Pub Date : 2026-10-15Epub Date: 2026-08-24DOI: 10.1109/JSEN.2026.3724806
Sharon Russo;Nadia G. Boetti;Matteo Giardino;Francesco Chiavaioli;Davide Janner
In this article, we present an ethanol (EtOH) sensor based on a D-shaped optical fiber functionalized with a nanostructured layer of gold nanostars (AuNSs). The functionalization was achieved via a seed-mediated growth method, enabling uniform and controlled nanoparticle deposition on the fiber surface. The sensor was integrated into a custom-designed microfluidic chip, allowing precise control of analyte delivery and ensuring highly reproducible measurements. The sensing mechanism relies on the interaction between the evanescent field of the D-shaped fiber and the AuNSs, which enhances light–matter interaction and increases sensitivity to refractive index (RI) variations induced by EtOH concentration changes. The device exhibited a highly linear response (R${}^{2} =99.960$ ) over a concentration range of 0%–40%, with a detection limit of 0.07% and a response time of approximately 10 s. The combination of nanostructured plasmonic materials and microfluidic integration results in improved sensitivity, repeatability, and response speed. These results demonstrate the potential of D-shaped fiber platforms functionalized with gold nanostructures for the development of compact and efficient chemical sensing systems.
{"title":"Gold Nanostars-Based Microfluidic Optical Fiber Sensor for Enhanced Ethanol Detection","authors":"Sharon Russo;Nadia G. Boetti;Matteo Giardino;Francesco Chiavaioli;Davide Janner","doi":"10.1109/JSEN.2026.3724806","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3724806","url":null,"abstract":"In this article, we present an ethanol (EtOH) sensor based on a D-shaped optical fiber functionalized with a nanostructured layer of gold nanostars (AuNSs). The functionalization was achieved via a seed-mediated growth method, enabling uniform and controlled nanoparticle deposition on the fiber surface. The sensor was integrated into a custom-designed microfluidic chip, allowing precise control of analyte delivery and ensuring highly reproducible measurements. The sensing mechanism relies on the interaction between the evanescent field of the D-shaped fiber and the AuNSs, which enhances light–matter interaction and increases sensitivity to refractive index (RI) variations induced by EtOH concentration changes. The device exhibited a highly linear response (R<inline-formula> <tex-math>${}^{2} =99.960$ </tex-math></inline-formula>) over a concentration range of 0%–40%, with a detection limit of 0.07% and a response time of approximately 10 s. The combination of nanostructured plasmonic materials and microfluidic integration results in improved sensitivity, repeatability, and response speed. These results demonstrate the potential of D-shaped fiber platforms functionalized with gold nanostructures for the development of compact and efficient chemical sensing systems.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 20","pages":"30335-30342"},"PeriodicalIF":4.5,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11664259","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149176139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-10-15Epub Date: 2026-09-04DOI: 10.1109/JSEN.2026.3729011
Chitturi Suneel Kumar;I. Balakrishna;Situ Rani Patre
The demand for real-time food quality monitoring has accelerated the development of low-cost, passive, and printable sensing platforms. This article presents a passive chipless radio frequency identification (RFID) resonator with enhanced sensitivity for intelligent food packaging applications. The proposed design uses a slot-based corner-loaded square loop resonator (CLSLR) operating at 3.5 GHz to achieve stable backscattering and reliable performance under robust environmental conditions. The corner-loaded configuration increases frequency deviation under dielectric loading, resulting in enhanced sensitivity. To validate the sensing mechanism, the dielectric properties of a milk bread (food sample) are measured under controlled moisture (humid) conditions. The response of the proposed tag with bread samples as dielectric loading is monitored using a Horn antenna and a network analyzer. The frequency shifts in the measured response confirm its capability to distinguish different moisture states of the bread sample. The results demonstrate that the proposed tag resonator provides stable, orientation-independent operation and high sensitivity, making it suitable for passive food-quality monitoring applications.
{"title":"A High-Sensitivity Chipless RFID Resonator Exploiting Dielectric Loading for Food Packaging Applications","authors":"Chitturi Suneel Kumar;I. Balakrishna;Situ Rani Patre","doi":"10.1109/JSEN.2026.3729011","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3729011","url":null,"abstract":"The demand for real-time food quality monitoring has accelerated the development of low-cost, passive, and printable sensing platforms. This article presents a passive chipless radio frequency identification (RFID) resonator with enhanced sensitivity for intelligent food packaging applications. The proposed design uses a slot-based corner-loaded square loop resonator (CLSLR) operating at 3.5 GHz to achieve stable backscattering and reliable performance under robust environmental conditions. The corner-loaded configuration increases frequency deviation under dielectric loading, resulting in enhanced sensitivity. To validate the sensing mechanism, the dielectric properties of a milk bread (food sample) are measured under controlled moisture (humid) conditions. The response of the proposed tag with bread samples as dielectric loading is monitored using a Horn antenna and a network analyzer. The frequency shifts in the measured response confirm its capability to distinguish different moisture states of the bread sample. The results demonstrate that the proposed tag resonator provides stable, orientation-independent operation and high sensitivity, making it suitable for passive food-quality monitoring applications.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 20","pages":"31599-31607"},"PeriodicalIF":4.5,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149176163","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 : 2026-10-15Epub Date: 2026-07-03DOI: 10.1109/JSEN.2026.3708066
Amin Kajbaf;Ehsan Yazdian;Mohammad Ali Akhaee;Ramin Toosi;Saeed Gazor
Hand gesture recognition (HGR) using radar sensors enables intuitive, contact-free human–computer interaction. However, real-world deployment is hindered by data loss (DL) induced by interference from nearby radars and environmental obstructions. To address this challenge, we propose a deep learning-based sequence modeling framework that is robust to missing or corrupted data. The system employs an encoder–decoder network to reconstruct clean latent representations from impaired inputs, followed by a scale-shift module that aligns features with gesture categories for accurate classification. Experimental results demonstrate strong resilience, maintaining stable performance with up to 35% DL. Under 20% DL, the system achieves 98.50% recognition accuracy. To evaluate generalization, we tested the model on a separate dataset collected in a new environment with an unseen user and real interference from one or two additional mmWave radars. These corrupted samples were used exclusively for testing, while DL was simulated during training. The proposed system maintained 96.61% accuracy under these adverse conditions, confirming its robustness and reliability in practical, data-degraded scenarios.
{"title":"Deep Gesture Recognition Under Data Loss","authors":"Amin Kajbaf;Ehsan Yazdian;Mohammad Ali Akhaee;Ramin Toosi;Saeed Gazor","doi":"10.1109/JSEN.2026.3708066","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3708066","url":null,"abstract":"Hand gesture recognition (HGR) using radar sensors enables intuitive, contact-free human–computer interaction. However, real-world deployment is hindered by data loss (DL) induced by interference from nearby radars and environmental obstructions. To address this challenge, we propose a deep learning-based sequence modeling framework that is robust to missing or corrupted data. The system employs an encoder–decoder network to reconstruct clean latent representations from impaired inputs, followed by a scale-shift module that aligns features with gesture categories for accurate classification. Experimental results demonstrate strong resilience, maintaining stable performance with up to 35% DL. Under 20% DL, the system achieves 98.50% recognition accuracy. To evaluate generalization, we tested the model on a separate dataset collected in a new environment with an unseen user and real interference from one or two additional mmWave radars. These corrupted samples were used exclusively for testing, while DL was simulated during training. The proposed system maintained 96.61% accuracy under these adverse conditions, confirming its robustness and reliability in practical, data-degraded scenarios.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 20","pages":"30682-30691"},"PeriodicalIF":4.5,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149176176","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 : 2026-10-15Epub Date: 2026-09-02DOI: 10.1109/JSEN.2026.3727594
Sanxi Wu;Hongjia Liu;Yuanyuan Li;Guoqiang Liu;Jing Liu
Electrical impedance tomography (EIT) is a nonradiant, noninvasive and low-cost imaging technique. It has great application prospects in medical imaging and industrial process monitoring. Despite its advantages, the challenges of soft field effect and ill-posedness of the inverse problem make image reconstruction difficult, which has limited the development of EIT. Imaging algorithm plays an important role in the EIT imaging process. Generally, Sensitivity Coefficient (SC) algorithm based on the SC matrix (SCM) and linear back-projection (LBP) algorithm based on the back-projection matrix (BPM) are two of the most widely used real-time image reconstruction methods. However, SC is limited by the ill-conditioning of the SCM and low sensitivity in the central region, while LBP suffers from star-shaped artifacts and neglects the attenuation along projection paths. In this article, a novel method is proposed named the back-projection–SC Fusion (BSCF), which forms a novel SCM by fusing traditional SCM and BPM. This method significantly reduces the condition number of the SCM, alleviates ill-posedness of the inverse problem, enhances the sensitivity in the central region and improves the representation of spatially varying contributions along the projection paths. Evaluations including singular value analysis, condition number and uniformity index demonstrate that the BSCF matrix exhibits superior mathematical properties. Numerical simulations and experiments comparing SC, LBP, weighted LBP (WLBP), one-step Landweber and BSCF demonstrate that BSCF generally achieves lower relative error (RE) and higher correlation coefficient (CC), together with more accurate reconstruction of object size, shape and position, particularly for central and multiple objects. It also exhibits the lowest average online computational time of 0.210 ms and maintains stable performance at signal-to-noise ratios (SNRs) of 15 and 10 dB. Overall, BSCF provides a favorable balance among reconstruction accuracy, computational efficiency, and noise robustness, showing strong potential for real-time EIT imaging applications.
{"title":"A Reconstruction Algorithm for EIT Based on the Back-Projection-Sensitivity Coefficient Fusion","authors":"Sanxi Wu;Hongjia Liu;Yuanyuan Li;Guoqiang Liu;Jing Liu","doi":"10.1109/JSEN.2026.3727594","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3727594","url":null,"abstract":"Electrical impedance tomography (EIT) is a nonradiant, noninvasive and low-cost imaging technique. It has great application prospects in medical imaging and industrial process monitoring. Despite its advantages, the challenges of soft field effect and ill-posedness of the inverse problem make image reconstruction difficult, which has limited the development of EIT. Imaging algorithm plays an important role in the EIT imaging process. Generally, Sensitivity Coefficient (SC) algorithm based on the SC matrix (SCM) and linear back-projection (LBP) algorithm based on the back-projection matrix (BPM) are two of the most widely used real-time image reconstruction methods. However, SC is limited by the ill-conditioning of the SCM and low sensitivity in the central region, while LBP suffers from star-shaped artifacts and neglects the attenuation along projection paths. In this article, a novel method is proposed named the back-projection–SC Fusion (BSCF), which forms a novel SCM by fusing traditional SCM and BPM. This method significantly reduces the condition number of the SCM, alleviates ill-posedness of the inverse problem, enhances the sensitivity in the central region and improves the representation of spatially varying contributions along the projection paths. Evaluations including singular value analysis, condition number and uniformity index demonstrate that the BSCF matrix exhibits superior mathematical properties. Numerical simulations and experiments comparing SC, LBP, weighted LBP (WLBP), one-step Landweber and BSCF demonstrate that BSCF generally achieves lower relative error (RE) and higher correlation coefficient (CC), together with more accurate reconstruction of object size, shape and position, particularly for central and multiple objects. It also exhibits the lowest average online computational time of 0.210 ms and maintains stable performance at signal-to-noise ratios (SNRs) of 15 and 10 dB. Overall, BSCF provides a favorable balance among reconstruction accuracy, computational efficiency, and noise robustness, showing strong potential for real-time EIT imaging applications.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 20","pages":"30556-30567"},"PeriodicalIF":4.5,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149176211","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 : 2026-10-15Epub Date: 2026-09-15DOI: 10.1109/JSEN.2026.3731196
Fan Shen;Yongfa Chen;Xinzhou Xu;Ziqian Li;Zhengyu Wang;Franz Pernkopf;Björn W. Schuller
Minimally invasive flexible cable-driven surgical robots usually benefit from lower inertia, compact design, and remote actuation. Among the cable-driven surgical robots, the ones with continuum joints can adapt to complex cases through a high degree of dexterity and pliability. Nevertheless, this kind of robot poses challenges to accurate estimation of the joints’ motion, mainly due to the flexible deformation ability and the influence of uncertain cable extension, diverse surgical instruments, and collisions during surgery. Fortunately, the challenges can be addressed through learning on collected data, yet conventional data-driven methods fail to sufficiently consider the correlation between multiple estimation sources. To this end, we propose a data-driven approach of a multibranch coattention recurrent network (MCRN) for estimating the motion of a cable-driven surgical-robotic continuum joint, comprising a parallel 1-D-convolutional module, a multibranch coattention module, and a recurrent module. These three modules aim to achieve local description, cross-source fusion, and temporal description, respectively, for motion estimation based on multiple sources of input control signals and the force and torque series of the joint’s linkage. We perform experiments on the cable-driven continuum-joint motion estimation (CD-CJME) dataset, with the results showing that the proposed approach achieves better performance compared with conventional data-driven strategies for sequential-data modeling using multiple estimation sources.
{"title":"Motion Estimation for Cable-Driven Surgical-Robotic Continuum Joints Using a Multibranch Coattention Recurrent Network","authors":"Fan Shen;Yongfa Chen;Xinzhou Xu;Ziqian Li;Zhengyu Wang;Franz Pernkopf;Björn W. Schuller","doi":"10.1109/JSEN.2026.3731196","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3731196","url":null,"abstract":"Minimally invasive flexible cable-driven surgical robots usually benefit from lower inertia, compact design, and remote actuation. Among the cable-driven surgical robots, the ones with continuum joints can adapt to complex cases through a high degree of dexterity and pliability. Nevertheless, this kind of robot poses challenges to accurate estimation of the joints’ motion, mainly due to the flexible deformation ability and the influence of uncertain cable extension, diverse surgical instruments, and collisions during surgery. Fortunately, the challenges can be addressed through learning on collected data, yet conventional data-driven methods fail to sufficiently consider the correlation between multiple estimation sources. To this end, we propose a data-driven approach of a multibranch coattention recurrent network (MCRN) for estimating the motion of a cable-driven surgical-robotic continuum joint, comprising a parallel 1-D-convolutional module, a multibranch coattention module, and a recurrent module. These three modules aim to achieve local description, cross-source fusion, and temporal description, respectively, for motion estimation based on multiple sources of input control signals and the force and torque series of the joint’s linkage. We perform experiments on the cable-driven continuum-joint motion estimation (CD-CJME) dataset, with the results showing that the proposed approach achieves better performance compared with conventional data-driven strategies for sequential-data modeling using multiple estimation sources.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 20","pages":"31195-31206"},"PeriodicalIF":4.5,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149176244","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 : 2026-10-15Epub Date: 2026-09-11DOI: 10.1109/JSEN.2026.3731116
Cole J. Dorman;Dillon C. Kiernan;Joe Miller;Jay Trojan;George Hsu;Mark B. Moldwin
Accurate magnetic field measurements from the PNI RM3100 magnetometer, a commercial magneto-inductive (MI) sensor, can be impacted by temperature-dependent behavior that introduces systematic error. This work characterizes the thermal sawtooth gain observed in the RM3100 under controlled thermal conditions, identifies the physical origin of the signature, and proposes both ground-calibration and hardware mitigation strategies. Experimental results show the sawtooth is driven solely by relative temperature change, independent of the rate of change of temperature, and exhibits a repeatable signature that remains invariant for a given set of measurement parameters. The signature is shown to arise from quantization error between the magnetic sensing oscillation mechanism and the internal counter clock. This relationship is validated through simulation, and mitigation approaches are demonstrated by increasing the internal counter clock frequency.
{"title":"Identification and Removal of Thermal Sawtooth Gain in the PNI RM3100","authors":"Cole J. Dorman;Dillon C. Kiernan;Joe Miller;Jay Trojan;George Hsu;Mark B. Moldwin","doi":"10.1109/JSEN.2026.3731116","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3731116","url":null,"abstract":"Accurate magnetic field measurements from the PNI RM3100 magnetometer, a commercial magneto-inductive (MI) sensor, can be impacted by temperature-dependent behavior that introduces systematic error. This work characterizes the thermal sawtooth gain observed in the RM3100 under controlled thermal conditions, identifies the physical origin of the signature, and proposes both ground-calibration and hardware mitigation strategies. Experimental results show the sawtooth is driven solely by relative temperature change, independent of the rate of change of temperature, and exhibits a repeatable signature that remains invariant for a given set of measurement parameters. The signature is shown to arise from quantization error between the magnetic sensing oscillation mechanism and the internal counter clock. This relationship is validated through simulation, and mitigation approaches are demonstrated by increasing the internal counter clock frequency.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 20","pages":"30293-30302"},"PeriodicalIF":4.5,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11689665","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149176316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-10-15Epub Date: 2026-09-04DOI: 10.1109/JSEN.2026.3729045
Zexin Long;Qi Yang;Xuejing Liu;Yang Li
Atomic magnetometers serve as crucial high-precision measurement instruments in the field of weak magnetic field detection. Alkali metal vapor cells are the core optical components inside atomic magnetometers, and accurate characterization of the internal thermal field of vapor cells is essential for performance evaluation and thermal design optimization of magnetometers. To address the limitation that traditional temperature measurement methods fail to reflect the actual gas temperature inside vapor cells, this article proposes a noncontact temperature measurement method based on infrared radiation for 2-D temperature field measurement inside alkali metal vapor cells. When pumped by a 795 nm laser, the vapor cell heated to the operating temperature emits infrared radiation in all directions. This study establishes an equation model correlating the infrared radiation generated along the laser incident direction and its orthogonal direction with the 2-D planar temperature distribution inside the vapor cell. We subdivide the target 2-D plane into discrete temperature units and adopt the algebraic reconstruction technique (ART) to invert local temperature distributions. Experiments were performed on a cubic rubidium (Rb) vapor cell with a side length of 20 mm. The results reveal that after interference elimination, the radiation intensity emitted by each temperature unit presents a linear correlation with the fourth power of its temperature. Under unilateral bottom heating conditions, the internal 2-D temperature field distribution inside the vapor cell can be successfully reconstructed. Within the temperature range of 353–383 K, the target 2-D temperature plane is divided into $20~times ~20$ temperature units. The minimum temperature deviation between the reconstructed distributions and atomic absorption spectroscopy (AAS) verification data was 1.02 K, with a spatial resolution of 1 mm. The proposed method effectively reduces the measurement error of infrared radiation thermometry, providing a novel approach for 2-D temperature field characterization and thermal optimization design of alkali metal vapor cells.
{"title":"Tomographic Temperature Reconstruction Inside Alkali Metal Vapor Cells Based on Infrared Radiation","authors":"Zexin Long;Qi Yang;Xuejing Liu;Yang Li","doi":"10.1109/JSEN.2026.3729045","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3729045","url":null,"abstract":"Atomic magnetometers serve as crucial high-precision measurement instruments in the field of weak magnetic field detection. Alkali metal vapor cells are the core optical components inside atomic magnetometers, and accurate characterization of the internal thermal field of vapor cells is essential for performance evaluation and thermal design optimization of magnetometers. To address the limitation that traditional temperature measurement methods fail to reflect the actual gas temperature inside vapor cells, this article proposes a noncontact temperature measurement method based on infrared radiation for 2-D temperature field measurement inside alkali metal vapor cells. When pumped by a 795 nm laser, the vapor cell heated to the operating temperature emits infrared radiation in all directions. This study establishes an equation model correlating the infrared radiation generated along the laser incident direction and its orthogonal direction with the 2-D planar temperature distribution inside the vapor cell. We subdivide the target 2-D plane into discrete temperature units and adopt the algebraic reconstruction technique (ART) to invert local temperature distributions. Experiments were performed on a cubic rubidium (Rb) vapor cell with a side length of 20 mm. The results reveal that after interference elimination, the radiation intensity emitted by each temperature unit presents a linear correlation with the fourth power of its temperature. Under unilateral bottom heating conditions, the internal 2-D temperature field distribution inside the vapor cell can be successfully reconstructed. Within the temperature range of 353–383 K, the target 2-D temperature plane is divided into <inline-formula> <tex-math>$20~times ~20$ </tex-math></inline-formula> temperature units. The minimum temperature deviation between the reconstructed distributions and atomic absorption spectroscopy (AAS) verification data was 1.02 K, with a spatial resolution of 1 mm. The proposed method effectively reduces the measurement error of infrared radiation thermometry, providing a novel approach for 2-D temperature field characterization and thermal optimization design of alkali metal vapor cells.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 20","pages":"31403-31412"},"PeriodicalIF":4.5,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149175974","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 : 2026-10-15Epub Date: 2026-09-01DOI: 10.1109/JSEN.2026.3727809
J. F. Alves
Thermoformed piezoelectret transducers (TPTs) have emerged as low-cost polymer-based acoustic sensors for partial discharge (PD) monitoring in high-voltage insulation systems. Although previous studies have demonstrated their feasibility under laboratory and field conditions, the available literature remains fragmented across material design, sensing mechanisms, experimental validation, technology comparison, and calibration. This review consolidates and critically assesses these aspects by examining the microstructured polymer architecture and electromechanical response of TPTs, as well as the influence of acoustic propagation, structural coupling, sensor dynamics, analog conditioning, and signal processing on the recorded waveform. The progression of experimental evidence is analyzed from controlled air-gap arrangements to oil-immersed transformers, energized equipment, comparisons with commercial acoustic-emission sensors, and acoustic-electrical calibration. The TPTs are also assessed in relation to conventional electrical, high-frequency current transformer, ultrahigh-frequency, piezoceramic acoustic-emission, and fiber-optic sensing technologies. The reviewed studies show that TPTs can detect PD-related acoustic activity and exhibit strong agreement with reference sensors under controlled conditions. However, acoustic amplitude cannot be universally converted into apparent charge because the measurement depends on defect type, geometry, propagation medium, sensor position, coupling conditions, frequency response, acquisition chain, and calibration procedure. Based on this analysis, a physically grounded and metrologically constrained framework is proposed for interpreting TPT measurements. The TPTs are identified as promising candidates for scalable and cost-sensitive acoustic monitoring, particularly in hybrid and distributed sensing systems, provided that calibration domains, uncertainty sources, long-term stability, and transferability limits are explicitly established.
{"title":"Sensing Principles, Calibration, and Comparative Assessment of Thermoformed Piezoelectret Acoustic Sensor Technology for Partial Discharge Monitoring: A Review","authors":"J. F. Alves","doi":"10.1109/JSEN.2026.3727809","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3727809","url":null,"abstract":"Thermoformed piezoelectret transducers (TPTs) have emerged as low-cost polymer-based acoustic sensors for partial discharge (PD) monitoring in high-voltage insulation systems. Although previous studies have demonstrated their feasibility under laboratory and field conditions, the available literature remains fragmented across material design, sensing mechanisms, experimental validation, technology comparison, and calibration. This review consolidates and critically assesses these aspects by examining the microstructured polymer architecture and electromechanical response of TPTs, as well as the influence of acoustic propagation, structural coupling, sensor dynamics, analog conditioning, and signal processing on the recorded waveform. The progression of experimental evidence is analyzed from controlled air-gap arrangements to oil-immersed transformers, energized equipment, comparisons with commercial acoustic-emission sensors, and acoustic-electrical calibration. The TPTs are also assessed in relation to conventional electrical, high-frequency current transformer, ultrahigh-frequency, piezoceramic acoustic-emission, and fiber-optic sensing technologies. The reviewed studies show that TPTs can detect PD-related acoustic activity and exhibit strong agreement with reference sensors under controlled conditions. However, acoustic amplitude cannot be universally converted into apparent charge because the measurement depends on defect type, geometry, propagation medium, sensor position, coupling conditions, frequency response, acquisition chain, and calibration procedure. Based on this analysis, a physically grounded and metrologically constrained framework is proposed for interpreting TPT measurements. The TPTs are identified as promising candidates for scalable and cost-sensitive acoustic monitoring, particularly in hybrid and distributed sensing systems, provided that calibration domains, uncertainty sources, long-term stability, and transferability limits are explicitly established.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 20","pages":"29972-29979"},"PeriodicalIF":4.5,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149175995","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}
To address the susceptibility of 2-D membrane nanoelectromechanical system (NEMS) resonant gas sensors to temperature drift, this study proposes a trace-gas sensing mechanism based on a pressure-tuned circular MoS2 membrane resonator. The gas pressure is utilized to regulate the central deflection and prestress state of the MoS2 membrane. The negative temperature coefficient induced by the initial prestrain is counterbalanced by the positive temperature coefficient arising from large-deflection nonlinear stiffness, thereby enabling near-zero-temperature-drift operation at a target temperature. A pressure–deflection–effective stiffness and effective mass–resonant frequency theoretical model is established and numerically examined by finite-element simulation. The results demonstrate that the pressure difference can continuously tune the temperature coefficient of the resonant frequency and generate a near-zero-drift point at a specific pressure. Taking the adsorption of trace nitrogen dioxide (NO${}_{{2}}$ ) gas as a case study, we theoretically evaluated the sensing response of the sensing mechanism in combination with theoretical simulations. The results show that compared with the no-pressure-tuning reference groups, the temperature drifts of the two groups with different initial tensions were reduced by 98.87% and 99.43%, respectively. The signal-to-temperature-interference ratios (STIRs) under the designed pressure were 3.77 and 14.97, respectively. These results suggest that the gas-induced frequency shifts can be distinguished from the residual temperature-induced interference under constant-pressure or actively regulated pressure conditions. The proposed pressure tuning scheme does not require thermostatic control or DC gate voltage compensation. It provides a new design strategy for low-power and high-stability 2-D material-based NEMS gas sensors.
{"title":"Pressure-Tuned Near-Zero-Temperature-Drift Mechanism for MoS2 2-D NEMS Resonant Trace-Gas Sensors","authors":"Xu Jin;Yan Li;Han Zhang;Zhujie Zhao;Lijia Zhang;Liang He;Dong F. Wang;Dan Ma;Cao Xia","doi":"10.1109/JSEN.2026.3727275","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3727275","url":null,"abstract":"To address the susceptibility of 2-D membrane nanoelectromechanical system (NEMS) resonant gas sensors to temperature drift, this study proposes a trace-gas sensing mechanism based on a pressure-tuned circular MoS<sub>2</sub> membrane resonator. The gas pressure is utilized to regulate the central deflection and prestress state of the MoS<sub>2</sub> membrane. The negative temperature coefficient induced by the initial prestrain is counterbalanced by the positive temperature coefficient arising from large-deflection nonlinear stiffness, thereby enabling near-zero-temperature-drift operation at a target temperature. A pressure–deflection–effective stiffness and effective mass–resonant frequency theoretical model is established and numerically examined by finite-element simulation. The results demonstrate that the pressure difference can continuously tune the temperature coefficient of the resonant frequency and generate a near-zero-drift point at a specific pressure. Taking the adsorption of trace nitrogen dioxide (NO<inline-formula> <tex-math>${}_{{2}}$ </tex-math></inline-formula>) gas as a case study, we theoretically evaluated the sensing response of the sensing mechanism in combination with theoretical simulations. The results show that compared with the no-pressure-tuning reference groups, the temperature drifts of the two groups with different initial tensions were reduced by 98.87% and 99.43%, respectively. The signal-to-temperature-interference ratios (STIRs) under the designed pressure were 3.77 and 14.97, respectively. These results suggest that the gas-induced frequency shifts can be distinguished from the residual temperature-induced interference under constant-pressure or actively regulated pressure conditions. The proposed pressure tuning scheme does not require thermostatic control or DC gate voltage compensation. It provides a new design strategy for low-power and high-stability 2-D material-based NEMS gas sensors.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 20","pages":"30164-30172"},"PeriodicalIF":4.5,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149176002","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 : 2026-10-15Epub Date: 2026-09-10DOI: 10.1109/JSEN.2026.3730668
Elham Alaei;Syed Ali Raza Bukhari;Tanzila Afrin;Laura Wells;Robert Campbell;Yongjun Lai
Monitoring continuous intraocular pressure (IOP) is essential for the diagnosis and management of glaucoma; however, current microfluidic sensing techniques lack design optimization and leave substantial room for improvement. In this study, we present a highly sensitive microfluidic contact lens designed to transform intraocular deformation into measurable fluid displacement. The device incorporates a wide reservoir channel, coupled to a narrow indicator channel, enabling amplified displacement, while an integrated air reservoir improves the overall sensitivity. The lens is fabricated using Ecoflex-0030, a soft and biocompatible elastomer with a low Young’s modulus whose strain responsiveness surpasses conventional polydimethylsiloxane (PDMS)-based microfluidic contact lenses. Experimental evaluations using a synthetic eye model demonstrate the highest displacement sensitivity reported to date for microfluidic contact lens sensors, with consistent performance validated through repeated trials and cyclic pressure testing. To further improve device performance, a comprehensive microchannel-location study was conducted that revealed strongly nonuniform strain distributions across the corneal surface. Four lens designs with varying microchannel locations were fabricated and extensively tested to obtain the ideal location for microchannel placement. The sensitivity characterization revealed substantial variation across the different channel locations, with values of 0.5057,1.032, 0.775, and 0.614 mm/mmHg observed for the designs D6, D7, D8, and D9 (at 6, 7, 8, and 9 mm diameter), respectively. The final optimized layout of D7 produced a superior response, reaching 1.032 mm/mmHg, which surpasses previously reported performance in microfluidic contact lenses. These findings demonstrate the importance of mechanical coupling and structural optimization to obtain a highly sensitive and reliable sensor.
{"title":"A Microfluidic Contact Lens With Optimized Channel Placement for Enhanced Sensitivity for Continuous Intraocular Pressure Monitoring","authors":"Elham Alaei;Syed Ali Raza Bukhari;Tanzila Afrin;Laura Wells;Robert Campbell;Yongjun Lai","doi":"10.1109/JSEN.2026.3730668","DOIUrl":"https://doi.org/10.1109/JSEN.2026.3730668","url":null,"abstract":"Monitoring continuous intraocular pressure (IOP) is essential for the diagnosis and management of glaucoma; however, current microfluidic sensing techniques lack design optimization and leave substantial room for improvement. In this study, we present a highly sensitive microfluidic contact lens designed to transform intraocular deformation into measurable fluid displacement. The device incorporates a wide reservoir channel, coupled to a narrow indicator channel, enabling amplified displacement, while an integrated air reservoir improves the overall sensitivity. The lens is fabricated using Ecoflex-0030, a soft and biocompatible elastomer with a low Young’s modulus whose strain responsiveness surpasses conventional polydimethylsiloxane (PDMS)-based microfluidic contact lenses. Experimental evaluations using a synthetic eye model demonstrate the highest displacement sensitivity reported to date for microfluidic contact lens sensors, with consistent performance validated through repeated trials and cyclic pressure testing. To further improve device performance, a comprehensive microchannel-location study was conducted that revealed strongly nonuniform strain distributions across the corneal surface. Four lens designs with varying microchannel locations were fabricated and extensively tested to obtain the ideal location for microchannel placement. The sensitivity characterization revealed substantial variation across the different channel locations, with values of 0.5057,1.032, 0.775, and 0.614 mm/mmHg observed for the designs D6, D7, D8, and D9 (at 6, 7, 8, and 9 mm diameter), respectively. The final optimized layout of D7 produced a superior response, reaching 1.032 mm/mmHg, which surpasses previously reported performance in microfluidic contact lenses. These findings demonstrate the importance of mechanical coupling and structural optimization to obtain a highly sensitive and reliable sensor.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"26 20","pages":"30229-30237"},"PeriodicalIF":4.5,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149176003","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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