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IEEE Transactions on Device and Materials Reliability Publication Information IEEE器件与材料可靠性学报

IF 2.5 3区工程技术

IEEE Transactions on Device and Materials Reliability Pub Date : 2025-06-09 DOI: 10.1109/TDMR.2025.3558210

引用次数: 0

Call for Nominations for Editor-in-Chief IEEE Transactions on Electron Devices(TED) IEEE电子设备汇刊（TED）总编辑提名公告

IF 2.5 3区工程技术

IEEE Transactions on Device and Materials Reliability Pub Date : 2025-06-09 DOI: 10.1109/TDMR.2025.3558656

引用次数: 0

Wide Band Gap Semiconductors for Automotive Applications 汽车用宽带隙半导体

IF 2.5 3区工程技术

IEEE Transactions on Device and Materials Reliability Pub Date : 2025-06-09 DOI: 10.1109/TDMR.2025.3575820

引用次数: 0

Efficient and Robust Fabrication of Soft Sensors via Injection With Auxiliary Suction in Multilayered Microchannels With a Liquid Metal Alloy 基于液态金属合金的多层微通道辅助吸入注射软传感器的高效鲁棒制造

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-06 DOI: 10.1109/JSEN.2025.3575503

Hyungseok Yoon;Seung-Won Kim

{"title":"Efficient and Robust Fabrication of Soft Sensors via Injection With Auxiliary Suction in Multilayered Microchannels With a Liquid Metal Alloy","authors":"Hyungseok Yoon;Seung-Won Kim","doi":"10.1109/JSEN.2025.3575503","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3575503","url":null,"abstract":"From 2011 to August 2024, 795 papers have utilized liquid metals like eutectic gallium-indium alloy (EGaIn) or Galinstan in microfluidic systems, flexible electronics, and soft robotics, as reported in the Scopus database. The most common manufacturing techniques include manual needle injection, stencil printing, direct writing, and vacuum filling, with manual needle injection being the most prevalent due to its simplicity and cost-effectiveness. However, this method often results in high failure rates and inconsistent outcomes due to manual variability. Other techniques also present challenges, such as high setup costs and limitations based on material stiffness. To address these issues, a needle injection with an auxiliary suction method has been introduced. This approach enhances manufacturing success and consistency, especially in multilayered microchannel structures with varying material stiffness. The incorporation of auxiliary suction reduces fabrication time by 25.3% and decreases pressure on the microfluidic channels by 10.3%, leading to more stable and reliable production of multilayered microchannel soft sensors. This method is expected to significantly advance liquid metal-based applications by providing a more efficient, affordable, and reliable fabrication process.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 13","pages":"23948-23957"},"PeriodicalIF":4.3,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144557725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Blue Narrowband Photomultiplication Type Organic Photodetector Using ZnPc as Photon Field Modulation Layer 利用ZnPc作为光子场调制层的蓝色窄带光电倍增型有机光电探测器

IF 2.1 4区工程技术

IEEE Transactions on Nanotechnology Pub Date : 2025-06-06 DOI: 10.1109/TNANO.2025.3577501

Sampati Rao Sridhar;Medha Joshi;Brijesh Kumar

引用次数: 0

Transformer-Based RGBT Tracking With Spatio-Temporal Information Fusion 基于变压器的时空信息融合rbt跟踪

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-05 DOI: 10.1109/JSEN.2025.3575188

Di Yuan;Haiping Zhang;Qiao Liu;Xiaojun Chang;Zhenyu He

{"title":"Transformer-Based RGBT Tracking With Spatio-Temporal Information Fusion","authors":"Di Yuan;Haiping Zhang;Qiao Liu;Xiaojun Chang;Zhenyu He","doi":"10.1109/JSEN.2025.3575188","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3575188","url":null,"abstract":"RGB-thermal (RGBT) tracking usually uses an RGB tracker as the base model, and then uses the RGBT dataset to fully fine-tune the model. These methods ignore the differences in target features in the RGB domain and the TIR domain. At the same time, existing RGBT trackers match the spatial features of the initial template and the search image, ignoring the role of temporal information in RGBT tracking, resulting in the failure of the tracker to track in complex scenarios such as change in the appearance of the target and occlusion. To address the above problems, we propose a simple and efficient tracker called STTrack. The tracker adopts a symmetric dual-stream structure, which consists of several fine tuning transformer (FT Transformer) encoders, a prediction head, and an online update module. Specifically, the FT Transformer encoder first adds some trainable parameters to the frozen pretrained RGB-based tracker, transfers the feature extraction capability from the RGB domain to the TIR domain, and enhances the model’s perception of cross-modal data; second, the output features of the RGB and TIR modalities are fused and fed into the prediction head to obtain the target’s position; finally, the online update module obtains an online template with temporal information, which complements the spatial information provided by the initial template. The spatio-temporal information provided by the dual templates improves the RGBT tracker’s ability to locate targets in complex environments. Extensive quantitative and qualitative experiments demonstrate that our approach achieves state-of-the-art performance on four most popular RGBT benchmarks and runs at 32 FPS in real time.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 13","pages":"25386-25396"},"PeriodicalIF":4.3,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving Distributed Moving Horizon Estimation Over Wireless Sensor Networks With Application to Mobile Robot Localization 改进无线传感器网络的分布式移动地平线估计及其在移动机器人定位中的应用

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-05 DOI: 10.1109/JSEN.2025.3573283

Chaoyang Liang;Defeng He;Yun Chen

{"title":"Improving Distributed Moving Horizon Estimation Over Wireless Sensor Networks With Application to Mobile Robot Localization","authors":"Chaoyang Liang;Defeng He;Yun Chen","doi":"10.1109/JSEN.2025.3573283","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3573283","url":null,"abstract":"This article investigates the distributed state estimation (DSE) problem for constrained nonlinear systems over wireless sensor networks (WSNs). We propose a novel hybrid distributed moving horizon estimation (DMHE) framework that combines both local measurements and prior estimates from neighboring nodes. The local estimation is performed in real time by solving an optimization problem that fuses these two information sources, thereby enhancing accuracy and robustness. A key advantage of our framework lies in designing the consensus prior weighting parameters offline via linear matrix inequalities (LMIs), providing a more flexible and scalable approach to improving global estimation performance. Furthermore, under disturbance boundedness, collective observability, and network connectivity, we prove that the global estimation error converges exponentially to a well-defined bound. The proposed framework generalizes two distinct DMHE approaches—consensus on prior estimates and consensus on measurements. Numerical results on a mobile robot localization task demonstrate its superior performance, underscoring both its theoretical soundness and practical feasibility.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 13","pages":"26032-26041"},"PeriodicalIF":4.3,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Capacitive Humidity Sensor With Enhanced Sensitivity Based on Graphene Oxide/Lignosulfonate With Laser-Induced Graphene Electrodes for Noncontact Detection 基于氧化石墨烯/木质素磺酸盐激光诱导石墨烯电极非接触检测的高灵敏度电容式湿度传感器

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-05 DOI: 10.1109/JSEN.2025.3575104

Yexiong Huang;Chunxin Hao;Xingyuan Wang;Zikai Bao;Tingyu Liu;Jinmin Li;Shuaiqi Li;Mingyu Pi;Dingke Zhang

{"title":"Capacitive Humidity Sensor With Enhanced Sensitivity Based on Graphene Oxide/Lignosulfonate With Laser-Induced Graphene Electrodes for Noncontact Detection","authors":"Yexiong Huang;Chunxin Hao;Xingyuan Wang;Zikai Bao;Tingyu Liu;Jinmin Li;Shuaiqi Li;Mingyu Pi;Dingke Zhang","doi":"10.1109/JSEN.2025.3575104","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3575104","url":null,"abstract":"High-performance graphene-based humidity sensors have attracted significant attention in noncontact detection and human-interface interaction. Nevertheless, fabricating high-performance graphene-based humidity sensors using low-cost and environmentally friendly approaches remains a challenge. In this article, a capacitive humidity sensor with enhanced sensitivity based on graphene oxide (GO)/lignosulfonate (LS) with laser-induced graphene (LIG) electrodes is proposed using the laser direct writing technology and the drop-coating method. NOMEX polyimide composite paper is employed to prepare interdigitated electrodes through laser direct writing technology. Renewable LS is introduced into GO as a humidity-sensitive layer to enhance the humidity-sensing performance of the sensors. The sensitivity can be greatly improved to 58057 pF/% RH under the optimized parameters. Meanwhile, the graphene-based humidity sensor features low hysteresis, excellent repeatability, and long-term stability. Furthermore, the humidity sensor demonstrates potential application in human respiration monitoring and noncontact human-interface interaction. This work can provide a strategy for designing and fabricating high-performance graphene-based humidity sensors for noncontact monitoring applications.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 13","pages":"25887-25893"},"PeriodicalIF":4.3,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multiantenna Fusion Fingerprint Localization Based on Weighted Broad Learning System 基于加权广义学习系统的多天线融合指纹定位

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-04 DOI: 10.1109/JSEN.2025.3574436

Zhigang Liu;Yuying Wang;Jialing Chen

引用次数: 0

New Spectral and Textural Feature Combinations for Corrosion Detection in Hyperspectral Images of Special Nuclear Materials Packages 特殊核材料包装高光谱图像腐蚀检测的新光谱和纹理特征组合

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-04 DOI: 10.1109/JSEN.2025.3574923

Aoife Keane;Thomas Hillman;Antonio Di Buono;Neil Cockbain;Robert Bernard;Dirk Engelberg;Paul Murray;Jaime Zabalza

{"title":"New Spectral and Textural Feature Combinations for Corrosion Detection in Hyperspectral Images of Special Nuclear Materials Packages","authors":"Aoife Keane;Thomas Hillman;Antonio Di Buono;Neil Cockbain;Robert Bernard;Dirk Engelberg;Paul Murray;Jaime Zabalza","doi":"10.1109/JSEN.2025.3574923","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3574923","url":null,"abstract":"This article presents a novel approach to corrosion detection on special nuclear material (SNM) packages using hyperspectral imaging (HSI). Laboratory samples of carbon steel are exposed to chloride salt solutions (NaCl and KCl) in concentrations ranging from 0.001 to 1.0 M. Images of these samples are captured using a hyperspectral sensor in the visible-near-infrared range [400–1000 nm]. Spectral and spatial features, namely principal components, windowed gradients (WGs), and local binary patterns (LBPs) are extracted from the hyperspectral images. The HSI feature vectors are then used to train a support vector machine (SVM) to detect corrosion. Literature in HSI for corrosion detection emphasizes the spectral features while neglecting the important information that can be gleaned from the spatial domain, for example, textural features. This work demonstrates that the combination of spectral and textural information in corrosion detection can outperform spectral or spatial information alone. The SVM trained on the laboratory samples is then applied to hyperspectral images of an SNM package. Here, the results show a consistency of the joint spectral and textural feature vector giving an excellent indication of where corrosion products have formed. This work introduces a novel nondestructive (ND) and noncontact method for assessing corrosion products on steel surfaces, significantly reducing the visual ambiguity in corrosion detection. Our proposed dual-feature HSI approach marks a significant advancement in the field, providing a more accurate and comprehensive means of detecting corrosion products when compared to existing approaches that focus on spectral or spatial features in isolation.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 13","pages":"25373-25385"},"PeriodicalIF":4.3,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0