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Modelling of a tubular solid oxide fuel cell with different designs of indirect internal reformer

Journal of Energy Chemistry 2014年第2期23卷 251-263页

作者： p.kim-lohsoontorn F.priyakorn U.Wetwatana N.Laosiripojana Department of Chemical Engineering Mahidol University The Joint Graduate School of Energy and Environment King Mongkut’s University of Technology Thonburi Chemical process Engineering The Sirindhorn Internation Thai German Graduate School of EngineeringKing Mongkut’s University of Technology North Bangkok

The cell performance and temperature gradient of a tubular solid oxide fuel cell with indirect internal reformer （IIR-SOFC） fuelled by natural gas, containing a typical catalytic packed-bed reformer, a catalytic coated wall reformer, a catalytic annular reformer, and a novel catalytic annular-coated wall reformer were investigated with an aim to determine the most efficient internal reformer system. Among the four reformer designs, IIR-SOFC containing an annular-coated wall reformer exhibited the highest performance in terms of cell power density （0.67 *** 2） and electrical efficiency （68%） with an acceptable temperature gradient and a moderate pressure drop across the reformer （3.53 × 10 5 kpa）. IIR-SOFC with an annular-coated wall reformer was then studied over a range of operating conditions： inlet fuel temperature, operating pressure, steam to carbon （S ： C） ratio, gas flow pattern （co-flow and counter-flow pattern）, and natural gas compositions. The simulation results showed that the temperature gradient across the reformer could not be decreased using a lower fuel inlet temperature （1223 K-1173 K） and both the power density and electrical efficiency of the cell also decreased by lowering fuel inlet temperature. Operating in higher pressure mode （1-10 bar） improved the temperature gradient and cell performance. Increasing the S ： C ratio from 2 ： 1 to 4：1 could decrease the temperature drop across the reformer but also decrease the cell performance. The average temperature gradient was higher and smoother in IIR-SOFC under a co-flow pattern than that under a counter-flow pattern, leading to lower overpotential and higher cell performance. Natural gas compositions significantly affected the cell performance and temperature gradient. Natural gas containing lower methane content provided smoother temperature gradient in the system but showed lower power density and electrical efficiency.

关键词： indirect internal reforming solid oxide fuel cell annular-coated wall reformer packed-bed reformer catalytic coated wall reformer catalyticannular reformer

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Hyperreflective photonic crystals created by shearing colloidal dispersions at ultrahigh volume fraction

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Microsystems & Nanoengineering 2024年第1期10卷 161-173页

作者： Minji kim Jong Bin kim Shin-Hyun kim Department of Chemical and Biomolecular Engineering Korea Advanced Institute of Science and Technology(KAIST)Daejeon 34141Republic of Korea

Colloidal crystallization serves as one of the most economic and scalable production methods for photonic ***,insufficient optical performance,nonuniformity and low reproducibility remain challenges for advanced high-value *** this study,we optimally formulate a photocurable dispersion of silica particles and apply shear flow to unify the orientation of the colloidal crystals,ensuring high optical performance and *** silica particles experience strong repulsion at ultrahigh volume fractions of 50%but demonstrate low mobility,leading to polycrystalline *** shear flow to the dispersions allows the silica particles to rearrange into larger crystalline domains with a unidirectional orientation along the *** shear-induced structural change produces absolute reflectivity at the stopband as high as 90%and a high transparency of 90%at off-resonant wavelengths with minimal diffusive ***,the strong interparticle repulsion ensures a uniform volume fraction of particles throughout the dispersion,reducing deviations in the optical *** intricately micropattern the photocurable dispersions using ***,the photonic films and patterns can be stacked to form multiple layers,displaying mixed structural colors and multiple reflectance peaks without sacrificing *** superior photonic materials hold promise for various optical applications,including optical components and anticounterfeiting patches.

关键词： properties. dispersion reflectivity

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Boosted Lithium-Ion Transport Kinetics in n-Type Siloxene Anodes Enabled by Selective Nucleophilic Substitution of phosphorus

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Nano-Micro Letters 2024年第10期16卷 618-637页

作者： Se In kim Woong-Ju kim Jin Gu Kang Dong-Wan kim School of Civil Environmental and Architectural EngineeringKorea University02841 SeoulSouth Korea Nanophotonics Research Center Korea Institute of Science and Technology02792 SeoulSouth Korea

Doped two-dimensional(2D)materials hold significant promise for advancing many technologies,such as microelectronics,optoelectronics,and energy ***,n-type 2D oxidized Si nanosheets,namely n-type siloxene(n-SX),are employed as Li-ion battery *** thermal evaporation of sodium hypophosphite at 275℃,p atoms are effectively incorporated into siloxene(SX)without compromising its 2D layered morphology and unique Kautsky-type crystal ***,selective nucleophilic substitution occurs,with only Si atoms being replaced by p atoms in the O_(3)≡Si-H *** resulting n-SX possesses two delocalized electrons arising from the presence of two electron donor types:(i)p atoms residing in Si sites and(ii)H *** doping concentrations are varied by controlling the amount of precursors or their mean free *** at 2000 mA g^(-1),the n-SX electrode with the optimized doping concentration(6.7×10^(19) atoms cm^(-3))delivers a capacity of 594 mAh g^(-1) with a 73%capacity retention after 500 *** improvements originate from the enhanced kinetics of charge transport processes,including electronic conduction,charge transfer,and solid-state *** approach proposed herein offers an unprecedented route for engineering SX anodes to boost Li-ion storage.

关键词： Li-ion battery Two-dimensional N-type siloxene Doping mechanism Kinetics

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Investigation of operation and degradation mechanisms in ZnTeSe blue quantum-dot light-emitting diodes by identifying recombination zone

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Nano Research 2024年第7期17卷 6527-6533页

作者： Oul Cho Sujin park Hogeun Chang Jiwhan kim Jaekwon kim Sungwoo kim Taehyung kim Jeonghun Kwak Department of Electrical and Computer Engineering Inter-university Semiconductor Research Centerand Soft Foundry InstituteSeoul National UniversitySeoul 08826Republic of Korea Material Research Center Samsung Advanced Institute of TechnologySuwonGyeonggi-do 16419Republic of Korea

ZnTeSe quantum dots(QDs),recognized as promising eco-friendly blue electroluminescent emitters,remain under-explored in light-emitting diode(LED)***,to elucidate the operation and degradation mechanisms of ZnTeSe blue QD-LEDs,stacked ZnTeSe QD layers with discernable luminescence are designed by varying Te doping concentrations,and the recombination zones(RZs)of the blue QD-LEDs are *** RZs are identified near the hole-transport layer(HTL),confirmed by angular-dependent electroluminescence measurements and optical *** addition,in order to investigate carrier dynamics in the process of recombination,the transient electroluminescence(tr-EL)signals of the dichromatic QD-LEDs are *** a result,it is inferred that the RZ initially formed near the electron-transport layer(ETL)due to the high injection barriers of ***,due to the fast electron mobility,the RZ shifts toward the HTL as the operating current *** the device lifetime tests,the RZ remains stationary while the photoluminescence(pL)corresponding to the RZ undergoes a substantial decrease,indicating that the degradation is accelerated by the concentrated *** this study contributes to a deeper understanding of the operational mechanisms of ZnTeSe blue QD-LEDs.

关键词： quantum dots light-emitting diodes degradation recombination zones carrier dynamics

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Dragonfly Interaction Algorithm for Optimization of Queuing Delay in Industrial Wireless Networks

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Journal of Bionic Engineering 2024年第1期21卷 447-485页

作者： Sanjay Bhardwaj Da-Hye kim Dong-Seong kim Department of IT Convergence Engineering ICT Convergence Research CenterKumoh National Institute of TechnologyGumiSouth Korea

In industrial wireless networks,data transmitted from source to destination are highly *** often leads to the queuing of the data,and poor management of the queued data results in excessive delays,increased energy consumption,and packet ***,a nature-inspired-based Dragonfly Interaction Optimization Algorithm(DMOA)is proposed for optimization of the queue delay in industrial wireless *** term“interaction”herein used is the characterization of the“flying movement”of the dragonfly towards damselflies(female dragonflies)for *** a result,interaction is represented as the flow of transmitted data packets,or traffic,from the source to the base *** includes each and every feature of dragonfly movement as well as awareness of the rival dragonflies,predators,and damselflies for the desired optimization of the queue *** features are juxtaposed as noise and interference,which are further used in the calculation of industrial wireless metrics:latency,error rate(reliability),throughput,energy efficiency,and fairness for the optimization of the queue *** analysis,convergence analysis,the Wilcoxon test,the Friedman test,and the classical as well as the 2014 IEEE Congress of Evolutionary Computation(CEC)on the benchmark functions are also used for the evaluation of DMOA in terms of its robustness and *** results demonstrate the robustness of the proposed algorithm for both classical and benchmarking functions of the IEEE CEC ***,the accuracy and efficacy of DMOA were demonstrated by means of the convergence rate,Wilcoxon testing,and ***,fairness using Jain’s index in queue delay optimization in terms of throughput and latency,along with computational complexity,is also evaluated and compared with other *** results show that DMOA exceeds other bio-inspired optimization algorithms in terms of fairness in queue delay management and average packet *** proposed a

关键词： Dragonfly Damselfly Interaction Queuing delay Optimization Industrial wireless networks

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Anomaly Detection in Imbalanced Encrypted Traffic with Few packet Metadata-Based Feature Extraction

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CMES-COMpUTER MODELING IN ENGINEERING & SCIENCES 2024年第10期141卷 585-607页

作者： kim, Min-Gyu kim, Hwankuk Kookmin Univ Dept Financial Informat Secur Seoul 02707 South Korea Kookmin Univ Dept Informat Secur Cryptog Math Seoul 02707 South Korea

In the IoT (Internet of Things) domain, the increased use of encryption protocols such as SSL/TLS, VpN (Virtual private Network), and Tor has led to a rise in attacks leveraging encrypted traffic. While research on anomaly detection using AI (Artificial Intelligence) is actively progressing, the encrypted nature of the data poses challenges for labeling, resulting in data imbalance and biased feature extraction toward specific nodes. This study proposes a reconstruction error-based anomaly detection method using an autoencoder (AE) that utilizes packet metadata excluding specific node information. The proposed method omits biased packet metadata such as Ip and port and trains the detection model using only normal data, leveraging a small amount of packet metadata. This makes it well-suited for direct application in IoT environments due to its low resource consumption. In experiments comparing feature extraction methods for AE-based anomaly detection, we found that using flowbased features significantly improves accuracy, precision, F1 score, and AUC (Area Under the Receiver Operating Characteristic Curve) score compared to packet-based features. Additionally, for flow-based features, the proposed method showed a 30.17% increase in F1 score and improved false positive rates compared to Isolation Forest and OneClassSVM. Furthermore, the proposed method demonstrated a 32.43% higher AUC when using packet features and a 111.39% higher AUC when using flow features, compared to previously proposed oversampling methods. This study highlights the impact of feature extraction methods on attack detection in imbalanced, encrypted traffic environments and emphasizes that the one-class method using AE is more effective for attack detection and reducing false positives compared to traditional oversampling methods.

关键词： One-class anomaly detection feature extraction auto-encoder encrypted traffic CICIoT2023

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Ag-GST/HfO_(x)-based unidirectional threshold switching selector with low leakage current and threshold voltage distribution for high-density cross-point arrays

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Rare Metals 2024年第1期43卷 280-288页

作者： Kyoung-Joung Yoo Dae-Yun Kang Nahyun kim Ho-Jin Lee Ta-Hyeong kim Taeho kim Tae Geun kim School of Electrical Engineering Korea UniversitySeoul 02841Republic of Korea

The use of electrochemical-metallization-based volatile threshold switching selectors in cross-point arrays has been widely explored owing to their high on-off ratios and simple ***,these devices are unsuitable for cross-point architectures because of the difficulty in controlling the random filament formation that results in large fluctuations in the threshold voltage during *** this study,we investigated the unidirectional threshold transition characteristics associated with an Ag/GST/HfO_(x)/pt-based bilayer selector and demonstrated the occurrence of a low leakage current(programming currents of the device could be significantly *** the crossbar array configuration,we performed equivalent circuit analysis of a one-selector oneresistor(1S1R) devices and estimated the optimal array size to demonstrate the applicability of the proposed *** maximum acceptable crossbar array size of the 1S1R device with the Ag/GST/HfO_(x)/pt/Ti/NiO_(x)/pt structure was 5.29×10^(14)(N^(2),N=2.3×10^(7)).

关键词： Selector device Tunneling barrier Threshold switching Sputtering 1S1R Cross-point array

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Trend of Developing Aqueous Liquid and Gel Electrolytes for Sustainable,Safe,and High‑performance Li‑Ion Batteries

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Nano-Micro Letters 2024年第1期16卷 17-34页

作者： Donghwan Ji Jaeyun kim School of Chemical Engineering Sungkyunkwan University(SKKU)Suwon 16419Republic of Korea Department of Health Sciences and Technology Samsung Advanced Institute for Health Sciences&Technology(SAIHST)Sungkyunkwan University(SKKU)Suwon 16419Republic of Korea Biomedical Institute for Convergence at SKKU(BICS) Sungkyunkwan University(SKKU)Suwon 16419Republic of Korea Institute of Quantum Biophysics(IQB) Sungkyunkwan University(SKKU)Suwon 16419Republic of Korea present Address:Department of NanoEngineering University of California San DiegoLa JollaSan DiegoCA 92093USA

Current lithium-ion batteries(LIBs)rely on organic liquid electrolytes that pose significant risks due to their flammability and *** potential for environmental pollution and explosions resulting from battery damage or fracture is a critical ***-based(aqueous)electrolytes have been receiving attention as an alternative to organic ***,a narrow electrochemicalstability window,water decomposition,and the consequent low battery operating voltage and energy density hinder the practical use of aqueous ***,developing novel aqueous electrolytes for sustainable,safe,high-performance LIBs remains *** Review first commences by summarizing the roles and requirements of electrolytes–separators and then delineates the progression of aqueous electrolytes for LIBs,encompassing aqueous liquid and gel electrolyte development trends along with detailed principles of the *** aqueous electrolytes are progressed based on strategies using superconcentrated salts,concentrated diluents,polymer additives,polymer networks,and artificial passivation layers,which are used for suppressing water decomposition and widening the electrochemical stability window of water of the *** addition,this Review discusses potential strategies for the implementation of aqueous Li-metal batteries with improved electrolyte–electrode interfaces.A comprehensive understanding of each strategy in the aqueous system will assist in the design of an aqueous electrolyte and the development of sustainable and safe high-performance batteries.

关键词： Lithium-ion battery(LIB) Aqueous electrolyte Gel electrolyte Electrochemical stability window Li dendrite

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Systematic Security Guideline Framework through Intelligently Automated Vulnerability Analysis

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Computers, Materials & Continua 2024年第3期78卷 3867-3889页

作者： Dahyeon kim Namgi kim Junho Ahn Computer Information Technology Korea National University of TransportationChungju27469Korea Department of AI Computer Science and Engineering Kyonggi UniversitySuwon16227Korea

This research aims to propose a practical framework designed for the automatic analysis of a product’s comprehensive functionality and security vulnerabilities,generating applicable guidelines based on real-world *** existing analysis of software security vulnerabilities often focuses on specific features or *** partial and arbitrary analysis of the security vulnerabilities makes it challenging to comprehend the overall security vulnerabilities of the *** key novelty lies in overcoming the constraints of partial *** proposed framework utilizes data from various sources to create a comprehensive functionality profile,facilitating the derivation of real-world security *** guidelines are dynamically generated by associating functional security vulnerabilities with the latest Common Vulnerabilities and Exposure(CVE)and Common Vulnerability Scoring System(CVSS)scores,resulting in automated guidelines tailored to each *** guidelines are not only practical but also applicable in real-world software,allowing for prioritized security *** proposed framework is applied to virtual private network(VpN)software,wherein a validated Level 2 data flow diagram is generated using the Spoofing,Tampering,Repudiation,Information Disclosure,Denial of Service,and Elevation of privilege(STRIDE)technique with references to various papers and examples from related *** analysis resulted in the identification of a total of 121 *** successful implementation and validation demonstrate the framework’s efficacy in generating customized guidelines for entire systems,subsystems,and selected modules.

关键词： Framework automation vulnerability analysis security guidelines

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Malware Detection Using Dual Siamese Network Model

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CMES-COMpUTER MODELING IN ENGINEERING & SCIENCES 2024年第1期141卷 563-584页

作者： An, Byeongyeol Yang, Jeahyuk kim, Seoyeon kim, Taeguen Soonchunhyang Univ Dept Software Convergence Asan 31538 South Korea Soonchunhyang Univ Dept Mobil Convergence Secur Asan 31538 South Korea Soonchunhyang Univ Dept Informat Secur Engn Asan 31538 South Korea

This paper proposes a new approach to counter cyberattacks using the increasingly diverse malware in cyber security. Traditional signature detection methods that utilize static and dynamic features face limitations due to the continuous evolution and diversity of new malware. Recently, machine learning-based malware detection techniques, such as Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), have gained attention. While these methods demonstrate high performance by leveraging static and dynamic features, they are limited in detecting new malware or variants because they learn based on the characteristics of existing malware. To overcome these limitations, malware detection techniques employing One-Shot Learning and FewShot Learning have been introduced. Based on this, the Siamese Network, which can effectively learn from a small number of samples and perform predictions based on similarity rather than learning the characteristics of the input data, enables the detection of new malware or variants. We propose a dual Siamese network-based detection framework that utilizes byte images converted from malware binary data to grayscale, and opcode frequency-based images generated after extracting opcodes and converting them into 2-gram frequencies. The proposed framework integrates two independent Siamese network models, one learning from byte images and the other from opcode frequency-based images. The detection models trained on the different kinds of images generated separately apply the L1 distance measure to the output vectors the models generate, calculate the similarity, and then apply different weights to each model. Our proposed framework achieved a malware detection accuracy of 95.9% and 99.83% in the experiments using different malware datasets. The experimental results demonstrate that our malware detection model can effectively detect malware by utilizing two different types of features and employing the dual Siamese network-based mod

关键词： Siamese network malware detection few-shot learning

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