Pub Date : 2025-01-10DOI: 10.1109/JSEN.2025.3525700
Shiquan Ding;Jun Huang;Zhanchuan Cai;Yong Ma;Kangle Wu;Fan Fan
Infrared (IR) and visible (VI) image fusion enables to combine the strengths of both original images adequately, retaining essential target information and abundant detailed textures. Existing fusion methods mainly cater to well-illuminated scenes. Although some researchers have explored complex scenes, there are still some unresolved issues, such as suboptimal lighting levels and loss of local details. To overcome these issues, we introduce a novel method named FIAFusion. FIAFusion is structured into three primary components: initially, the illumination-adaptive network (IAN) adjusts the illumination of the original VI image adaptively. Subsequently, the fusion network (FUN) efficiently merges the complementary information from the original IR image and the illumination-adapted VI image into a fused image of high visual quality. To achieve an ideal illumination level in the fused image, the feedback network (FEN) is designed to feedback on the illumination information of the fused image to both IAN and FUN, guiding the illumination correction to facilitate mutual promotion between illumination adaptation and fusion process effectively. Extensive comparative and supplementary experiments conducted on LLVIP and MSRS datasets indicate that our method surpasses state-of-the-art (SOTA) IR and VI image fusion methods. Moreover, our method demonstrates significant performance improvements in pedestrian detection tasks.
{"title":"FIAFusion: A Feedback-Based Illumination-Adaptive Infrared and Visible Image Fusion Method","authors":"Shiquan Ding;Jun Huang;Zhanchuan Cai;Yong Ma;Kangle Wu;Fan Fan","doi":"10.1109/JSEN.2025.3525700","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3525700","url":null,"abstract":"Infrared (IR) and visible (VI) image fusion enables to combine the strengths of both original images adequately, retaining essential target information and abundant detailed textures. Existing fusion methods mainly cater to well-illuminated scenes. Although some researchers have explored complex scenes, there are still some unresolved issues, such as suboptimal lighting levels and loss of local details. To overcome these issues, we introduce a novel method named FIAFusion. FIAFusion is structured into three primary components: initially, the illumination-adaptive network (IAN) adjusts the illumination of the original VI image adaptively. Subsequently, the fusion network (FUN) efficiently merges the complementary information from the original IR image and the illumination-adapted VI image into a fused image of high visual quality. To achieve an ideal illumination level in the fused image, the feedback network (FEN) is designed to feedback on the illumination information of the fused image to both IAN and FUN, guiding the illumination correction to facilitate mutual promotion between illumination adaptation and fusion process effectively. Extensive comparative and supplementary experiments conducted on LLVIP and MSRS datasets indicate that our method surpasses state-of-the-art (SOTA) IR and VI image fusion methods. Moreover, our method demonstrates significant performance improvements in pedestrian detection tasks.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"7667-7680"},"PeriodicalIF":4.3,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143438325","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}
Pub Date : 2025-01-09DOI: 10.1109/JPHOTOV.2024.3523546
Chiara Barretta;Astrid E. Macher;Marc Köntges;Julian Ascencio-Vásquez;Marko Topič;Gernot Oreski
A damage analysis was conducted on photovoltaic modules with identical bill of materials exposed to different climates: Cfb moderate and Af tropical, according to the Köppen-Geiger climate classification. The combination of high temperature, relative humidity, and high ultraviolet (UV) radiation was the cause of severe degradation for the modules exposed to tropical climates (TR), whereas the module exposed to a moderate climate did not experience a significant loss in performance. The modules installed in TR, on the contrary, showed significant power degradation after approximately 8 years of exposure, primarily attributed to acetic acid-related degradation modes. Encapsulant samples were extracted from the selected modules and characterized to determine changes in chemical structure, thermal stability, and consumption of additives and stabilizers. The results of qualitative additive analysis showed that the UV absorber was no longer detectable in the front encapsulant extracted from modules exposed in TR. The consumption of the stabilizers was considered as the main cause of reduction of molar mass. The presence of acetic acid was evident in both electroluminescence images and ion chromatography results. While differential scanning calorimetry successfully detected a reduction in molar mass, thermogravimetric analysis, and infrared spectroscopy proved unsuitable for identifying chain scission phenomena.
{"title":"Effect of Encapsulant Degradation on Photovoltaic Modules Performances Installed in Different Climates","authors":"Chiara Barretta;Astrid E. Macher;Marc Köntges;Julian Ascencio-Vásquez;Marko Topič;Gernot Oreski","doi":"10.1109/JPHOTOV.2024.3523546","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2024.3523546","url":null,"abstract":"A damage analysis was conducted on photovoltaic modules with identical bill of materials exposed to different climates: Cfb moderate and Af tropical, according to the Köppen-Geiger climate classification. The combination of high temperature, relative humidity, and high ultraviolet (UV) radiation was the cause of severe degradation for the modules exposed to tropical climates (TR), whereas the module exposed to a moderate climate did not experience a significant loss in performance. The modules installed in TR, on the contrary, showed significant power degradation after approximately 8 years of exposure, primarily attributed to acetic acid-related degradation modes. Encapsulant samples were extracted from the selected modules and characterized to determine changes in chemical structure, thermal stability, and consumption of additives and stabilizers. The results of qualitative additive analysis showed that the UV absorber was no longer detectable in the front encapsulant extracted from modules exposed in TR. The consumption of the stabilizers was considered as the main cause of reduction of molar mass. The presence of acetic acid was evident in both electroluminescence images and ion chromatography results. While differential scanning calorimetry successfully detected a reduction in molar mass, thermogravimetric analysis, and infrared spectroscopy proved unsuitable for identifying chain scission phenomena.","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"15 2","pages":"290-296"},"PeriodicalIF":2.5,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143455097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-09DOI: 10.1109/JSEN.2025.3525541
Jiangtian Yang;Xiaoqian Duo;Mingguang Liu
The fault prognosis of the motor plays a key role in reducing unplanned maintenance and improving machine reliability and safety. The main problem of industrial applications lies in usually only a small amount of operation data of motors is available. Establishing an effective forecasting model is a challenging task. A novel prognostics approach based on the hybrid entropy of motor current signal and a combined forecasting model is proposed. First, the wavelet packet energy entropy and Renyi spectrum entropy are extracted from the online motor current signal and then are integrated into a unified one. Since the hybrid entropy describes the change in current signals from the views of concentration degree of time-frequency-domain energy and the uniformity degree of spectrum distribution systematically, it represents motor working conditions accurately. Next, a hybrid approach based on wavelet transform, autoregressive integrated moving average (ARIMA), and improved GM(1, 1) model is employed. The time series of entropy values was decomposed into different trend items by wavelet transform, and the growth trend and random trend are described by the background value optimization GM(1, 1) model and ARIMA model, respectively. Finally, the prediction output was obtained by wavelet reconstruction. Industrial experiment results demonstrate the effectiveness of the proposed approach for motor fault prediction based on small amounts of data.
{"title":"Motor Failure Prediction Using Hybrid Entropy and Combined Forecasting Model","authors":"Jiangtian Yang;Xiaoqian Duo;Mingguang Liu","doi":"10.1109/JSEN.2025.3525541","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3525541","url":null,"abstract":"The fault prognosis of the motor plays a key role in reducing unplanned maintenance and improving machine reliability and safety. The main problem of industrial applications lies in usually only a small amount of operation data of motors is available. Establishing an effective forecasting model is a challenging task. A novel prognostics approach based on the hybrid entropy of motor current signal and a combined forecasting model is proposed. First, the wavelet packet energy entropy and Renyi spectrum entropy are extracted from the online motor current signal and then are integrated into a unified one. Since the hybrid entropy describes the change in current signals from the views of concentration degree of time-frequency-domain energy and the uniformity degree of spectrum distribution systematically, it represents motor working conditions accurately. Next, a hybrid approach based on wavelet transform, autoregressive integrated moving average (ARIMA), and improved GM(1, 1) model is employed. The time series of entropy values was decomposed into different trend items by wavelet transform, and the growth trend and random trend are described by the background value optimization GM(1, 1) model and ARIMA model, respectively. Finally, the prediction output was obtained by wavelet reconstruction. Industrial experiment results demonstrate the effectiveness of the proposed approach for motor fault prediction based on small amounts of data.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"7006-7014"},"PeriodicalIF":4.3,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430492","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}
In this study, to enhance sensor performance a nonenzymatic lactic acid (LA) sensor based on SnO2 was developed and modified via graphitic carbon nitride (g-C3N4)/ZnS composite material to enhance its sensing performance. The modified sensor generates a voltage through the reaction between LA and the material, and its performance is characterized using a voltage-time measurement system. Specific evaluation criteria include average sensitivity, linearity, repeatability, response time, selectivity, drift effect, and limit of detection (LOD). Experimental evidence shows that compared to the unmodified SnO2 variant, the g-C3N4/ZnS-modified sensor exhibits superior performance in LA concentrations ranging from 1 to 9 mM, with an average sensitivity of 8.02 ± 0.12 mV/mM and with a linearity of 0.999. This modification significantly enhances sensor performance.
{"title":"Preparation of a Nonenzymatic Potentiometric Lactic Acid Biosensor Modified by g-C₃N₄/ZnS Composite Materials on a SnO₂-Coated Flexible Printed Circuit Board","authors":"Yu-Hsun Nien;Xin-Han Chen;Jung-Chuan Chou;Chih-Hsien Lai;Po-Yu Kuo;Po-Hui Yang;Jyun-Ming Huang;Wei-Shun Chen;Yu-Wei Chen;Yi-Wen Huang","doi":"10.1109/JSEN.2024.3525078","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3525078","url":null,"abstract":"In this study, to enhance sensor performance a nonenzymatic lactic acid (LA) sensor based on SnO2 was developed and modified via graphitic carbon nitride (g-C3N4)/ZnS composite material to enhance its sensing performance. The modified sensor generates a voltage through the reaction between LA and the material, and its performance is characterized using a voltage-time measurement system. Specific evaluation criteria include average sensitivity, linearity, repeatability, response time, selectivity, drift effect, and limit of detection (LOD). Experimental evidence shows that compared to the unmodified SnO2 variant, the g-C3N4/ZnS-modified sensor exhibits superior performance in LA concentrations ranging from 1 to 9 mM, with an average sensitivity of 8.02 ± 0.12 mV/mM and with a linearity of 0.999. This modification significantly enhances sensor performance.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"6007-6016"},"PeriodicalIF":4.3,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422823","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}
The yield of photovoltaic (PV) modules is influenced by various environmental factors, particularly solar irradiance and temperature. However, the measured solar irradiance does not accurately represent the real light intensity absorbed by different types of solar cells, and the measured temperature does not represent the actual cell temperature in PV modules. In this article, equivalent irradiance and temperature are proposed and used to improve the accuracy of output performance estimation of PV modules. First, equivalent irradiance and temperature under different operating condition are obtained by fitting measured I–V data by using the guaranteed convergence particle swarm optimization. Second, the relationship between the equivalent irradiance and temperature and environmental factors is established by an artificial neural network (ANN) model. Two types of ANNs with different input vector are proposed to calculated equivalent irradiance and temperature. The accuracy of the proposed method was validated by experimental data for four different types of PV modules under wide operating conditions.
{"title":"A Novel Method for Performance Estimation of PV Modules Using Equivalent Irradiance and Temperature","authors":"Jinlong Zhang;Zhenguang Liang;Yunpeng Zhang;Hai Zhou;Ji Wu;Honglu Zhu","doi":"10.1109/JPHOTOV.2024.3521090","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2024.3521090","url":null,"abstract":"The yield of photovoltaic (PV) modules is influenced by various environmental factors, particularly solar irradiance and temperature. However, the measured solar irradiance does not accurately represent the real light intensity absorbed by different types of solar cells, and the measured temperature does not represent the actual cell temperature in PV modules. In this article, equivalent irradiance and temperature are proposed and used to improve the accuracy of output performance estimation of PV modules. First, equivalent irradiance and temperature under different operating condition are obtained by fitting measured <italic>I–V</i> data by using the guaranteed convergence particle swarm optimization. Second, the relationship between the equivalent irradiance and temperature and environmental factors is established by an artificial neural network (ANN) model. Two types of ANNs with different input vector are proposed to calculated equivalent irradiance and temperature. The accuracy of the proposed method was validated by experimental data for four different types of PV modules under wide operating conditions.","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"15 2","pages":"274-279"},"PeriodicalIF":2.5,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143455099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-09DOI: 10.1109/JSEN.2024.3525441
Usman Anwar;Tughrul Arslan;Peter Lomax;Tom C. Russ
Vascular dementia is the second most prevalent type of dementia among the elderly population and is one of the leading causes of mortality. Ischemic stroke and brain atrophy are the predominant pathologies associated with vascular dementia. Early detection and regular monitoring are crucial to prevent the advancement of vascular dementia. Conventional medical imaging is expensive, requires extensive medical supervision and is not easily accessible. This research presents a novel concept of low-cost and noninvasive smart glasses, equipped with miniaturized octagonal monopole-patch antenna (OMPA) sensors and a crescent array sensor for vascular dementia detection. This radio frequency (RF) enabled portable system is capable of accurately identifying and imaging brain infarction, atrophy, and stroke in their early stages. The fabricated device is experimentally verified using multiple artificial stroke and atrophy targets inside a realistic brain phantom. The backscattered RF data is iteratively processed using customized imaging algorithms to achieve improved image quality, noise suppression, and contrast resolution with reduced image artifacts and computational complexity. Based on the iterative refinement, the double-stage minimum variance delay multiply and sum (DS-MV-DMAS) algorithm is proposed for imaging stroke and brain atrophy. The quantitative results indicate that DS-MV-DMAS results in 43% lower level of side lobes and leads to 26%, 28%, and 27% improvement in signal-to-noise ratio (SNR), full width at half-maximum and contrast ratio (CR), respectively, compared to other state-of-the-art (SOTA) imaging algorithms. The promising results demonstrate the feasibility of the prototype system as a cost-effective, portable, and noninvasive alternative for the diagnosis and monitoring of vascular dementia.
{"title":"Radio Frequency-Based Vascular Dementia Sensing and Imaging System Targeting Smart Glasses","authors":"Usman Anwar;Tughrul Arslan;Peter Lomax;Tom C. Russ","doi":"10.1109/JSEN.2024.3525441","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3525441","url":null,"abstract":"Vascular dementia is the second most prevalent type of dementia among the elderly population and is one of the leading causes of mortality. Ischemic stroke and brain atrophy are the predominant pathologies associated with vascular dementia. Early detection and regular monitoring are crucial to prevent the advancement of vascular dementia. Conventional medical imaging is expensive, requires extensive medical supervision and is not easily accessible. This research presents a novel concept of low-cost and noninvasive smart glasses, equipped with miniaturized octagonal monopole-patch antenna (OMPA) sensors and a crescent array sensor for vascular dementia detection. This radio frequency (RF) enabled portable system is capable of accurately identifying and imaging brain infarction, atrophy, and stroke in their early stages. The fabricated device is experimentally verified using multiple artificial stroke and atrophy targets inside a realistic brain phantom. The backscattered RF data is iteratively processed using customized imaging algorithms to achieve improved image quality, noise suppression, and contrast resolution with reduced image artifacts and computational complexity. Based on the iterative refinement, the double-stage minimum variance delay multiply and sum (DS-MV-DMAS) algorithm is proposed for imaging stroke and brain atrophy. The quantitative results indicate that DS-MV-DMAS results in 43% lower level of side lobes and leads to 26%, 28%, and 27% improvement in signal-to-noise ratio (SNR), full width at half-maximum and contrast ratio (CR), respectively, compared to other state-of-the-art (SOTA) imaging algorithms. The promising results demonstrate the feasibility of the prototype system as a cost-effective, portable, and noninvasive alternative for the diagnosis and monitoring of vascular dementia.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"7310-7322"},"PeriodicalIF":4.3,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446189","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}
Pub Date : 2025-01-09DOI: 10.1109/JSEN.2024.3525055
Udara S. Somarathna;Behnam Garakani;Darshana L. Weerawarne;Mohammed Alhendi;Mark D. Poliks;Matthew Misner;Andrew Burns;Gurvinder S. Khinda;Azar Alizadeh
Water-based carbon inks provide a cost-effective and sustainable alternative to organic-solvent-based metal conductive inks, making them attractive for wearable sensor applications. However, poor adhesion on nonporous polymer substrates and susceptibility to temperature and humidity fluctuations raise concerns about printability and reliability, hindering their widespread commercial adoption. This study focuses on screen-printing defect-free multilayer structures on flexible and stretchable polymer substrates using a commercial water-based conductive carbon black (CB) ink and evaluating their reliability. A robust printing process was developed by modifying the fabrication flow, optimizing printing parameters, and maintaining atmospheric relative humidity (RH) between 70% and 75%. Multilayer sweat-rate electrodes (SREs) with conductors and resistors were successfully screen-printed using a solvent-based silver ink and a water-based CB ink, respectively, and their environmental and mechanical reliability was comprehensively investigated. The water-based carbon resistors printed on polyimide substrate demonstrated promising results. Ambient-dried resistors on polyimide exhibited satisfactory electrical performance and reliability, while thermal curing further reduced their electrical resistance by 18% without compromising reliability. Moreover, these resistors demonstrated excellent environmental and mechanical reliability by withstanding thermal exposure at 125 ° C, RH of 15%, and 500 tensile bending cycles at a 1-cm bend radius, suggesting their suitability for wearable sensors. Failure analysis revealed the development of crater-like morphological structures during the drying process, which later acted as stress concentration points. Resistors printed on polyester, high-density polyethylene, and thermoplastic polyurethane (TPU) substrates failed due to cracking, delamination, ink-to-ink interactions, or out-of-plane deformation. Cracking and delamination patterns provided useful insights into failure mechanisms.
{"title":"Reliability of Screen-Printed Water-Based Carbon Resistors for Sustainable Wearable Sensors","authors":"Udara S. Somarathna;Behnam Garakani;Darshana L. Weerawarne;Mohammed Alhendi;Mark D. Poliks;Matthew Misner;Andrew Burns;Gurvinder S. Khinda;Azar Alizadeh","doi":"10.1109/JSEN.2024.3525055","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3525055","url":null,"abstract":"Water-based carbon inks provide a cost-effective and sustainable alternative to organic-solvent-based metal conductive inks, making them attractive for wearable sensor applications. However, poor adhesion on nonporous polymer substrates and susceptibility to temperature and humidity fluctuations raise concerns about printability and reliability, hindering their widespread commercial adoption. This study focuses on screen-printing defect-free multilayer structures on flexible and stretchable polymer substrates using a commercial water-based conductive carbon black (CB) ink and evaluating their reliability. A robust printing process was developed by modifying the fabrication flow, optimizing printing parameters, and maintaining atmospheric relative humidity (RH) between 70% and 75%. Multilayer sweat-rate electrodes (SREs) with conductors and resistors were successfully screen-printed using a solvent-based silver ink and a water-based CB ink, respectively, and their environmental and mechanical reliability was comprehensively investigated. The water-based carbon resistors printed on polyimide substrate demonstrated promising results. Ambient-dried resistors on polyimide exhibited satisfactory electrical performance and reliability, while thermal curing further reduced their electrical resistance by 18% without compromising reliability. Moreover, these resistors demonstrated excellent environmental and mechanical reliability by withstanding thermal exposure at 125 ° C, RH of 15%, and 500 tensile bending cycles at a 1-cm bend radius, suggesting their suitability for wearable sensors. Failure analysis revealed the development of crater-like morphological structures during the drying process, which later acted as stress concentration points. Resistors printed on polyester, high-density polyethylene, and thermoplastic polyurethane (TPU) substrates failed due to cracking, delamination, ink-to-ink interactions, or out-of-plane deformation. Cracking and delamination patterns provided useful insights into failure mechanisms.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"6449-6463"},"PeriodicalIF":4.3,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446366","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}
The development of signal enhancement techniques in fiber-optic sensors has facilitated accurate measurements of low-concentration samples. In this article, a fiber-optic sensor based on local surface plasmon resonance (LSPR), which combines offset splicing and S-taper techniques with low-dimensional materials, is proposed for putrescine (PUT) detection. The multimode fiber–single-mode fiber–multimode fiber sliding structure is fabricated by lateral offset technique. In addition, the S-taper is fabricated on the misaligned MMF, which can produce more light energy leakage. Gold nanoparticles (AuNPs), cerium oxide nanorods, and multiwall carbon nanotubes (MWCNTs) are attached to the fiber probe to improve the sensitivity of the fiber-optic sensor and achieve fast sample detection. PUT is detected by specific recognition of the diamine oxidase (DAO). Based on the above two methods, the optical fiber probe is applied to the detection of PUT. The sensitivity of 795.33 pm/$mu$ M and the detection limit of 0.8223 $mu$ M are achieved over the detection range of 0–100 $mu$ M. The experimental results show that the signal-enhanced fiber-optic sensor has great potential for fast, accurate, and label-free PUT.
{"title":"Signal-Enhanced Fiber-Optic LSPR Sensor With Hybrid Nanointerface for Ultrasensitive Detection of Putrescine in Low Concentrations","authors":"Wenshuai Ma;Guoru Li;Xiangshan Li;Ragini Singh;Bingyuan Zhang;Santosh Kumar","doi":"10.1109/JSEN.2024.3525189","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3525189","url":null,"abstract":"The development of signal enhancement techniques in fiber-optic sensors has facilitated accurate measurements of low-concentration samples. In this article, a fiber-optic sensor based on local surface plasmon resonance (LSPR), which combines offset splicing and S-taper techniques with low-dimensional materials, is proposed for putrescine (PUT) detection. The multimode fiber–single-mode fiber–multimode fiber sliding structure is fabricated by lateral offset technique. In addition, the S-taper is fabricated on the misaligned MMF, which can produce more light energy leakage. Gold nanoparticles (AuNPs), cerium oxide nanorods, and multiwall carbon nanotubes (MWCNTs) are attached to the fiber probe to improve the sensitivity of the fiber-optic sensor and achieve fast sample detection. PUT is detected by specific recognition of the diamine oxidase (DAO). Based on the above two methods, the optical fiber probe is applied to the detection of PUT. The sensitivity of 795.33 pm/<inline-formula> <tex-math>$mu$ </tex-math></inline-formula>M and the detection limit of 0.8223 <inline-formula> <tex-math>$mu$ </tex-math></inline-formula>M are achieved over the detection range of 0–100 <inline-formula> <tex-math>$mu$ </tex-math></inline-formula>M. The experimental results show that the signal-enhanced fiber-optic sensor has great potential for fast, accurate, and label-free PUT.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"6388-6395"},"PeriodicalIF":4.3,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446279","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}
Pub Date : 2025-01-09DOI: 10.1109/JSEN.2024.3524657
Chuan Qiao;Hui Li;Zikang Li;Yuntao Wu
In conventional liquid crystal microlens array (LC-MLA), the discontinuous and nonuniform alignment of liquid crystal (LC) presents a significant challenge. We address this issue by introducing an innovative orientation microstructure that employs aluminum-doped zinc oxide (AZO). This approach could ensure stable and continuous alignment in LC-MLA. We reconstruct high-definition images from acquired light field images with enhanced contrast and signal-to-noise ratio (SNR) by applying the total variation (TV) denoising algorithm and convex optimization theory. The proposed AZO-based alignment method exhibits high-performance properties in the orientation of LC molecules. Experimental results reveal that the AZO microstructure induces a stable and continuous alignment of LC molecules, reconstructing an image with a peak SNR (PSNR) of approximately 34 dB and a structural similarity index (SSIM) of about 0.912. Compared to conventional LC-MLA, our method achieves superior light field images and substantially enhances the resolution of light field images.
{"title":"Liquid Crystal Microlens Arrays Based on Aluminum-Doped Zinc Oxide Oriented Microstructure Facilitate Light Field Image Resolution Enhancement","authors":"Chuan Qiao;Hui Li;Zikang Li;Yuntao Wu","doi":"10.1109/JSEN.2024.3524657","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3524657","url":null,"abstract":"In conventional liquid crystal microlens array (LC-MLA), the discontinuous and nonuniform alignment of liquid crystal (LC) presents a significant challenge. We address this issue by introducing an innovative orientation microstructure that employs aluminum-doped zinc oxide (AZO). This approach could ensure stable and continuous alignment in LC-MLA. We reconstruct high-definition images from acquired light field images with enhanced contrast and signal-to-noise ratio (SNR) by applying the total variation (TV) denoising algorithm and convex optimization theory. The proposed AZO-based alignment method exhibits high-performance properties in the orientation of LC molecules. Experimental results reveal that the AZO microstructure induces a stable and continuous alignment of LC molecules, reconstructing an image with a peak SNR (PSNR) of approximately 34 dB and a structural similarity index (SSIM) of about 0.912. Compared to conventional LC-MLA, our method achieves superior light field images and substantially enhances the resolution of light field images.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"5995-6006"},"PeriodicalIF":4.3,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422885","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}
A kind of magnetic field sensor with enhanced sensitivity was designed by integrating the fiber Bragg gratings (FBGs) with the curved terbium-dysprosium-iron alloy (Terfenol-D) rods. Seven magnetic field sensors with Terfenol-D rods of different curvatures were fabricated and tested. The highest enhancement in magnetic field sensitivity is observed for sensors equipped with Terfenol-D rods having a curvature of 50 m$^{-{{1}}}$ . In addition, the designed sensor demonstrated directional sensitivity to the magnetic field, which was obtained to be 3.5 pm/° at 10 mT. The utilization of magnetostrictive materials in unconventional shapes (magnetostrictive rods in curved shapes) in this study not only enhances magnetic field sensitivity but also opens up a world of possibilities for future specific applications.
{"title":"Fiber-Optic Magnetic Field Sensor Based on Curved Terfenol-D Rod Combined With FBG","authors":"Zhe Yang;Shengli Pu;Tengfei Xu;Weinan Liu;Chencheng Zhang;Mahieddine Lahoubi","doi":"10.1109/JSEN.2025.3525539","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3525539","url":null,"abstract":"A kind of magnetic field sensor with enhanced sensitivity was designed by integrating the fiber Bragg gratings (FBGs) with the curved terbium-dysprosium-iron alloy (Terfenol-D) rods. Seven magnetic field sensors with Terfenol-D rods of different curvatures were fabricated and tested. The highest enhancement in magnetic field sensitivity is observed for sensors equipped with Terfenol-D rods having a curvature of 50 m<inline-formula> <tex-math>$^{-{{1}}}$ </tex-math></inline-formula>. In addition, the designed sensor demonstrated directional sensitivity to the magnetic field, which was obtained to be 3.5 pm/° at 10 mT. The utilization of magnetostrictive materials in unconventional shapes (magnetostrictive rods in curved shapes) in this study not only enhances magnetic field sensitivity but also opens up a world of possibilities for future specific applications.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"6234-6241"},"PeriodicalIF":4.3,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430466","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}
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