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차세대 리튬이온 이차전지를 위한 망간 헥사사이아노페레이트 양극과 주석 보호 마그네슘 음극의 개발 및 전기화학적 성능 연구
No full textPrussian Blue analogues, Sn-protected Mg, Post-lithium-ion batteries, Cathode, AnodeⅠ. Introduction 1
1.1. The necessities of post-lithium-ion batteries 1
1.2. Sodium-ion batteries 2
1.3. Rechargeable magnesium batteries 3
1.4. Prussian blue analogues 4
Ⅱ. Experimental 6
2.1. Manganese hexacyanoferrate cathode 6
2.1.1. Synthesis of manganese hexacyanoferrate 6
2.1.2. Material characterization 6
2.1.3. Electrochemical characterization 7
2.2. Sn-protected Mg anode 8
2.2.1. Materials 8
2.2.2. Preparation of Sn-protected Mg metal 8
2.2.3. Preparation of Mo6S8 cathode 9
2.2.4. Physicochemical characterization 10
2.2.5. Electrochemical characterization 10
Ⅲ. Results and discussions 12
3.1. Results of manganese hexacyanoferrate cathode 12
3.1.1. Removal of H2O in MnHCF 12
3.1.2. Electrochemical characterization 14
3.1.3. Structural evolution 16
3.2. Results of Sn-protected Mg anode 18
3.2.1. Electrochemical properties of bare Mg metal 18
3.2.2. Surface characteristics & electrochemical performance of Sn-protected Mg 20
3.2.3. Mechanism of Mg plating on Sn-protected Mg 24
Ⅳ. Conclusion 28
Ⅴ. Supporting information 30
Ⅵ. References 34
요약문 39MasterdCollectio
An Integration of Cryptography and Physical Layer Security for Multibeam Satellite Systems
No full textDue to the broadcasting nature, satellite signals are vulnerable to potential eavesdropping attacks, which pose a significant security risk for users. Physical layer security (PLS) and cryptography technologies have been independently developed to address this security risk. However, the independent use of each technology in the power-limited satellite systems results in a trade-off problem between onboard power consumption and security performance due to additional encryption costs and dependence of PLS on the performance of eavesdroppers (Eves). In this paper, we integrate the PLS and cryptography considering the complementary properties of the adaptability to wireless channel characteristics and inherent message confidentiality for secure multibeam satellite networks. To this end, we estimate the eavesdropping risk as a function of the given number of Eves for independent and collaborative attacks. Moreover, we design an onboard power model utilized for transmission and computation, and Gaussian beamforming based on the eavesdropping risk. Then, we derive solutions for onboard power allocation, beam scheduling, and security algorithm selection in the non-orthogonal multiple access (NOMA) systems. Finally, we demonstrate that the secure transmission performance improves even under the increment of the eavesdropping risk, and the trade-off performance between cryptography and PLS is provided through analytical and simulation results. IEEEFALSEsciescopu
Enhanced cesium adsorption and desorption mechanisms in ZnFe Prussian blue analogs: Structural transformation and reusability
No full textThe management of radioactive cesium (137Cs) is critical due to its long half-life, environmental persistence, and harmful effects on human health and ecosystems. Although Prussian blue analogs (PBAs) have gained attention for their potential in adsorption-based Cs+ removal, the structural changes that occur during adsorption and desorption cycling are poorly understood. This study investigates the synthesis of ZnFe-PBAs using various methodologies, including photochemical reduction and the use of different precursors and reducing agents, to achieve diverse oxidation states in their lattice structures. The photochemically synthesized ZnFe-PBAs exhibited significantly enhanced Cs+ adsorption capacities compared to those of conventional materials. Comprehensive characterization techniques, including X-ray diffraction, Fourier transform infrared spectroscopy, and X-ray photoelectron spectroscopy, were employed to assess the physicochemical properties of the ZnFe-PBAs and examine their structural changes during Cs+ adsorption and desorption. The results revealed that the ZnFe samples exhibited distinct structural transformations, with ZnFe-W showing rapid structural changes that facilitated rapid Cs+ adsorption and desorption. In contrast, ZnFe-Y maintained a stable cubic structure throughout the process. Adsorption isotherm and kinetic studies confirmed that ion exchange with K+ is the primary mechanism of Cs+ adsorption, and it was deduced that the desorption efficiency varied with the choice of desorption solution. This study highlights the importance of understanding structural changes during Cs+ removal and provides insights into designing more efficient and reusable adsorbents. These findings suggest that ZnFe-PBAs have strong potential for 137Cs removal in simulated nuclear waste environments and a promising strategy for radioactive contaminant management. © 2024 Elsevier B.V.FALSEsci
Information Age-Based Task Splitting Scheme for Edge Computing-Enabled Networks
No full textThis letter focuses on data freshness-based task splitting in edge computing (EC)-enabled networks, where a user's subtasks are offloaded to EC servers through radio access networks (RANs). A control tower (CT) receives information of available computing resources from EC servers and channel information. Considering the freshness of received information at CT, we define a successful offloading probability (SOP), then formulate the SOP maximization problem by optimizing the task splitting. We propose an alternative algorithm by decomposition with approximation and bisection methods. Numerical results demonstrate the proposed algorithm outperforms a baseline, emphasizing the importance of data freshness on the optimization. © IEEE.FALSEsciescopu
Resolution Improvement Algorithm with Two Targets Using Envelope of the Beat Signals for FMCW Radars
No full textThis paper proposes a resolution improvement algorithm with two targets using the envelope of the beat signals for frequency modulated continuous wave (FMCW) radar. The range resolution of FMCW radars is determined by the bandwidth, as the size of the bandwidth is proportional to the observation window (OW). If the OW is sufficiently large, multiple frequencies with small differences between sinusoids can be well estimated. However, if the OW is insufficient, multiple sinusoids with similar frequencies may be incorrectly assumed to be a single frequency. The proposed algorithm leverages the property that the envelope of the beat signal contains information about the difference between two frequencies to estimate the frequencies missed due to the insufficient size of the OW. Specifically, it uses the fast Fourier transform (FFT) results that were incorrectly estimated as a single target, along with the FFT results of the envelope of the beat signal. Performance evaluations demonstrate that the proposed algorithm achieves improved resolution without a significant increase in overall complexity. © IEEE.FALSEsciescopu
FR-MIL: Distribution Re-Calibration-Based Multiple Instance Learning With Transformer for Whole Slide Image Classification
No full textIn digital pathology, whole slide images (WSI) are crucial for cancer prognostication and treatment planning. WSI classification is generally addressed using multiple instance learning (MIL), alleviating the challenge of processing billions of pixels and curating rich annotations. Though recent MIL approaches leverage variants of the attention mechanism to learn better representations, they scarcely study the properties of the data distribution itself i.e., different staining and acquisition protocols resulting in intra-patch and inter-slide variations. In this work, we first introduce a distribution re-calibration strategy to shift the feature distribution of a WSI bag (instances) using the statistics of the max-instance (critical) feature. Second, we enforce class (bag) separation via a metric loss assuming that positive bags exhibit larger magnitudes than negatives. We also introduce a generative process leveraging Vector Quantization (VQ) for improved instance discrimination i.e., VQ helps model bag latent factors for improved classification. To model spatial and context information, a position encoding module (PEM) is employed with transformer-based pooling by multi-head self-attention (PMSA). Evaluation of popular WSI benchmark datasets reveals our approach improves over state-of-the-art MIL methods. Further, we validate the general applicability of our method on classic MIL benchmark tasks and for point cloud classification with limited points. https://github.com/PhilipChicco/FRMILFALSEsci
Advancements in framework materials for enhanced energy harvesting
No full textEnergy harvesting, the process of capturing ambient energy from various sources and converting it into usable electrical power, has attracted a lot of attention due to its potential to provide long-term and self-sufficient energy solutions. This comprehensive review thoroughly explores the use of metal-organic frameworks (MOFs) and covalent organic frameworks (COFs) for energy harvesting by piezoelectric and triboelectric nanogenerators (PENGs and TENGs). It begins by classifying and outlining the structural diversity of MOFs and COFs, which is key to understanding their importance in energy applications. Key characterization techniques are focused on emphasizing their importance in optimizing material properties for efficient energy conversion. The working mechanisms of PENGs and TENGs are discussed, focusing on their ability to transform mechanical energy into electrical energy and their advantages in operation. The use of MOFs and COFs in energy harvesting applications is then discussed, including synthesis procedures, unique characteristics relevant to electricity conversion, and various practical applications such as self-powered sensors and wearable electronics. Current challenges such as stability, scalability, and performance improvements are explored, as well as proposed future improvements to help advance current research. Finally, the study highlights the importance of framework materials for the development of energy harvesting systems, providing an invaluable resource for academics and engineers seeking to exploit the potential of these materials for renewable energy sources. The goal of this article is to stimulate further invention and implementation of efficient materials-based energy harvesting framework devices by integrating recent advances and mapping future possibilities. © 2025 The Royal Society of Chemistry.FALSEsciescopu
Vialess heterogeneous skin patch for multimodal monitoring and stimulation
Get PDFSystem-level wearable electronics require to be flexible to ensure conformal contact with the skin, but they also need to integrate rigid and bulky functional components to achieve system-level functionality. As one of integration methods, folding integration offers simplified processing and enhanced functionality through rigid-soft region separation, but so far, it has mainly been applied to modality of electrical sensing and stimulation. This paper introduces a vialess heterogeneous skin patch with multi modalities that separates the soft region and strain-robust region through folded structure. Our system includes electrical and optical modalities for hemodynamic and cardiovascular monitoring, and a force-electrically driven micropump for drug delivery. Each modality is demonstrated through on-demand drug delivery, flexible waveguide-based PPG monitoring, and ECG and body movement monitoring. Wireless data transmission and real-time measurement validate the feedback operation for multi-modalities. This engineered closed-loop platform offers the possibility for broad applications, including cardiovascular monitoring and chronic disease management. © 2025. The Author(s).TRUEsciescopu
An Edge Accelerator With 5 MB of 0.256-pJ/bit Embedded RRAM and a Localization Solver for Bristle Robot Surveillance
No full textAccelerators for miniaturized robots addressing tasks such as autonomous surveillance need to balance their compute capabilities against the requirements for low energy use and a compact form factor imposed by the small size of the platforms. Many applications require machine learning (ML) inference for perception tasks as well as estimation of the robot's own trajectory for localization. The paradigm of using large on-die memories to store deep neural network (DNN) weights on-chip has the potential to yield improved efficiency by reducing off-chip memory accesses. By implementing these large weight stores on-die using an embedded nonvolatile memory (eNVM) technology, density can be improved while leakage can be reduced using power-down modes. Furthermore, the localization workflow requires the evaluation of state equations with concurrent addition operations. This presents a potential bottleneck, motivating a dedicated localization block. We introduce an accelerator combining a resistive random access memory (RRAM)-based inference subsection and a localization accelerator block using an SRAM- like cross-coupled structure. The inference subsection combines INT8 matrix datapaths with 5 MB of RRAM (2.07 Mb/mm(2) considering the 20.25-mm(2 )die) at 0.256 pJ/bit and 12.8 GB/s, and supports an SRAM-retentive power-down mode consuming 110 mu W. At full utilization, at V MIN , throughput is 102.4 GOPS and efficiency is 0.84 TOPS/W. The localization block allows voltage-pulse-driven data updates to support concurrent in-place addition to address the related bottleneck. © IEEE.FALSEsciescopu
