Pub Date : 2025-12-16DOI: 10.1016/j.sna.2025.117407
Hakan Altuntaş , Mehmet Selçuk Arslan
Accurate temperature control is essential in domestic induction cooktops for energy efficiency and cooking performance. One of the most suitable ways to measure temperature within the domestic induction cooktops is by using non-contact temperature measurement techniques like infrared (IR) temperature sensors. A key challenge in non-contact IR temperature measurement is the reliance on the emissivity of the object, which can lead to significant errors when emissivity is unknown or variable. The emissivity of cooking vessel is influenced by surface properties, and its color, making precise measurement challenging. In this study, we developed an advanced sensor system capable of identifying the surface properties of cooking vessels, including color, allowing for the estimation of emissivity. This system enables accurate temperature measurement by adjusting the IR sensor’s readings based on the cooking vessel’s emissivity. The proposed method improves the accuracy of temperature measurement in domestic induction cooktops, leading to better temperature control and enhanced cooking results.
{"title":"Real-time emissivity estimation using a smart sensor system for infrared temperature measurement","authors":"Hakan Altuntaş , Mehmet Selçuk Arslan","doi":"10.1016/j.sna.2025.117407","DOIUrl":"10.1016/j.sna.2025.117407","url":null,"abstract":"<div><div>Accurate temperature control is essential in domestic induction cooktops for energy efficiency and cooking performance. One of the most suitable ways to measure temperature within the domestic induction cooktops is by using non-contact temperature measurement techniques like infrared (IR) temperature sensors. A key challenge in non-contact IR temperature measurement is the reliance on the emissivity of the object, which can lead to significant errors when emissivity is unknown or variable. The emissivity of cooking vessel is influenced by surface properties, and its color, making precise measurement challenging. In this study, we developed an advanced sensor system capable of identifying the surface properties of cooking vessels, including color, allowing for the estimation of emissivity. This system enables accurate temperature measurement by adjusting the IR sensor’s readings based on the cooking vessel’s emissivity. The proposed method improves the accuracy of temperature measurement in domestic induction cooktops, leading to better temperature control and enhanced cooking results.</div></div>","PeriodicalId":21689,"journal":{"name":"Sensors and Actuators A-physical","volume":"399 ","pages":"Article 117407"},"PeriodicalIF":4.9,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791575","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 : 2025-12-16DOI: 10.1016/j.sna.2025.117412
Wei Chen , Xiuchuan Jing , Zhuang Li , Yongxi Ma , Hongda Gu , Haiqing Miao , Zhong Wang , Guohe Wang
Attaching flexible resistive strain sensors to human skin enables response detection of behaviours towards real-time physiological monitoring. However, current flexible resistive strain sensors hinder themselves from practical applications due to their low sensitivity, small linear working range, and poor wearing comfort. In this research, a conductive thermoplastic polyurethane (TPU) membrane is fabricated using TEMPO modified nanocellulose (TNC) decorated with carbon quantum dots (CQDs) to prepare flexible highly sensitive, and breathable strain sensors. Results show that the mechanical property and strain response range of the TPU membrane is significantly enhanced by CQDs-TNC. The TPU membrane also exhibits the highest sensitivity (GF= 49.4 in the 30∼80 % strain range) and a wide response range (0–80 %). At 5 %wt of CQDs-TNC, the membrane displays the highest elongation at break (389.8 %) with maximum breaking stress approaching 9.7 MPa. The CQDs-TNC/TPU membrane exhibits fast response and recovery times (85 ms and 93 ms), low hysteresis (8.9 %), and excellent dynamic cyclic strain performance (1000 stretch/release cycles). The CQDs/TMC/TPU-resistive strain sensor (CTT-RSS) sensor well conforms to human joints, and accurately produces real-time regular resistance strain responses based on human movements. In all, this study contributes a novel research design for fabricating flexible and sensitive sensor to the development of smart textiles.
{"title":"Fabrication of flexible and sensitive resistance strain sensor by flexible TPU decorated with CQDs/TNC composite","authors":"Wei Chen , Xiuchuan Jing , Zhuang Li , Yongxi Ma , Hongda Gu , Haiqing Miao , Zhong Wang , Guohe Wang","doi":"10.1016/j.sna.2025.117412","DOIUrl":"10.1016/j.sna.2025.117412","url":null,"abstract":"<div><div>Attaching flexible resistive strain sensors to human skin enables response detection of behaviours towards real-time physiological monitoring. However, current flexible resistive strain sensors hinder themselves from practical applications due to their low sensitivity, small linear working range, and poor wearing comfort. In this research, a conductive thermoplastic polyurethane (TPU) membrane is fabricated using TEMPO modified nanocellulose (TNC) decorated with carbon quantum dots (CQDs) to prepare flexible highly sensitive, and breathable strain sensors. Results show that the mechanical property and strain response range of the TPU membrane is significantly enhanced by CQDs-TNC. The TPU membrane also exhibits the highest sensitivity (GF= 49.4 in the 30∼80 % strain range) and a wide response range (0–80 %). At 5 %wt of CQDs-TNC, the membrane displays the highest elongation at break (389.8 %) with maximum breaking stress approaching 9.7 MPa. The CQDs-TNC/TPU membrane exhibits fast response and recovery times (85 ms and 93 ms), low hysteresis (8.9 %), and excellent dynamic cyclic strain performance (1000 stretch/release cycles). The CQDs/TMC/TPU-resistive strain sensor (CTT-RSS) sensor well conforms to human joints, and accurately produces real-time regular resistance strain responses based on human movements. In all, this study contributes a novel research design for fabricating flexible and sensitive sensor to the development of smart textiles.</div></div>","PeriodicalId":21689,"journal":{"name":"Sensors and Actuators A-physical","volume":"399 ","pages":"Article 117412"},"PeriodicalIF":4.9,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791674","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 : 2025-12-16DOI: 10.1016/j.sna.2025.117405
Jianhua Wang , Shenhua Zhang , Yanxi Yang
In fringe projection profilometry (FPP), the captured fringes on highlight surface are often saturated. Traditional high dynamic range (HDR) methods require additional fringe projection or hardware assistance. In this paper, a hybrid network architecture that combines improved U-Net and generative adversarial networks (GAN) is proposed for saturation fringe self restoration without any assistance. Firstly, the encoder does not use pooling layer for downsampling, but instead achieves downsampling by increasing the stride of the convolutional layer from 1 to 2, which avoids the loss of detailed features caused by pooling processing. 4 × 4 convolution kernel increases the receptive field compared to U-Net's 3 × 3 convolution kernel. Secondly, the improved U-Net adopts asymmetric skip connection, which allows the decoder to gradually transition from higher-level abstract features to lower level detail features by utilizing the features of different layers of the encoder when restoring the image. Finally, the adversarial learning mechanism in GAN is adopted to optimize the performance of the generator and discriminator. The generator is responsible for generating more realistic images, while the discriminator is responsible for verifying whether the image is generated by the generator. In the process of mutual game, the ability to generate real images and the ability to discern are continuously improved until they reach a Nash equilibrium. The experimental results show that the fringe PSNR of the proposed GAN-U-Net has been significantly improved compared to that of U-Net, while the absolute phase RMSE is reduced by approximately 10.91 % −64.15 %.
{"title":"Deep learning-based high dynamic range 3D measurement: The combination of GAN and U-Net","authors":"Jianhua Wang , Shenhua Zhang , Yanxi Yang","doi":"10.1016/j.sna.2025.117405","DOIUrl":"10.1016/j.sna.2025.117405","url":null,"abstract":"<div><div>In fringe projection profilometry (FPP), the captured fringes on highlight surface are often saturated. Traditional high dynamic range (HDR) methods require additional fringe projection or hardware assistance. In this paper, a hybrid network architecture that combines improved U-Net and generative adversarial networks (GAN) is proposed for saturation fringe self restoration without any assistance. Firstly, the encoder does not use pooling layer for downsampling, but instead achieves downsampling by increasing the stride of the convolutional layer from 1 to 2, which avoids the loss of detailed features caused by pooling processing. 4 × 4 convolution kernel increases the receptive field compared to U-Net's 3 × 3 convolution kernel. Secondly, the improved U-Net adopts asymmetric skip connection, which allows the decoder to gradually transition from higher-level abstract features to lower level detail features by utilizing the features of different layers of the encoder when restoring the image. Finally, the adversarial learning mechanism in GAN is adopted to optimize the performance of the generator and discriminator. The generator is responsible for generating more realistic images, while the discriminator is responsible for verifying whether the image is generated by the generator. In the process of mutual game, the ability to generate real images and the ability to discern are continuously improved until they reach a Nash equilibrium. The experimental results show that the fringe PSNR of the proposed GAN-U-Net has been significantly improved compared to that of U-Net, while the absolute phase RMSE is reduced by approximately 10.91 % −64.15 %.</div></div>","PeriodicalId":21689,"journal":{"name":"Sensors and Actuators A-physical","volume":"399 ","pages":"Article 117405"},"PeriodicalIF":4.9,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791756","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 : 2025-12-16DOI: 10.1016/j.sna.2025.117401
Thomas Schweizer , Kapil Tagale , Henrik Nöbel , Andreas Schander , Michael J. Vellekoop
Controlled opening of sealed microsensors is crucial for their correct functioning. Often, sensors need to be protected from the environment until they are deployed. This could be against humidity, harmful gases or biological contamination. Fragments of the sealing membrane are not wanted on the sensing element after actuation and the seal should be removed completely. In this work, a method to utilize micro-machined silicon nitride membranes for this purpose is described. With an electric current, heaters on the membrane can induce thermal stress and break the sealing. A novel way to hold the splinters together with the help of a structured Parylene-C layer has been implemented. To fully expose the sensor area, bi-layered membranes have been investigated to exploit the self-roll-up effect caused by different intrinsic stress levels in the layers of the sealing membrane. Different variations of membrane composition have been fabricated and compared. To optimize the opening process, various designs for the metal electrodes have been designed, simulated and successfully tested.
{"title":"Optimization of the opening mechanism for micromachined sealings with a sacrificial multi-layer-membrane and thermoelectric actuation","authors":"Thomas Schweizer , Kapil Tagale , Henrik Nöbel , Andreas Schander , Michael J. Vellekoop","doi":"10.1016/j.sna.2025.117401","DOIUrl":"10.1016/j.sna.2025.117401","url":null,"abstract":"<div><div>Controlled opening of sealed microsensors is crucial for their correct functioning. Often, sensors need to be protected from the environment until they are deployed. This could be against humidity, harmful gases or biological contamination. Fragments of the sealing membrane are not wanted on the sensing element after actuation and the seal should be removed completely. In this work, a method to utilize micro-machined silicon nitride membranes for this purpose is described. With an electric current, heaters on the membrane can induce thermal stress and break the sealing. A novel way to hold the splinters together with the help of a structured Parylene-C layer has been implemented. To fully expose the sensor area, bi-layered membranes have been investigated to exploit the self-roll-up effect caused by different intrinsic stress levels in the layers of the sealing membrane. Different variations of membrane composition have been fabricated and compared. To optimize the opening process, various designs for the metal electrodes have been designed, simulated and successfully tested.</div></div>","PeriodicalId":21689,"journal":{"name":"Sensors and Actuators A-physical","volume":"399 ","pages":"Article 117401"},"PeriodicalIF":4.9,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791576","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}
This study designed a novel high-efficiency air-coupled ultrasonic transducer based on a modified 1–3–2 piezoelectric composite with an epoxy/hollow glass microsphere filler system. Theoretical modeling was employed to investigate the effects of ceramic volume fraction under different substrate thicknesses on the acoustic performance of the 1–3–2 piezoelectric composite. The fabricated composite demonstrated measured parameters of 0.7 for electromechanical coupling factor and 14.05 MRayl for acoustic impedance, showing good agreement with theoretical predictions. Subsequently, a simulation model of the 1–3–2 air-coupled ultrasonic transducer was established based on the Leach model and transmission line theory. Comparative analysis revealed that the double-layer matching design enhanced the detection signal amplitude by approximately 123.2 % compared to single-layer matching, thereby determining the optimal matching layer parameters. Finally, the developed transducer exhibited superior defect detection capability in comparative tests with commercial Japanese probes.
{"title":"Design and fabrication of a new air-coupled ultrasonic transducer based on 1–3-2 piezoelectric composite filled with epoxy resin/hollow glass microsphere polymer","authors":"Jinjie Zhou , Ziliang Jia , Pengfei Zhou , Qiyun Liu","doi":"10.1016/j.sna.2025.117387","DOIUrl":"10.1016/j.sna.2025.117387","url":null,"abstract":"<div><div>This study designed a novel high-efficiency air-coupled ultrasonic transducer based on a modified 1–3–2 piezoelectric composite with an epoxy/hollow glass microsphere filler system. Theoretical modeling was employed to investigate the effects of ceramic volume fraction under different substrate thicknesses on the acoustic performance of the 1–3–2 piezoelectric composite. The fabricated composite demonstrated measured parameters of 0.7 for electromechanical coupling factor and 14.05 MRayl for acoustic impedance, showing good agreement with theoretical predictions. Subsequently, a simulation model of the 1–3–2 air-coupled ultrasonic transducer was established based on the Leach model and transmission line theory. Comparative analysis revealed that the double-layer matching design enhanced the detection signal amplitude by approximately 123.2 % compared to single-layer matching, thereby determining the optimal matching layer parameters. Finally, the developed transducer exhibited superior defect detection capability in comparative tests with commercial Japanese probes.</div></div>","PeriodicalId":21689,"journal":{"name":"Sensors and Actuators A-physical","volume":"399 ","pages":"Article 117387"},"PeriodicalIF":4.9,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791580","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 : 2025-12-15DOI: 10.1016/j.sna.2025.117406
Ziyi An, Sihang Lv, Jiaqi Wang, Wendong Zhang, Lijiao Zu, Shi Qiu, Wa Jin, Xinghu Fu
A composite multi-parameter fiber sensor based on the Vernier effect was designed and fabricated for simultaneous axial strain and curvature measurement. The sensor integrates a Fabry-Perot interferometer (FPI) and a multimode interferometer (MMI), each constructed using hollow core fiber (HCF) with differing core diameters. The FPI uses an HCF with a larger core diameter, while the MMI is formed by cascading an HCF with a smaller core diameter to an HCF with a larger core diameter. Due to their distinct sensing mechanisms, the two interferometers respond differently, enabling simultaneous detection of axial strain and curvature. Experimental results indicate axial strain and curvature sensitivities of 2.94 pm/µε and 8.53 nm/m⁻¹ respectively, when the MMI is used as the sensing element. When the FPI is used as the sensing element, the strain sensitivity is enhanced to −4.38 pm/µɛ, and the curvature sensitivity is −5.61 nm/m⁻¹ . This sensor provides a novel tool for multi-dimensional parameter collection in intelligent control systems.
{"title":"Composite multi-parameter sensor based on hollow core fiber for measuring the axial strain and curvature","authors":"Ziyi An, Sihang Lv, Jiaqi Wang, Wendong Zhang, Lijiao Zu, Shi Qiu, Wa Jin, Xinghu Fu","doi":"10.1016/j.sna.2025.117406","DOIUrl":"10.1016/j.sna.2025.117406","url":null,"abstract":"<div><div>A composite multi-parameter fiber sensor based on the Vernier effect was designed and fabricated for simultaneous axial strain and curvature measurement. The sensor integrates a Fabry-Perot interferometer (FPI) and a multimode interferometer (MMI), each constructed using hollow core fiber (HCF) with differing core diameters. The FPI uses an HCF with a larger core diameter, while the MMI is formed by cascading an HCF with a smaller core diameter to an HCF with a larger core diameter. Due to their distinct sensing mechanisms, the two interferometers respond differently, enabling simultaneous detection of axial strain and curvature. Experimental results indicate axial strain and curvature sensitivities of 2.94 pm/µε and 8.53 nm/m⁻¹ respectively, when the MMI is used as the sensing element. When the FPI is used as the sensing element, the strain sensitivity is enhanced to −4.38 pm/µɛ, and the curvature sensitivity is −5.61 nm/m⁻¹ . This sensor provides a novel tool for multi-dimensional parameter collection in intelligent control systems.</div></div>","PeriodicalId":21689,"journal":{"name":"Sensors and Actuators A-physical","volume":"399 ","pages":"Article 117406"},"PeriodicalIF":4.9,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791678","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}
Despite recent progress in decoupling algorithms for multi-axis force sensors, the high cost of high-fidelity (HF) calibration data severely limits dataset size, resulting in poor generalization in complex multi-axis loading scenarios. To address these challenges, a physics-informed transfer learning-based decoupling algorithm is proposed to reduce the dependence on HF multi-axis coupled calibration data. The proposed method comprises two primary parts. First, HF data are obtained from multi-axis coupled calibration experiments, while low-fidelity (LF) data are generated using a physics-based surrogate model derived via the Least Squares (LS) method. The LF dataset captures the first-order coupling characteristics of the sensor and serves as the source domain, whereas the HF dataset represents the target domain. Second, Bayesian Optimization (BO) is employed to identify optimal hyperparameters that ensure the network structure is commensurate with the nonlinear coupling complexity of the sensor. A fully connected neural network is pre-trained on the LF dataset to encode low-order coupling mechanisms and subsequently fine-tuned using the HF dataset to compensate for higher-order nonlinear effects. Compared with LS, Extreme Learning Machine (ELM), and Artificial Neural Network (ANN), the proposed method achieves superior accuracy, reaching an RRMSE of 0.009 with error reductions of 60.9 %, 30.7 % and 40 % under identical calibration data conditions. Moreover, the proposed method substantially reduces the reliance on HF calibration data, achieving accuracy comparable to ELM and ANN trained with approximately 200 and 250 samples using only 100 HF samples.
{"title":"Novel decoupling algorithm based on transfer learning for multi-axis force sensor","authors":"Yijian Wang, Xiaozhe Ju, Xing Chen, Siyu Zhang, Li Pan, Hongshi Ruan, Lihua Liang, Yangjian Xu","doi":"10.1016/j.sna.2025.117397","DOIUrl":"10.1016/j.sna.2025.117397","url":null,"abstract":"<div><div>Despite recent progress in decoupling algorithms for multi-axis force sensors, the high cost of high-fidelity (HF) calibration data severely limits dataset size, resulting in poor generalization in complex multi-axis loading scenarios. To address these challenges, a physics-informed transfer learning-based decoupling algorithm is proposed to reduce the dependence on HF multi-axis coupled calibration data. The proposed method comprises two primary parts. First, HF data are obtained from multi-axis coupled calibration experiments, while low-fidelity (LF) data are generated using a physics-based surrogate model derived via the Least Squares (LS) method. The LF dataset captures the first-order coupling characteristics of the sensor and serves as the source domain, whereas the HF dataset represents the target domain. Second, Bayesian Optimization (BO) is employed to identify optimal hyperparameters that ensure the network structure is commensurate with the nonlinear coupling complexity of the sensor. A fully connected neural network is pre-trained on the LF dataset to encode low-order coupling mechanisms and subsequently fine-tuned using the HF dataset to compensate for higher-order nonlinear effects. Compared with LS, Extreme Learning Machine (ELM), and Artificial Neural Network (ANN), the proposed method achieves superior accuracy, reaching an RRMSE of 0.009 with error reductions of 60.9 %, 30.7 % and 40 % under identical calibration data conditions. Moreover, the proposed method substantially reduces the reliance on HF calibration data, achieving accuracy comparable to ELM and ANN trained with approximately 200 and 250 samples using only 100 HF samples.</div></div>","PeriodicalId":21689,"journal":{"name":"Sensors and Actuators A-physical","volume":"399 ","pages":"Article 117397"},"PeriodicalIF":4.9,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791680","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 : 2025-12-15DOI: 10.1016/j.sna.2025.117409
Ziwei Liu , Dongming Fang , Jun Du , Chong Lei , Hengchao Sun , Shuai Jiang , Zhiqiang Wang , Peixiao Li
A MEMS fluxgate current sensing chip designed for DC/AC weak and small current detection is proposed, which integrates a thick-film magnetic core, three-dimensional (3D) coil windings, and an on-chip current-carrying conductor on a silicon substrate to construct the complete device architecture. External magnetic field generated by the measured current is concentrated by the high-permeability magnetic core and modulated onto the 3D sensing coils to generate a voltage signal, achieving an improvement in current sensitivity over comparable micro-fluxgate current sensors. Experimental results reveal that the fabricated chip exhibits a linear measurement range from 10 mA to 1 A, achieving a detection accuracy of 0.67 % at 10 mA, under optimal sinusoidal excitation conditions of 100 kHz and 35 mA. The noise at 1 Hz is 0.97 μA/√Hz, and the power consumption is 33.8 mW. The proposed current sensing chip is capable of detecting both direct and alternating currents with a bandwidth ranging from DC to 512 Hz. This work demonstrates the miniaturization of conventional fluxgate current sensors, providing an innovative integrated current sensing solution for space-constrained applications in smart grids and new energy fields.
{"title":"A MEMS fluxgate current sensing chip applicable to DC/AC weak and small current detection","authors":"Ziwei Liu , Dongming Fang , Jun Du , Chong Lei , Hengchao Sun , Shuai Jiang , Zhiqiang Wang , Peixiao Li","doi":"10.1016/j.sna.2025.117409","DOIUrl":"10.1016/j.sna.2025.117409","url":null,"abstract":"<div><div>A MEMS fluxgate current sensing chip designed for DC/AC weak and small current detection is proposed, which integrates a thick-film magnetic core, three-dimensional (3D) coil windings, and an on-chip current-carrying conductor on a silicon substrate to construct the complete device architecture. External magnetic field generated by the measured current is concentrated by the high-permeability magnetic core and modulated onto the 3D sensing coils to generate a voltage signal, achieving an improvement in current sensitivity over comparable micro-fluxgate current sensors. Experimental results reveal that the fabricated chip exhibits a linear measurement range from 10 mA to 1 A, achieving a detection accuracy of 0.67 % at 10 mA, under optimal sinusoidal excitation conditions of 100 kHz and 35 mA. The noise at 1 Hz is 0.97 μA/√Hz, and the power consumption is 33.8 mW. The proposed current sensing chip is capable of detecting both direct and alternating currents with a bandwidth ranging from DC to 512 Hz. This work demonstrates the miniaturization of conventional fluxgate current sensors, providing an innovative integrated current sensing solution for space-constrained applications in smart grids and new energy fields.</div></div>","PeriodicalId":21689,"journal":{"name":"Sensors and Actuators A-physical","volume":"399 ","pages":"Article 117409"},"PeriodicalIF":4.9,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791754","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 : 2025-12-15DOI: 10.1016/j.sna.2025.117366
Jianya Wei , Zehua Wang , Jingyi Bai , Dana Dabiri
Dual-dye pressure-sensitive paint (PSP) combines a pressure-responsive luminophore with either a reference dye or a temperature dye to compensate for either model movement or temperature variations, respectively. Yet accurate pixel-wise separation of their overlapping emissions remains a challenge. This study introduces a matrix-based tristimulus value transformation that projects raw red–green–blue images onto dye-specific basis vectors derived from hue–saturation–value-filtered single-dye coupons. As an example of describing this approach, Pt(II) meso-tetra(pentafluorophenyl)porphyrin (PtTFPP) is used as the pressure-sensitive dye, while Coumarin 500 is used as the reference dye. The closed-form decomposition requires no additional optics and preserves full sensor resolution, thereby making it suitable for real-time applications. Validation in a vacuum chamber spanning 0.05–758 Torr shows that the separated PtTFPP channel follows a near-linear Stern–Volmer response with a regression coefficient of 0.9998, while the Coumarin 500 channel remains essentially constant, confirming its pressure independence. The Coumarin 500-to-PtTFPP intensity ratio from single-dye and dual-dye data is likewise linear across the full pressure range, further verifying separation fidelity. The proposed workflow advances dual-dye PSP toward routine quantitative pressure mapping and lays the foundation for simultaneous pressure–temperature diagnostics in aerodynamic and other complex flow environments.
{"title":"A tristimulus value transformation calibration method for spectral emission separation in dual-dye pressure-sensitive paints","authors":"Jianya Wei , Zehua Wang , Jingyi Bai , Dana Dabiri","doi":"10.1016/j.sna.2025.117366","DOIUrl":"10.1016/j.sna.2025.117366","url":null,"abstract":"<div><div>Dual-dye pressure-sensitive paint (PSP) combines a pressure-responsive luminophore with either a reference dye or a temperature dye to compensate for either model movement or temperature variations, respectively. Yet accurate pixel-wise separation of their overlapping emissions remains a challenge. This study introduces a matrix-based tristimulus value transformation that projects raw red–green–blue images onto dye-specific basis vectors derived from hue–saturation–value-filtered single-dye coupons. As an example of describing this approach, Pt(II) meso-tetra(pentafluorophenyl)porphyrin (PtTFPP) is used as the pressure-sensitive dye, while Coumarin 500 is used as the reference dye. The closed-form decomposition requires no additional optics and preserves full sensor resolution, thereby making it suitable for real-time applications. Validation in a vacuum chamber spanning 0.05–758 Torr shows that the separated PtTFPP channel follows a near-linear Stern–Volmer response with a regression coefficient of 0.9998, while the Coumarin 500 channel remains essentially constant, confirming its pressure independence. The Coumarin 500-to-PtTFPP intensity ratio from single-dye and dual-dye data is likewise linear across the full pressure range, further verifying separation fidelity. The proposed workflow advances dual-dye PSP toward routine quantitative pressure mapping and lays the foundation for simultaneous pressure–temperature diagnostics in aerodynamic and other complex flow environments.</div></div>","PeriodicalId":21689,"journal":{"name":"Sensors and Actuators A-physical","volume":"399 ","pages":"Article 117366"},"PeriodicalIF":4.9,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841340","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}
The selection of an appropriate substrate and sensing layer remains a critical challenge in gas-sensor development. This study develops biodegradable gas sensors using poly(lactic acid)/poly(ethylene glycol) (PLA/PEG) fiber substrates and tracing paper (TP), functionalized with polyaniline (PANI) and polyaniline/graphene oxide (PANI/GO) sensing layers, and integrates them into an electronic nose for discrimination of cinnamon bark essential oils from Cinnamomum zeylanicum (true cinnamon, TCBEO) and Cinnamomum cassia (false cinnamon, FCBEO). The sensors are characterized by ATR-FTIR and SEM and evaluated for sensitivity, limit of detection (LOD), limit of quantification (LOQ), hysteresis, response and recovery times, stability over 90 days, and cross-interference with common edible oils and humidity. All sensors were able to discriminate the volatile compounds of C. zeylanicum and C. cassia bark essential oil, exhibit linear sensitivities in the range 7.9–12.2 Ohm·ppm⁻¹ , LODs between 0.5866 and 0.9844 ppm, and LOQs between 1.9555 and 3.2814 ppm. Hysteresis was minimal (<1 %), response times range from 19.9 to 39.4 s, and recovery times from 40 to 89 s. Sensors fabricated on PLA/PEG fibers show the highest sensitivities and the lowest LOD/LOQ values, whereas PANI/GO composites enhance electron transport and contribute to improved sensitivity at low analyte concentrations. Stability tests indicate acceptable performance retention over 90 days, with larger sensitivity loss observed at the lowest concentration (2 ppm). Interference tests show negligible cross-sensitivity to soybean, corn, sunflower oils and vaseline, but partial signal overlap with olive oil and FCBEO; relative humidity notably affects sensor response at high levels (≈75 % RH). These results demonstrate that PLA/PEG fiber substrates provide a sustainable, high-performance platform for electronic-nose applications aimed at essential-oil discrimination.
{"title":"Biodegradable gas sensors based on PLA/PEG for discrimination of cinnamon bark essential oils using an electronic nose","authors":"Giovana Feltes , Ilizandra Aparecida Fernandes , Rafaella Takehara Paschoalin , Juliana Steffens , Natalia Paroul , Clarice Steffens","doi":"10.1016/j.sna.2025.117400","DOIUrl":"10.1016/j.sna.2025.117400","url":null,"abstract":"<div><div>The selection of an appropriate substrate and sensing layer remains a critical challenge in gas-sensor development. This study develops biodegradable gas sensors using poly(lactic acid)/poly(ethylene glycol) (PLA/PEG) fiber substrates and tracing paper (TP), functionalized with polyaniline (PANI) and polyaniline/graphene oxide (PANI/GO) sensing layers, and integrates them into an electronic nose for discrimination of cinnamon bark essential oils from <em>Cinnamomum zeylanicum</em> (true cinnamon, TCBEO) and <em>Cinnamomum cassia</em> (false cinnamon, FCBEO). The sensors are characterized by ATR-FTIR and SEM and evaluated for sensitivity, limit of detection (LOD), limit of quantification (LOQ), hysteresis, response and recovery times, stability over 90 days, and cross-interference with common edible oils and humidity. All sensors were able to discriminate the volatile compounds of <em>C. zeylanicum</em> and <em>C. cassia</em> bark essential oil, exhibit linear sensitivities in the range 7.9–12.2 Ohm·ppm⁻¹ , LODs between 0.5866 and 0.9844 ppm, and LOQs between 1.9555 and 3.2814 ppm. Hysteresis was minimal (<1 %), response times range from 19.9 to 39.4 s, and recovery times from 40 to 89 s. Sensors fabricated on PLA/PEG fibers show the highest sensitivities and the lowest LOD/LOQ values, whereas PANI/GO composites enhance electron transport and contribute to improved sensitivity at low analyte concentrations. Stability tests indicate acceptable performance retention over 90 days, with larger sensitivity loss observed at the lowest concentration (2 ppm). Interference tests show negligible cross-sensitivity to soybean, corn, sunflower oils and vaseline, but partial signal overlap with olive oil and FCBEO; relative humidity notably affects sensor response at high levels (≈75 % RH). These results demonstrate that PLA/PEG fiber substrates provide a sustainable, high-performance platform for electronic-nose applications aimed at essential-oil discrimination.</div></div>","PeriodicalId":21689,"journal":{"name":"Sensors and Actuators A-physical","volume":"399 ","pages":"Article 117400"},"PeriodicalIF":4.9,"publicationDate":"2025-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841292","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}
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