.6 Synthesis of COF-ESPOX 42
3.3.7 Synthesis of COF-ESPOX/Pd 42
3.3.8 Adsorption Kinetics 42
3.3.9 Adsorption Isotherms 43
3.3.10 Recycle Test of COF-ESPOX 43
3.3.11 Catalytic Test of COF-ESPOX/Pd 43
3.3.12 Characterization 44
3.4 Result and Discussion 45
3.4.1 Formation of EL Soot Particle 45
3.4.2 Enhanced Water Pollutant Removal Using Highly Dispersible
Carbon Nanoparticles Embedded with Covalent Organic
Frameworks 50
3.4.3 Catalytic Property of COF-ESPOX Embedded with Palladium (Pd)
Nanoparticles (COF-ESPOX/Pd) 57
3.5 Conclusion 60
3.4 References 61
IV. Mixed Matrix Polymer Composites Membrane for Sustainability Water
Purification
4.1 Introduction 66
4.2 Materials 69
4.3 Experimental Method 69
4.3.1 Fabrication of PE-COF-ESPOX Membrane (PCEm) 69
4.3.2 Water Flux and Dye Removal Test 69
4.3.3 Direct Contact Membrane Distillation (DCMD) Test 70
4.3.4 Characterization 71
4.4 Result and Discussion 71
4.4.1 PCEm for Water Pollutant Removal 71
4.5 Conclusion 80
4.6 References 81
요약문 84DoctordCollectio
Priority-Based Resource Allocation with Reuse for Platoon Vehicles in 5G-V2X Network
No full textV2X network, Platoon, Vehicles, Resource allocation algorithm, Resource reuseList of Contents
Abstract i
List of contents ii
List of table iii
List of algoritms iv
List of figures v
Ⅰ. INTRODUCION 1
ⅠⅠ. BACKGROUND 6
2.1 V2X Communication Overview and NR-V2X 6
2.2 Platoon Communication 7
2.3 NR-V2X Resource Allocation 10
ⅠⅠⅠ. SYSTEM MODELING AND RESOURCE ALLOCATION ALGORITHM 13
3.1 System Model 13
3.2 Proposed resource allocation algorithm 17
ⅠV. RESULTS AND ANALYSIS 23
4.1 Simulation Configuration and Performance Metrics 23
4.2 Simulation Results and Analysis 26
V. CONCLUSION 32
REFERENCES 33
SUMMARY (Korean) 36
List of table
Table 4.1 Simulation Parameters in Simu5G and SUMO 23
List of algoritms
Algoritm 1 Pre-allocation 20
Algoritm 2 Resource Allocation for Platoon Vehicle 21
Algoritm 3 Resource Allocation for General Vehicle 22MasterdCollectio
Privacy-Preserving Image Captioning with Partial Encryption and Deep Learning
Full text linkAlthough image captioning has gained remarkable interest, privacy concerns are raised because it relies heavily on images, and there is a risk of exposing sensitive information in the image data. In this study, a privacy-preserving image captioning framework that leverages partial encryption using Double Random Phase Encoding (DRPE) and deep learning is proposed to address privacy concerns. Unlike previous methods that rely on full encryption or masking, our approach involves encrypting sensitive regions of the image while preserving the image’s overall structure and context. Partial encryption ensures that the sensitive regions’ information is preserved instead of lost by masking it with a black or gray box. It also allows the model to process both encrypted and unencrypted regions, which could be problematic for models with fully encrypted images. Our framework follows an encoder–decoder architecture where a dual-stream encoder based on ResNet50 extracts features from the partially encrypted images, and a transformer architecture is employed in the decoder to generate captions from these features. We utilize the Flickr8k dataset and encrypt the sensitive regions using DRPE. The partially encrypted images are then fed to the dual-stream encoder, which processes the real and imaginary parts of the encrypted regions separately for effective feature extraction. Our model is evaluated using standard metrics and compared with models trained on the original images. Our results demonstrate that our method achieves comparable performance to models trained on original and masked images and outperforms models trained on fully encrypted data, thus verifying the feasibility of partial encryption in privacy-preserving image captioning. © 2025 by the authors.TRUEsciescopu
Enhancing Electrochemical Performance of Ni-rich Cathode Materials through Dual Lithium-ion Conductive Coating
No full textKeywords: Ni-rich cathode materials, Surface modification, Li-ion conductive coating, Surface stabilization, Electrochemical performanceCHAPTER 1. INTRODUCTION 1
1.1. Lithium-ion batteries 1
1.2. Emergence of Ni-rich cathode materials 2
1.3. Challenges of Ni-rich cathode materials 3
1.3.1. Cation mixing 3
1.3.2. Electrolyte decomposition 4
1.3.3. Residual lithium compounds 5
1.4. Lithium-ion conductive coating (LCC) to enhance electrochemical performance of Ni-rich cathode materials 7
1.5. Objectives of This Research Work 8
CHAPTER 2. EXPERIMENTAL SECTION 12
2.1. Materials 12
2.2. Preparation of dual Lithium-ion conductive coated Ni-rich cathode materials 12
2.3. Characterization 13
2.4. Electrochemical Measurement 14
CHAPTER 3. Result and Discussion 15
3.1. Materials Characterization 15
3.2. Electrochemical characterizations 22
3.3. Post-cycling analysis 32
CHAPTER 4. Conclusion 36
Reference 39MasterdCollectio
APPARATUS AND METHOD OF RECOVERING IMAGE USING ARBITRARY BITWISE COEFFICIENT ESTIMATION FOR DE-QUANTIZATION
No full text딥러닝 기반의 암호화 및 난독화 된 데이터 자동 분석
No full textDeep Learning, Data Analysis, Cryptanalysis, Privacy-PreservingⅠ. INTRODUCTION 1
1.1. Motivations and Objectives 1
1.2. Overview 5
1.3. Contributions and Outline 7
Ⅱ. DEEP LEARNING-BASED ENCRYPTED DATA ANALYSIS 9
2.1. Deep Learning-based Cryptanalysis on Optical Cryptographic Algorithm 9
2.1.1. Methodology 9
2.1.2. Experiments 16
2.2. Deep Learning-based Cryptanalysis on Block Ciphers 23
2.2.1. Methodology 23
2.2.2. Experiments 36
2.3. Deep Learning-based Cryptanalysis on Public-Key Cryptography 49
2.3.1. Methodology 49
2.3.2. Experiments 52
Ⅲ. DEEP LEARNING-BASED OBFUSCATED DATA ANALYSIS 64
3.1. Methodology 64
3.1.1. Poisson-Multinomial Distribution-based Photon Counting Imaging (PMD-PCI) 64
3.1.2. Deep Learning-based Privacy-Preserving Image Classification Scheme 65
3.2. Experiments 70
3.2.1. Dataset 70
3.2.2. Implementation Details 70
3.2.3. Evaluation Metric 71
3.2.4. Results 72
Ⅳ. CONCLUSION AND FUTURE WORK 81
4.1. Summary and Discussion 81
References 85
요 약 문 91DoctordCollectio
The studies on pharmacodynamics of levodopa-induced dyskinesia and dopaminergic control of memory flexibility
No full textDopamine, Dopamine sensing, Dopamine receptor, Parkinson’s disease, Levodopa-induced dyskinesia, Hippocampus-dependent memory, Contextual memory도파민 (DA)은 우리 뇌에서 생성되는 신경 전달 물질의 일종으로, 자극의 유형에 따라 도파민은 독특한 뇌 회로를 통하여 신체 기능을 조절합니다. 이러한 도파민 회로의 기능 장애는 도파민 관련 질병의 발병과 진행을 초래할 수 있습니다.
첫 번째 파트에서는 도파민 동역학을 모니터링 하기 위한 첨단 신경과학 도구를 공동 연구자들과 함께 개발했습니다. 도파민의 정밀한 모니터링은 뇌 기능을 이해하고 파킨슨병(PD), 조현병, 중독 등 도파민 연관 신경질환의 치료법을 발견하는 데 중요합니다. 우리는 높은 도파민 민감도, 선택성, 생체적합성을 가진 새로운 DA 감지 도구를 개발하였고, 이를 통해 설치류 파킨슨병 모델에서 도파민 동역학을 성공적으로 모니터링했습니다. 또한, 생체 내 고속주기성 전압측정법 (FSCV)에 사용되는 새로운 분석 도구인 2차 유도 기반 배경 드리프트 제거 (SDBR)를 개발했습니다. 표준 FSCV는 화학적 흡착으로 인한 배경 충전 전류 축적으로 인해 빠른 도파민 동역학(분 단위의 변화)을 측정하는 유용한 도구입니다. 그러나 도파민 시스템을 이해하려면 긴 시간 범위(분에서 시간)에 걸친 도파민 동역학 모니터링 또한 필요합니다. 이 기술을 사용하여 생체 내에서 도파민의 변화를 짧은 시간에서부터 긴 시간까지 성공적으로 측정했습니다. 나아가 이 도구를 쥐의 반구성 파킨슨병 모델에 적용하여 레보도파 유도 운동이상증 (LID) 발병과 도파민 동역학 간의 관계를 밝혔습니다. 급성 레보도파 투여 후 도파민의 증가는 초기 파킨슨병 모델에서는 느리고 미미했으나, 레보도파 운동이상증 모델에서는 훨씬 빠르고 높게 증가했습니다. 또한, 레보도파 운동이상증 모델에서의 급속한 도파민 유도는 운동이상 회전 행동과 강한 양의 상관관계를 보였습니다.
두 번째 파트에서는 해마 치아 이랑의 도파민 수용 뉴런이 맥락 학습에 미치는 역할을 탐구했습니다. 해마는 일화적 기억 형성에 중요한 역할을 하지만, 정보가 다른 강도의 기억으로 저장되는 방식은 알려지지 않았습니다. 리포터 마우스 라인과 역행성 아데노관련바이러스 (AAV)를 사용하여 청반 영역이 치아 이랑으로 도파민을 분비할 수 있음을 확인했습니다. 치아 이랑은 해마 회로의 정보 유입 지점입니다. 또한, 치아 이랑 과립세포 (GCs)와 모시세포 (MCs)가 각각 도파민 수용체 1 (D1)과 2 (D2)를 발현함을 확인했습니다. 화학유전학적 억제와 조직학적 검증 기법을 포함한 능동 장소 회피 패러다임을 통해 모시 세포가 맥락 기억 형성에 미치는 역할을 발견했습니다. D2를 발현하는 모시세포는 맥락 기억 유연성에 독특한 역할을 가집니다. Drd2 억제 실험 결과, 모시세포 활동 증가로 인해 기억 유연성이 감소했으며, 화학유전학적 억제 실험에서는 행동 유연성의 촉진이 나타났습니다. 또한 생체 내 실시간 칼슘 이미징 기법을 통하여, 모시세포가 맥락 기억 과정에서 그들의 활성을 조절함으로써 유연한 기억 형성 조절을 할 수 있음을 확인하였습니다.
요약하자면, 박사 과정 동안 생체 내에서 활용 가능한 도파민 센싱 도구를 개발하고 이를 파킨슨병 동물 모델에 적용하여 약물 투여 후 긴 시간 동안 변화하는 도파민 패턴이 레보도파 운동이상증와 밀접한 연관이 있음을 확인하였습니다. 또한 해마 치아 이랑 내의 D2-발현 모시세포가 혐오 맥락 기억 학습에서의 역할을 규명했습니다. 이 연구들은 파킨슨병 및 알츠하이머병과 같은 기억 장애 치료를 위한 잠재적 치료 표적의 기전 이해에 중요한 연구가 될 수 있을 것입니다.|Dopamine (DA) is a type of neurotransmitter that is produced in our brain. Depending on the types of stimuli, DA modulates body functions via unique DA pathways. Malfunction of each pathway causes DA-related disease onset and its progression.
In the first part, I developed advanced neuroscience tools to monitor DA dynamics in multidisciplinary collaboratory projects. Precise monitoring of DA is important for understanding brain function and discovering treatment for DA-related neurological disorders, such as Parkinson’s disease (PD), schizophrenia, and addiction. We developed a new DA sensing tool which has high DA sensitivity, selectivity, and biocompatibility. Using these tools, we successfully monitored DA dynamics in vivo rodent PD model. Furthermore, we also developed a new analysis tool for in vivo fast-scan cyclic voltammetry (FSCV), which is called second-derivative-based background drift removal (SDBR). Standard FSCV is a useful tool for measuring phasic DA dynamics (changes in sub-minutes range) because of the accumulation of background charging current by chemical adsorption. However, to understand DA system, monitoring of tonic DA dynamics (changes in minutes to hour range) is also critical. Using this technique, we measured tonic and phasic change of DA in vivo. Furthermore, we applied this tool to mouse hemi-PD model to reveal the relationship between levodopa-induced dyskinesia (LID) onset and DA dynamics. We found increased tonic DA levels following acute levodopa administration were slow and marginal within the naïve PD model. However, these levels increased faster and higher in the LID model. Also, this rapid DA induction in LID has a strong positive correlation with dyskinetic rotation behavior.
In the second part, I explored the role of dopaminoceptive neurons in the hippocampal dentate gyrus for contextual and spatial memory. Despite significant role of dopamine in the memory process in the hippocampus, it remains unclear how each type of dopaminoceptive neurons responds to the environmental novelty and further involves in contextual and spatial learning. In the dentate gyrus (DG), dopamine receptor 1 (D1) is expressed in the selective subpopulation within granule cells (GCs), whereas dopamine receptor 2 (D2) is highly enriched in the hilar mossy cells. Using reporter mouse line and retrograde adeno-associated virus (AAV), I identified locus coeruleus (LC), but not ventral tegmental area (VTA) sends axonal projections into the dentate gyrus (DG), a gateway for cortical input to the trisynaptic circuit of the hippocampus. Using active place avoidance (APA) paradigm with chemogenetic inhibition and histological validation technique, MCs, which express D2, have a distinct role in contextual memory flexibility. The results of the Drd2 knockdown experiment showed decreased memory flexibility via increased MC activity. In contrast, chemogenetic inhibition experiments show facilitation of behavioral flexibility. And in vivo calcium imaging of MCs experiment identified that MCs tuned their activity along the learning process to achieve flexible memory regulation.
In summary, during my Ph.D. course, I developed advanced in vivo DA sensing tools and its application to identify the altered signature of striatal DA dynamics underlying LID in PD which reveals long-range tonic DA dynamics following drug administration. Also, I demonstrated the role of hippocampus dentate gyrus dopaminoceptive neurons, especially D2-expressing MCs in aversive contextual memory learning. These studies provide valuable insights into the mechanisms underlying potential therapeutic targets for treating PD and memory impairment.Chapter 1. Background 1
1. Dopamine and its receptors 1
2. Dopaminergic pathways 2
Chapter 2. Development of advanced neurotools to monitor dopamine dynamics 4
2.1. Introduction 4
2.2. Advanced neuroscience tools – Sub-Part 1 6
2.2.1. Introduction 6
2.2.2. Materials and methods 7
2.2.2.1. Animals 7
2.2.2.2. Unilateral Parkinson's model generation and its validation 8
2.2.2.3. In vivo DA sensing in PD mice model 9
2.2.2.4. In vivo biocompatibility test 9
2.2.3. Results 10
2.2.3.1. In vivo biocompatibility test of the newly developed DA probe 10
2.2.3.2. Real-time measurement of DA dynamics in the PD mice model 10
2.2.4. Discussion 11
2.3. Advanced neuroscience tools – Sub-Part 2 17
2.3.1. Introduction 17
2.3.2. Materials and methods 18
2.3.2.1. Data Acquisition and Analysis 18
2.3.2.2. Surgery and in vivo DA measurements 18
2.3.2.3. Second-Derivative-Based Background Drift Removal (SDBR) Method 19
2.3.3. Results 20
2.3.4. Discussion 22
2.4. Application of the advanced tools to pharmacodynamic analysis of levodopa-induced dyskinesia in Parkinson’s disease – Sub-Part 3 25
2.4.1. Introduction 25
2.4.2. Materials and methods 26
2.4.2.1. Animals 26
2.4.2.2. Stereotaxic surgeries 26
2.4.2.3. FSCV measurement of tonic DA changes 27
2.4.2.4. Slope calculation of tonic DA level changes 28
2.4.2.5. Chronic levodopa administration 29
2.4.2.6. Rotation test 30
2.4.2.7. Histology 30
2.4.2.8. Statistics 31
2.4.3. Results 31
2.4.3.1. Advanced FSCV technique to trace pharmacodynamics of levodopa in the PD model 31
2.4.3.2. Dyskinesia induction following chronic administration of levodopa in the PD model 33
2.4.3.3. Progressive onset of dyskinetic behavior in a LID model 35
2.4.3.4. Rapid induction of excessive hyperdopaminergic condition with LID progression 36
2.4.3.5. Correlation between dyskinetic behavior and the tonic DA dynamics along LID progression 36
2.4.4. Discussion 38
Chapter 3. Dopaminoceptive control of cognitive processing in the hippocampus 57
3.1. D2 regulation of hippocampal MCs for cognitive flexibility in fear-associated place memory 57
3.1.1. Introduction 57
3.1.2. Materials and methods 60
3.1.2.1. Animals 60
3.1.2.2. Stereotaxic surgery 61
3.1.2.3. Drug Administration 61
3.1.2.4. Active place avoidance (APA) 62
3.1.2.5. Histological analysis 63
3.1.2.6. Fluorescence imaging 63
3.1.2.7. In situ hybridization 63
3.1.2.8. In vivo calcium imaging with APA 64
3.1.2.9. Statistics 64
3.1.3. Results 65
3.1.3.1. Enhancement of cognitive flexibility by hM4Di-dependent control of Drd2-expressing neurons 65
3.1.3.2. Diminished cognitive flexibility and induction of local circuit changes by Drd2 gene silencing 67
3.1.3.3. Drastic enhancement of cognitive flexibility by MC-specific inhibition 69
3.1.3.4. Real-time calcium response monitoring of MCs during aversive learning. 70
3.1.4. Discussion 71
Chapter 4. Conclusion 87
References 90
Summary in Korean 97DoctordCollectio
Al-V-O-H-based electrode composition of calcium ion battery and calcium ion battery comprising the same
No full text본 발명은 칼슘 이온 전지용 전극 조성물이며, AlxV2O5ㆍy(H2O)를 포함하고, 상기 x는 0.1 003c# x 003c# 2이고, 상기 y는 0 003c# y 003c# 9인 것을 특징으로 하는 칼슘 이온 전지용 전극 조성물을 제공한다. 본 발명에 따른 칼슘 이온 전지용 전극 조성물은 기존에 이용된 1가의 양이온인 리튬 이온 대신 2가의 양이온인 칼슘 이온을 가역적으로 탈ㆍ삽입함으로써 전지의 성능이 우수한 효과가 있다