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Advancements in hydrogen gas leakage detection sensor technologies and safety measures

CLEAN ENERGY 2025年第1期9卷 263-277页

作者： Menon, Shyam Kumar Kumar, Adesh Mondal, Surajit UPES Sch Adv Engn Dept Elect & Elect Engn Dehra Dun 248007 Uttarakhand India

Hydrogen is hailed as a plentiful and clean energy source, which holds promise as a substitute for fossil fuels, particularly when produced through solar water splitting. However, its volatile and explosive nature necessitates stringent safety measures throughout its production, transportation, and utilization. This study analyzes hydrogen gas leakage detection by using various sensors such as ultrasonic, electrochemical, metal oxide (MOX), catalytic, and fiber Bragg grating sensors. Various sensor technologies are developed for hydrogen leak detection, and each offers unique advantages and challenges. Fiber optic sensors, leveraging changes in light interference, provide explosion resistance and durability, while ultrasonic sensors detect leaks through sound wave analysis, albeit with limited commercial application in hydrogen environments. Schlieren imaging offers real-time visualization of hydrogen behavior, predominantly in laboratory settings. Electrochemical sensors enable reliable detection through electrochemical interactions, while MOX sensors exhibit sensitivity and ease of manufacturing, albeit with challenges related to cross-sensitivity and response times. Catalytic gas sensors and thermal conductivity sensors offer alternative detection methods, with the former catalyzing hydrogen combustion for detection and the latter measuring temperature differentials upon exposure to hydrogen. The analysis of hydrogen leakage incidents highlights the importance of robust safety measures in hydrogen infrastructure and facilities. The integration of innovative sensing technologies with automated shutdown systems and robust materials has enhanced the reliability and efficiency of leak detection systems. Continued research and cooperation are essential to address residual challenges and further enhance the safety of hydrogen utilization in various industrial sectors. Hydrogen gas leakage detection sensors are reviewed, including types such as ultrasonic, electrochemic

关键词： fossil fuels FBG hydrogen natural gas sensor

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Synergistic design of mechanical properties between implantable sensor and concrete based on three-dimensional refined numerical model

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CONSTRUCTION AND BUILDING MATERIALS 2024年 426卷

作者： Liu, Chuankun Kong, Linghui Wei, Ya Tsinghua Univ Dept Civil Engn Key Lab Civil Engn Safety & Durabil China Educ Minist Beijing 100084 Peoples R China Southwest United Grad Sch Kunming 650092 Peoples R China

With the ongoing advancement in the construction and development of intelligent infrastructures, there has been a significant integration of sensors within structures. Portland Cement Concrete (PCC) pavement, being a predominant form of transportation infrastructures, necessitates comprehensive analysis due to its critical role. Given that flexural strength is a paramount design criterion for PCC pavements, concrete beams are selected as the primary focus for this study. Initially, a sophisticated three-dimensional numerical model is constructed. This model intricately incorporates the concepts of concrete damaged plasticity (CDP) and the cohesive zone model (CZM) to examine the interaction between the sensor and the concrete beam. The veracity of the numerical model is rigorously validated through methodical three-point bending tests, ensuring its reliability and accuracy. Subsequently, an innovative method for the synergistic design and assessment of the mechanical properties of the implantable sensor in conjunction with the concrete component is introduced. This methodology is underpinned by a novel synergistic performance index system. The system is stratified into different layers, with synergy degree as the target layer, and bearing performance, deformation coordination, and damage control as the criterion layer. In the final phase of the research, the study delves into the impacts of various factors such as size parameters, packaging materials, and positioning of the sensor on its synergistic performance with the concrete. The insights derived from this research are poised to offer valuable guidance for the integrated synergistic design of sensors. This is envisioned to facilitate optimal integration, ensuring long-term and precise monitoring of concrete structures, thereby contributing significantly to the field of intelligent infrastructure construction and maintenance.

关键词： Concrete damaged plasticity Cohesive zone model Implantable sensor Refined numerical model Synergistic performance

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Hardware Implementation of Edge Neural Network Computing for sensor With Memristors Based on Single-Crystalline LiNbO3 Thin Film

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IEEE sensors JOURNAL 2023年第8期23卷 8526-8534页

作者： Pan, Xinqiang Luo, Wen Shuai, Yao Hu, Shaogang Luo, Wenbo Qiao, Guanchao Zhou, Tong Wang, Jiejun Xie, Qin Huang, Shitian Liu, Yang Wu, Chuangui Zhang, Wanli Univ Elect Sci & Technol China UESTC State Key Lab Elect Thin Films & Integrated Device Chengdu 611731 Peoples R China UESTC Chongqing Inst Microelect Ind Technol Chongqing 401332 Peoples R China

With the development of artificial intelligent IoT (AIoT) and dramatic increase of the amount of data, conventional architecture, in which all the data collected by sensors are sent to the data center for processing and computing, suffered from heavy computing load in the data center, latency, and high energy consumption. Edge neural network computing at the sensor terminal is demanding. Based on the advantages of memristor in nature co-location of memory and computing, high computing parallelism, low energy consumption, and miniaturization potential, we proposed to take use of memristors to conduct edge neural network computing at sensor and realize the integration of sensing memory computing. Also, in order to solve the problems caused by resistance states variation and device-to-device variation without transistor connected in series, highly uniform memristors based on single-crystalline LiNbO3 (LN) thin film with two stable resistance states were fabricated and utilized to realize binarized neural networks computing, and the coupling between the pressure sensor output signal with the input of the memristor array has been built. The hardware implementation of memristor-based edge neural network computing on the signals of pressure sensor array has been realized. With the memristor-based edge neural network computing, recognition of three letters ("V," "Z," and "T") wrote on the pressure sensor array has been realized.

关键词： Memristors sensors Resistance Pressure sensors sensor arrays Training Hardware Artificial intelligent IoT (AIoT) edge computing integration of sensing memory computing memristor neural network

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Study and Realization of Environmental Health Diagnosis by Using Nanomaterial Based Fiber Optic sensor-A Review

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IEEE sensors JOURNAL 2023年第1期23卷 53-67页

作者： Singh, Shailendra Kumar Paul, Mukul Chandra Acad Sci & Innovat Res AcSIR Ghaziabad 201002 India Cent Glass & Ceram Res Inst Fiber Opt & Photon Div Kolkata 700032 India

In these days, the significance of fiber optic sensors has exceptionally increased due to technological advances in modern society. Nowadays, researchers are attracted toward the development of a sensor that possesses the integration of both fiber optic sensors and nanocomposite thin film to improve the sensor's performance. Thin-film nanomaterial based optical fiber sensors have great potential applications, namely, gas sensing, chemical sensing, biomolecules, food plant, industrial hazards, safety issues, drug monitoring, and heavy metal detections. There are various techniques, namely, evanescent field absorption spectroscopy, fiber Bragg grating (FBG), long-period grating (LPG), ringdown spectroscopy, surface plasmon resonance (SPR), Mach-Zehnder interferometer (MZI) techniques, and so on, which are used for the development of fiber optic sensors that are majorly emphasized in the current article. Numerous scientific researchers have demonstrated that functionalized fiber optic sensors are found more beneficial in terms of improvement of the sensing performance, such as sensitivity, repeatability, response time, specificity, recovery time, and repeatability. Henceforth, in this review article, we have focused on these requisite sensing parameters in detail. Furthermore, to keep human beings healthy, it is our responsibility to develop a sensor that can monitor the optimum toxic concentrations accurately. Thus, the monitoring of industrial environmental pollutants, such as NH3, ethylenediamine, alcohol, and acetone, is immensely important to save human lives on Earth. In the report, all the details of the target analytes, such as optimum concentrations, adverse effects on human beings, and monitoring techniques, are discussed.

关键词： sensors Optical fiber sensors Optical fibers Temperature sensors Monitoring Sensitivity Chemical sensors Ammonia sensor fiber optic sensor nanomaterial thin-film material volatile organic compounds (VOCs)

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Printed Wearable Sweat Rate sensor for Continuous In Situ Perspiration Measurement

ADVANCED INTELLIGENT SYSTEMS

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ADVANCED INTELLIGENT SYSTEMS 2025年第3期7卷

作者： Islam, Mohammad Shafiqul Cha, Sangwon Hassan, Md Farhad Cai, Wenxin Saniat, Tahsin Sejat Leach, Cedar Rose Khan, Yasser Univ Southern Calif Dept Elect & Comp Engn Los Angeles CA 90089 USA Univ Southern Calif Inst Technol & Med Syst ITEMS Keck Sch Med Los Angeles CA 90033 USA Univ Southern Calif Mork Family Dept Chem Engn & Mat Sci Los Angeles CA 90089 USA Georgia Inst Technol Sch Aerosp Engn Atlanta GA 30332 USA

Sweat rate measures key physiological states such as hydration levels and heat tolerance. Incorporating wearable technology with sweat rate sensors allows individuals to conveniently monitor their health, optimize workouts, and enhance occupational safety. However, challenges persist in such integration techniques, including intricate manufacturing, nonlinear responses to changes in sweat rates, and errors from the intermediate measurement of the distance sweat travels in the sensor. To address these issues, we present a comprehensive wearable platform that includes a fully printed, flexible sensor patch, readout electronics, and a mobile app for continuous, real-time monitoring of sweat rate. We fabricate a sensor patch with an area of 700 mm2 and a weight of 380 mg by utilizing direct 3D printing and scalable microfluidic fabrication. The microfluidic channels are 850 mu m wide and 164 mu m thick, with serpentine electrodes measuring sweat rate using capacitance. The custom readout electronics capture these changes in capacitance to accurately measure sweat rate, achieving a sensitivity of 0.01 mu L min-1. The sensor's performance is validated against analytical models, simulations, and on-body trials with commercial sensors. This cost-effective, flexible, and fully integrated sweat-sensing solution has significant potential in precision health.

关键词： capacitive sweat rate sensors bioelectronics flexible and printed electronics wearable electronics

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A Method for Automated Manufacturing of Ion-Selective Electrodes

IEEE SENSORS LETTERS

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IEEE sensors LETTERS 2025年第1期9卷

作者： Zhai, Jiawei Luo, Bin Liu, Tianyang Wang, Xiaodong Zhao, Chunjiang Beijing Univ Technol Fac Informat Technol Dept Artificial Intelligence & Automat Beijing 100124 Peoples R China Beijing Acad Agr & Forestry Sci Intelligent Equipment Res Ctr Beijing 100097 Peoples R China Minist Agr & Rural Affairs Key Lab Agr Sensors Beijing 100097 Peoples R China

Ion-selective electrodes (ISEs) play an important role in the field of electrochemical sensors and have a significant impact on future ion detection. At present, to address the sensor consistency issue in the commercialization process of ISE, we emphasize that automated manufacturing has the potential to achieve calibration-free sensors. First, the design of automated manufacturing requires expert experience to help understand the ISE mechanism and its structure. Then, we introduce two automated manufacturing processes for sensors to help understand the design and manufacturing process. Finally, we propose a device for semiautomated manufacturing of ISE and verify that automated manufacturing of ISE has better consistency and potential reproducibility than manual manufacturing of ISE. The results show that for the transduction layer (conductive graphite adhesive) coated automatically in the same batch, the impedance difference is 4.8 K Omega, while that of the manual batch is 36.6 K Omega. In the performance of cyclic voltammetry, the gap of peak current is reduced from 21.5 to 4.8 mu A.

关键词： Electrodes sensors Ions Wire Production Platinum Electric potential Solids sensor materials automation ion-selective electrode (ISE) LabVIEW manufacturing mechanical-electrical integration manufacturing mechanical-electrical integration

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Electrochemical sensors Go Nano: Carbon Nanomaterials for Ultrasensitive Heavy Metal Analysis

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CURRENT NANOSCIENCE 2025年第4期21卷 596-612页

作者： Zhou, Qingwei Fu, Li Zhu, Jiangwei Hangzhou Dianzi Univ Coll Mat & Environm Engn Hangzhou 310018 Peoples R China Nanjing Forestry Univ Coinnovat Ctr Sustainable Forestry Southern China Nanjing 210037 Peoples R China

Background Heavy metal contamination of food and the environment is a major concern worldwide. Conventional detection techniques like atomic absorption spectroscopy (AAS), inductively coupled plasma-optical emission spectrometry (ICP-OES) and inductively coupled plasma-mass spectrometry (ICP-MS) have limitations including high costs and insufficient sensitivity. Electrochemical sensors based on carbon nanomaterials have emerged as an attractive alternative for rapid, affordable, and ultrasensitive heavy metal *** This review summarizes recent advances in using carbon nanomaterials like ordered mesoporous carbon, carbon nanotubes, graphene and carbon dots for electrochemical sensing of toxic heavy metals. Synthesis methods, characterization techniques, functionalization strategies and detection mechanisms are *** High surface area, electrical conductivity and electrocatalytic activity of carbon nanomaterials enable preconcentration of metal ions and signal amplification at electrode interfaces. This results in remarkably low detection limits down to parts per trillion levels. Functionalization with metal nanoparticles, molecularly imprinted polymers and other nanocomposites further improves sensor selectivity and sensitivity. These sensors have been applied for the quantitative detection of arsenic, mercury, lead, cadmium, chromium, and other toxic metals in lab *** Electrochemical sensors based on carbon nanotubes, graphene, mesoporous carbon, and carbon dots are rapidly emerging as an ultrasensitive, cost-effective alternative to conventional techniques for on-site screening of heavy metal contamination in food and environment. Further validation using real-world samples and integration into portable field testing kits can enable widespread deployment.

关键词： Carbon materials electrochemical sensor heavy metal sensor detection nanocomposite

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Implantable pH Sensing System Using Vertically Stacked Silicon Nanowire Arrays and Body Channel Communication for Gastroesophageal Reflux Monitoring

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sensors 2024年第3期24卷 861页

作者： Kim, Changhee Han, Seungju Kim, Taehwan Lee, Sangmin Kyung Hee Univ Dept Elect & Informat Convergence Engn Yongin 17104 South Korea Kyung Hee Univ Dept Biomed Engn Yongin 17104 South Korea

Silicon nanowires (SiNWs) are emerging as versatile components in the fabrication of sensors for implantable medical devices because of their exceptional electrical, optical, and mechanical properties. This paper presents a novel top-down fabrication method for vertically stacked SiNWs, eliminating the need for wet oxidation, wet etching, and nanolithography. The integration of these SiNWs into body channel communication (BCC) circuits was also explored. The fabricated SiNWs were confirmed to be capable of forming arrays with multiple layers and rows. The SiNW-based pH sensors demonstrated a robust response to pH changes, and when tested with BCC circuits, they showed that it was possible to quantize based on pH when transmitting data through the human body. This study successfully developed a novel method for SiNW fabrication and integration into BCC circuits, which could lead to improvements in the reliability and efficiency of implantable medical sensors. The findings demonstrate significant potential for bioelectronic applications and real-time biochemical monitoring.

关键词： silicon nanowire MEMS body channel communication pH sensor

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A Machine-Learning Architecture for sensor Fault Detection, Isolation, and Accommodation in Digital Twins

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IEEE sensors JOURNAL 2023年第3期23卷 2522-2538页

作者： Darvishi, Hossein Ciuonzo, Domenico Rossi, Pierluigi Salvo Norwegian Univ Sci & Technol Dept Elect Syst N-7491 Trondheim Norway Ecole Polytech Fed Lausanne EPFL Signal Proc Lab LTS4 CH-1015 Lausanne Switzerland Univ Naples Federico II Dept Elect Engn & Informat Technol DIETI I-80125 Naples Italy SINTEF Energy Res Dept Gas Technol N-7491 Trondheim Norway

sensor technologies empower Industry 4.0 by enabling integration of in-field and real-time raw data into digital twins (DTs). However, sensors might be unreliable due to inherent issues and/or environmental conditions. This article aims at detecting anomalies instantaneously in measurements from sensors, identifying the faulty ones and accommodating them with appropriate estimated data, thus paving the way to reliable DTs. More specifically, a real-time general machine-learning-based architecture for sensor validation is proposed, built upon a series of neural-network estimators and a classifier. Estimators correspond to virtual sensors of all unreliable sensors (to reconstruct normal behavior and replace the isolated faulty sensor within the system), whereas the classifier is used for detection and isolation tasks. A comprehensive statistical analysis on three different real-world datasets is conducted and the performance of the proposed architecture is validated under hard and soft synthetically generated faults.

关键词： sensors sensor systems Fault diagnosis Artificial neural networks Task analysis Fault detection Proposals Digital twin (DT) fault diagnosis machine learning neural networks (NNs) sensor validation

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Thermal Compensation System for Silicon Piezoresistive Pressure sensors Based on Surface Fitting and Wild Horse Algorithm

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IEEE sensors JOURNAL 2024年第7期24卷 10347-10354页

作者： Su, Wenbin Ren, Wei Han, Xiangguang Hua, Yingli Mu, Xinrong Huang, Mimi Chen, Shuai Wang, Shengqi Cui, Zeyu Zhao, Libo Xi An Jiao Tong Univ Sch Mech Engn Xian 710049 Peoples R China Xi An Jiao Tong Univ Sch Instrument Sci & Technol Xian 710049 Peoples R China

Silicon piezoresistive pressure sensors suffer from temperature effects significantly. The thermal compensation system based on surface fitting and wild horse algorithm is proposed to overcome the nonlinearity. The polynomial coefficients in surface fitting are optimized using the wild horse algorithm. A platinum resistance thermometer (PRT) integrated in the silicon layer of the pressure sensor is employed to capture the local temperature variations. The extracted pressure and temperature changes are fed to the compensation algorithm via digital circuits. The results of calibration experiments show that the PRT has a maximum absolute error of 1.24 Omega , and the standard deviation of the output signal and sensitivity among several pressure sensors in the same batch is 4.5 mV and 0.07 mV/MPa, respectively, ensuring the accuracy for PRT and mass production repeatability for pressure sensors. The comprehensive performance of the compensation system was validated under 0-40 MPa and 0 degrees C-80 degrees C. The linearity of the sensor decreases from 8.1218%FS to 0.0629%FS on the calibration data. When the pressure and temperature change simultaneously, the linearity remains at 0.1112%FS. Hence, the system considerably reduces the temperature impact on silicon piezoresistive pressure sensors and exhibits strong integration and generalization.

关键词： Temperature sensors sensors Temperature measurement Piezoresistance Pressure sensors Silicon Surface fitting Platinum resistance thermometer (PRT) silicon piezoresistive pressure sensors surface fitting thermal compensation system

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