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Exploring ultrathin tungsten disulfide as a diffusion barrier for copper interconnects: advanced packaging reliability and a first-principles study

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Materials Today Nano 2025年 30卷

作者： Chavan, Vijay D. Lehenkari, Touko Yadav, Suhas Ustad, Ruhan E. Sheikh, Zulfqar Ali Avatare, Ajay T. Kamble, Tushar P. Sajjad, Laraib Komsa, Hannu-Pekka Sabale, Sandip Choi, Kyeong-Keun Park, Seungbae Dastgeer, Ghulam Kim, Honggyun Kim, Deok-kee Department of Electrical Engineering and Convergence Engineering for Intelligent Drone Sejong University Seoul05006 Korea Republic of Microelectronics Research Unit Faculty of Information Technology and Electrical Engineering University of Oulu Finland Department of Semiconductor Systems Engineering Sejong University Seoul05006 Korea Republic of Maharashtra Jaysingpur416101 India National Institute for Nanomaterials Technology Pohang University of Science and Technology Gyeongbuk 37673 Korea Republic of Department of Mechanical Engineering State University of New York at Binghamton VestalNY13850 United States Department of Physics and Astronomy Sejong University Seoul05006 Korea Republic of

The robust diffusion barriers (DB) are crucial due to the significant prevention of copper (Cu) diffusion/migration, which negatively affects interconnect reliability and compatibility in advanced packaging. With a half-pitch size (20 nm and below) a conventional Ta/TaN DB has a thickness limit to shrinkage below 4 nm, addressing the limited Cu conductivity, and inferior barrier properties to block Cu diffusion. Therefore, ultrathin 0.7 nm tungsten disulfide (WS2) is utilized as a pioneering DB for Cu interconnects to address this issue. Herein, W is primarily sputtered and sulfurized at 400 °C to convert into WS2, later confirmed by several characterizations. Based on JE, CV, temperature-dependent breakdown, and DFT verification, we conclude that the ultrathin 0.7 nm WS2 effectively blocks the Cu diffusion in the range of 9.7–10 MV/cm. Notably, the research is strongly supported by reliability tests, including (−200 to 400 °C) temperature-dependent JE at both low (14.8 MV/cm) and high (8 MV/cm) temperatures, Cu electroplating, warpage tests, tape tests, and other relevant evaluations, which are currently of significant interest in packaging. The obtained results show that the WS2 DB serving both liner/barrier properties is excellent as compared to conventional Ta(liner)/TaN(barrier). The study demonstrates that WS2 is BEOL-compatible and industry-friendly, facilitating interconnect scaling beyond the current technology node, and we should not be surprised if used in future advanced packaging. © 2025

关键词： Labels

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Multi-sensor data fusion across dimensions: A novel approach to synopsis generation using sensory data

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Journal of Industrial Information Integration 2025年 46卷

作者： Palash Yuvraj Ingle Young-Gab Kim Department of Computer and Information Security and Convergence Engineering for Intelligent Drone Sejong University Seoul 05006 Republic of Korea

Unmanned aerial vehicles (UAVs) and autonomous ground vehicles are increasingly outfitted with advanced sensors such as LiDAR, cameras, and GPS, enabling real-time object detection, tracking, localization, and navigation. These platforms generate high-volume sensory data, such as video streams and point clouds, that require efficient processing to support timely and informed decision-making. Although video synopsis techniques are widely used for visual data summarization, they encounter significant challenges in multi-sensor environments due to disparities in sensor modalities. To address these limitations, we propose a novel sensory data synopsis framework designed for both UAV and autonomous vehicle applications. The proposed system integrates a dual-task learning model with a real-time sensor fusion module to jointly perform abnormal object segmentation and depth estimation by combining LiDAR and camera data. The framework comprises a sensory fusion algorithm, a 3D-to-2D projection mechanism, and a Metropolis-Hastings-based trajectory optimization strategy to refine object tubes and construct concise, temporally-shifted synopses. This design selectively preserves and repositions salient information across space and time, enhancing synopsis clarity while reducing computational overhead. Experimental evaluations conducted on standard datasets (i.e., KITTI, Cityscapes, and DVS) demonstrate that our framework achieves a favorable balance between segmentation accuracy and inference speed. In comparison with existing studies, it yields superior performance in terms of frame reduction, recall, and F1 score. The results highlight the robustness, real-time capability, and broad applicability of the proposed approach to intelligent surveillance, smart infrastructure, and autonomous mobility systems.

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Ransomware Classification Framework Using the Behavioral Performance Visualization of Execution Objects

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computers, Materials & Continua 2022年第8期72卷 3401-3424页

作者： Jun-Seob Kim Ki-Woong Park Department of Computer and Information Security and Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea

A ransomware attack that interrupted the operation of Colonial Pipeline(a large *** pipeline company),showed that security threats by malware have become serious enough to affect industries and social infrastructure rather than individuals *** agents and characteristics of attacks should be identified,and appropriate strategies should be established accordingly in order to respond to such *** this purpose,the first task that must be performed is malware *** creators are well aware of this and apply various concealment and avoidance techniques,making it difficult to classify *** study focuses on new features and classification techniques to overcome these *** propose a behavioral performance visualization method using utilization patterns of system resources,such as the central processing unit,memory,and input/output,that are commonly used in performance analysis or tuning of *** extracted the usage patterns of the system resources for ransomware to performbehavioral performance *** results of the classification performance evaluation using the visualization results indicate an accuracy of at least 98.94%with a 3.69%loss ***,we designed and implemented a framework to perform the entire process—from data extraction to behavioral performance visualization and classification performance measurement—that is expected to contribute to related studies in the future.

关键词： Behavioral performance visualization ransomware malware classification

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AI-Driven Prioritization and Filtering of Windows Artifacts for Enhanced Digital Forensics

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computers, Materials & Continua 2024年第11期81卷 3371-3393页

作者： Juhwan Kim Baehoon Son Jihyeon Yu Joobeom Yun Department of Computer and Information Security and Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Republic of Korea

Digital forensics aims to uncover evidence of cybercrimes within compromised *** cybercrimes are often perpetrated through the deployment of malware,which inevitably leaves discernible traces within the compromised *** analysts are tasked with extracting and subsequently analyzing data,termed as artifacts,from these systems to gather ***,forensic analysts must sift through extensive datasets to isolate pertinent ***,manually identifying suspicious traces among numerous artifacts is time-consuming and *** studies addressed such inefficiencies by integrating artificial intelligence(AI)technologies into digital *** the efforts in previous studies,artifacts were analyzed without considering the nature of the data within them and failed to prove their efficiency through specific *** this study,we propose a system to prioritize suspicious artifacts from compromised systems infected with malware to facilitate efficient digital *** system introduces a double-checking method that recognizes the nature of data within target artifacts and employs algorithms ideal for anomaly *** key ideas of this method are:(1)prioritize suspicious artifacts and filter remaining artifacts using autoencoder and(2)further prioritize suspicious artifacts and filter remaining artifacts using logarithmic *** evaluation demonstrates that our system can identify malicious artifacts with high accuracy and that its double-checking method is more efficient than alternative *** system can significantly reduce the time required for forensic analysis and serve as a reference for future studies.

关键词： Digital forensics autoencoder logarithmic entropy prioritization anomaly detection windows artifacts artificial intelligence

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p-CuGaO2/β-Ga2O3 interfaces: A high-throughput approach for interface prediction and generation for power device applications

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Materials Today Advances 2025年 26卷

作者： Prasad, Chowdam Venkata Park, Jang Hyeok Hoai Ta, Qui Thanh Kim, Kyong Jae Jeon, Ho Jung Mir, Muzaffar Ali Raza, Mohsin Tri, Nguyen Ngoc Kim, Honggyun Labed, Madani Rim, You Seung Department of Semiconductor Systems Engineering and Convergence Engineering for Intelligent Drone Sejong University Seoul05006 Korea Republic of Institute of Semiconductor and System IC Sejong University Seoul05006 Korea Republic of Department of Semiconductor Systems Engineering Sejong University Seoul05006 Korea Republic of Institute of Advanced Technology Vietnam Academy of Science and Technology 1A TL29 Street Thanh Loc Ward District 12 Ho Chi Minh City700000 Viet Nam Lab of Computational Chemistry and Modelling Faculty of Natural Sciences Quy Nhon University Quy Nhon City55100 Viet Nam

This study integrates a p-type copper gallium oxide (p-CuGaO2) interlayer to enhance the performance of β-Ga2O3-based power devices, addressing challenges in achieving reliable p-type doping. The p-CuGaO2 interlayer is expected to improve breakdown voltage (BV) and reduce leakage current, increasing device efficiency and reliability under high-temperature conditions. The heterojunction (HJ) system of β-Ga2O3 and p-CuGaO2 is investigated using density functional theory (DFT) via the Vienna Ab initio Simulation Package (VASP) and experimental methods, focusing on the β-Ga2O3 (001)/p-CuGaO2 (006) interface. Binding energy, electron localization, charge density difference, and electrostatic potential drop are analyzed, identifying Configuration-1 as the optimal configuration due to its high binding energy and favorable structural properties. Annealing temperature impacts the microstructure, stoichiometry, optical, electrical, and transport properties of p-CuGaO2/β-Ga2O3 HJs. Electrical measurements reveal reduced turn-on voltage (Von), on-resistance (Ron), and leakage currents, with the highest BV of 1.62 kV achieved at 800 °C compared to Pt/β-Ga2O3 Schottky barrier diode (SBD). The interface state density (NSS) is evaluated using the high-low frequency approach. Silvaco TCAD simulations explore breakdown mechanisms, demonstrating the potential of p-CuGaO2 for β-Ga2O3 HJ power devices. These findings support the development and manufacture of robust β-Ga2O3 HJ power devices. © 2025 The Authors

关键词： Heterojunctions

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Efficient Deep Learning Framework for Fire Detection in Complex Surveillance Environment

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computer Systems science & engineering 2023年第7期46卷 749-764页

作者： Naqqash Dilshad Taimoor Khan JaeSeung Song Department of Convergence Engineering for Intelligent Drone Seoul05006Korea Department of Computer Science Islamia College PeshawarPeshawar25120Pakistan

To prevent economic,social,and ecological damage,fire detection and management at an early stage are significant yet *** computationally complex networks have been developed,attention has been largely focused on improving accuracy,rather than focusing on real-time fire ***,in this study,the authors present an efficient fire detection framework termed E-FireNet for real-time detection in a complex surveillance *** proposed model architecture is inspired by the VGG16 network,with significant modifications including the entire removal of Block-5 and tweaking of the convolutional layers of *** results in higher performance with a reduced number of parameters and inference ***,smaller convolutional kernels are utilized,which are particularly designed to obtain the optimal details from input images,with numerous channels to assist in feature *** E-FireNet,three steps are involved:preprocessing of collected data,detection of fires using the proposed technique,and,if there is a fire,alarms are generated and transmitted to law enforcement,healthcare,and management ***,E-FireNet achieves 0.98 accuracy,1 precision,0.99 recall,and 0.99 F1-score.A comprehensive investigation of various Convolutional Neural Network(CNN)models is conducted using the newly created Fire Surveillance SV-Fire *** empirical results and comparison of numerous parameters establish that the proposed model shows convincing performance in terms of accuracy,model size,and execution time.

关键词： Deep learning drone embedded vision emergency monitoring fire classification fire detection IoT search and rescue

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Deep Learning Based Underground Sewer Defect Classification Using a Modified RegNet

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computers, Materials & Continua 2023年第6期75卷 5451-5469页

作者： Yu Chen Sagar A.S.M.Sharifuzzaman Hangxiang Wang Yanfen Li L.Minh Dang Hyoung-Kyu Song Hyeonjoon Moon Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Department of Intelligent Mechatronics Engineering Sejong UniversitySeoul05006Korea Department of Information of Communication Engineering and Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea

The sewer system plays an important role in protecting rainfall and treating urban *** to the harsh internal environment and complex structure of the sewer,it is difficult to monitor the sewer *** are developing different methods,such as the Internet of Things and Artificial Intelligence,to monitor and detect the faults in the sewer *** learning is a promising artificial intelligence technology that can effectively identify and classify different sewer system ***,the existing deep learning based solution does not provide high accuracy prediction and the defect class considered for classification is very small,which can affect the robustness of the model in the constraint *** a result,this paper proposes a sewer condition monitoring framework based on deep learning,which can effectively detect and evaluate defects in sewer pipelines with high *** also introduce a large dataset of sewer defects with 20 different defect classes found in the sewer *** study modified the original RegNet model by modifying the squeeze excitation(SE)block and adding the dropout layer and Leaky Rectified Linear Units(LeakyReLU)activation function in the Block structure of RegNet *** study explored different deep learning methods such as RegNet,ResNet50,very deep convolutional networks(VGG),and GoogleNet to train on the sewer defect *** experimental results indicate that the proposed system framework based on the modified-RegNet(RegNet+)model achieves the highest accuracy of 99.5 compared with the commonly used deep learning *** proposed model provides a robust deep learning model that can effectively classify 20 different sewer defects and be utilized in real-world sewer condition monitoring applications.

关键词： Deep learning defect classification underground sewer computer vision convolutional neural network RegNet

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Improved Hybrid Precoding Technique with Low-Resolution for MIMO-OFDM System

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computers, Materials & Continua 2021年第8期68卷 2205-2220页

作者： Seulgi Lee Ji-Sung Jung Young-Hwan You Hyoung-Kyu Song Department of Information and Communication Engineering and Convergence for Intelligent DroneSejong UniversitySeoul05006Korea Department of Computer Engineering Sejong UniversitySeoul05006Korea

This paper proposes an improved hybrid beamforming system based on multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM)*** proposed beamforming system improves energy efficiency compared to the conventional hybrid beamforming *** sub-connected and full-connected structure are considered to apply the proposed *** the conventional hybrid beamforming,the usage of radio frequency(RF)chains and phase shifter(PS)gives high power and hardware *** this paper,the phase over sampling(POS)with switches(SW)is used in hybrid beamforming system to improve the energy *** POS-SW structure samples the value of analog beamformer to make lower resolution than conventional *** number of output data in POS is decided by the resolution of POS *** limited number of POS decides the resolution of antenna array and the values of POSs are designed from maximum and minimum phase angle antenna *** efficiency without the phase shifter is high although channel capacity is nearly similar with conventional ***,the amplifier with POS-SW system is proposed to improve the BER *** to the data bits,the output signals of POS are *** system with 2,3 and 4 bits is simulated to prove the proposed *** order to overcome the loss of low-resolution system,the amplifier with POS-SW system using channel information is *** average sum-rate of 4 bits system shows the similar performance with the conventional hybrid beamforming *** structure can play an important role by increasing the energy efficiency of the wireless communication system that many antennas are *** is shown that the BER,average sum rate and energy efficiency of the proposed scheme are more improved than the conventional hybrid beamforming system.

关键词： Hybrid beamforming MIMO-OFDM system analog precoding POS-SW

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Weighted Gauss-Seidel Precoder for Downlink Massive MIMO Systems

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computers, Materials & Continua 2021年第5期67卷 1729-1745页

作者： Jun-Yong Jang Won-Seok Lee Jae-Hyun Ro Young-Hawn You Hyoung-Kyu Song Department of Information and Communication Engineering Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea Department of Computer Engineering Sejong UniversitySeoul05006Korea

In this paper,a novel precoding scheme based on the Gauss-Seidel(GS)method is proposed for downlink massive multiple-input multiple-output(MIMO)*** GS method iteratively approximates the matrix inversion and reduces the overall complexity of the precoding *** addition,the GS method shows a fast convergence rate to the Zero-forcing(ZF)method that requires an exact invertible ***,to satisfy demanded error performance and converge to the error performance of the ZF method in the practical condition such as spatially correlated channels,more iterations are necessary for the GS method and increase the overall *** efficient approximation with fewer iterations,this paper proposes a weighted GS(WGS)method to improve the approximation accuracy of the GS *** optimal weights that accelerate the convergence rate by improved accuracy are computed by the least square(LS)*** the computation of weights,the different weights are applied for each iteration of the GS *** addition,an efficient method of weight computation is proposed to reduce the complexity of the LS *** simulation results show that bit error rate(BER)performance for the proposed scheme with fewer iterations is better than the GS method in spatially correlated channels.

关键词： Massive MIMO GS matrix inversion complexity weight

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An approach for measuring spatial similarity among COVID-19 epicenters

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Geo-Spatial Information science 2023年第3期26卷 496-513页

作者： Neda Kaffash Charandabi Abolghasem Sadeghi-Niaraki Soo-Mi Choi Tamer Abuhmed Geomatic Department Marand Technical FacultyUniversity of TabrizTabrizIran Department of Computer Science and Engineering and Convergence Engineering for Intelligent Drone Sejong UniversitySeoulSouth Korea College of Computing and Informatics Sungkyunkwan UniversitySuwonSouth Korea

Most countries and territories worldwide are affected by coronavirus disease 2019(COVID-19),and some cities have become known as epicenters owing to high *** of the changeable and unknown nature of the virus,managers of different cities could learn from the experiences of cities that have been successful in controlling COVID-19 instead of wasting time exploring different *** would be even more beneficial if they analyzed the experiences of similar *** similarity of such cities could be examined within a geographic information system based on various *** study investigated the similarities among eight cities-Wuhan,Tehran,Bergamo,Madrid,Paris,Daegu,New York,and Berlin-in terms of the COVID-19 situation(target)in these locations based on proximity factors,weather,and demographic ***,the factor and target layers were prepared,and then similar cities were identified using a similarity model and different distance *** results were aggregated using the Copeland method because of the different outcomes for each *** most similar city was identified for each selected city,and its similarity level was determined based on these *** results suggested the following pairs of similar cities:Wuhan-Berlin,Tehran-Berlin,Daegu-Wuhan,Bergamo-Madrid,Paris-Madrid,and New York-Paris based on COVID-19 related data up to 15 April 2020(target T1),and Daegu-Wuhan,Tehran-Madrid,Bergamo-Paris,Berlin-Paris,and New York-Madrid up to 8 December 2021(target T2)with a minimum and maximum similarity rate of 82.85%and 92.36%,*** similar cities,the most similar factors among the proximity criteria are the distance from bus and metro stations;among weather,the criteria are humidity and pressure;and among demographics,the criteria are male and female population ratios,literacy ratio,and death ratio from asthma and cancer,with a minimum and maximum difference of 0%and 64.94%,*** addition,according to the rando

关键词： COVID-19 GIS spatial similarity environmental factors demographic factors

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