Advanced Sensor Research最新文献_第9页

Zero-Power, Optical Toxic Gas and Vapor Sensors Utilizing Printed Nematic Liquid Crystal Patterns on Selectively Reactive Substrates 在选择性反应基板上利用印刷向列液晶图案的零功率光学有毒气体和蒸汽传感器

IF 3.5

Advanced Sensor Research Pub Date : 2025-03-05 DOI: 10.1002/adsr.202400166

Ryan A. Williams, Grace A. R. Rohaley, Ashwathanarayana Gowda, Gisele Pegorin, Andrea Oprandi, Denis Motovilov, Anthony Schneider, Elda Hegmann, Marianne E. Prévôt, Torsten Hegmann

{"title":"Zero-Power, Optical Toxic Gas and Vapor Sensors Utilizing Printed Nematic Liquid Crystal Patterns on Selectively Reactive Substrates","authors":"Ryan A. Williams, Grace A. R. Rohaley, Ashwathanarayana Gowda, Gisele Pegorin, Andrea Oprandi, Denis Motovilov, Anthony Schneider, Elda Hegmann, Marianne E. Prévôt, Torsten Hegmann","doi":"10.1002/adsr.202400166","DOIUrl":"10.1002/adsr.202400166","url":null,"abstract":"Health risks affiliated with exposure to a wide variety of toxic gases and vapors are a certainty for first responders such as firefighters and HAZMAT team members but also for countless other professions from water purification and chemical manufacturing to the oil and gas industry, among others, and even the general public. Here the fabrication and testing of several prototypes for a novel toxic gas sensor platform based on ink-jet printed nematic liquid crystal patterns are described. These sensors require zero power to operate and are characterized by high sensitivity down to highly relevant ppm and ppb levels, fast response times on the order of seconds, improved durability, and an overall design that is highly customizable by the potential end user. The response times of these sensors exponentially decrease with toxic gas concentration, thereby establishing the toxic gas diffusivity dependence of their mode of action. Such prototypes for two particular toxic gases, chlorine, and phosgene, performing interference testing in high humidity and smoke conditions as well as field testing with active firefighters are demonstrated.","PeriodicalId":100037,"journal":{"name":"Advanced Sensor Research","volume":"4 6","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adsr.202400166","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144273281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Overview: A Design Strategy for Dioxide Carbon QCM Gas Sensor Based on MOFs or COFs 概述：基于 MOFs 或 COFs 的二氧化碳 QCM 气体传感器的设计策略

IF 3.5

Advanced Sensor Research Pub Date : 2025-03-02 DOI: 10.1002/adsr.202400170

Xukun Wang, Tong Zhang

引用次数: 0

Compact Device for Monitoring Electret Filter Performance via Electric Field Strength 通过电场强度监测驻极体滤波器性能的紧凑型装置

IF 3.5

Advanced Sensor Research Pub Date : 2025-02-22 DOI: 10.1002/adsr.202400187

Johanna Zikulnig, Martin Lenzhofer, Christoph Mayer, Günter Grabher, Tobias Berchtold, Jürgen Kosel

引用次数: 0

Strain Redistribution Effect Based Composite Structured Sensor for Decouplable Tactile-Strain Double-Mode Perception 基于应变重分布效应的可解耦触觉-应变双模感知复合结构传感器

IF 3.5

Advanced Sensor Research Pub Date : 2025-02-21 DOI: 10.1002/adsr.202400147

Hanning Wang, Xiaofei Liu, Da Chen, Zhanbo Zhang, Xinyu Ma, Hongchen Yu, Quanlin Qu, Huifang Wang, Fujie Cao, Tong Zhang, Yijian Liu

{"title":"Strain Redistribution Effect Based Composite Structured Sensor for Decouplable Tactile-Strain Double-Mode Perception","authors":"Hanning Wang, Xiaofei Liu, Da Chen, Zhanbo Zhang, Xinyu Ma, Hongchen Yu, Quanlin Qu, Huifang Wang, Fujie Cao, Tong Zhang, Yijian Liu","doi":"10.1002/adsr.202400147","DOIUrl":"10.1002/adsr.202400147","url":null,"abstract":"A key challenge in electronic skin with dual haptic-stretch sensing is the interference between force-sensitive modes. Existing solutions require complex integration processes or mathematical decoupling models. Effectively decoupling stretch and pressure response in flexible force-sensitive sensors remains a critical task. Herein, a strain redistribution effect (SRE) of composite structural mainframe fulfills the decouple double-mode force-sensitive perception by the aid of a lightweight algorithm. The CAD-assisted design enables the dual-mode sensing structure to be configured as a three-layer stacked composite. Utilizing differential Young's modulus distribution, the strain redistribution effect is achieved across the structured frame. Tensile deformation and tactile pressure are measured via resistance from the strain amplification region and capacitance from the strain suppression region, respectively. Digital Image Correlation (DIC) confirms a 53% deformation in the amplification region under 10% tensile strain, demonstrating a fivefold amplification effect. A lightweight random forest algorithm effectively decouples resistance-capacitance signals, achieving R2 values of 0.99 and 0.75 for tensile deformation, and 0.99 and 0.78 for tactile pressure, respectively. This study leverages the strain redistribution effect of the composite structural frame to provide a novel structured integration scheme for the dual-mode decoupled force-sensitive sensing unit, which is expected to be a significant development path.","PeriodicalId":100037,"journal":{"name":"Advanced Sensor Research","volume":"4 4","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adsr.202400147","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fully-Printed Ion Sensor Arrays for Measuring Agricultural Nitrogen and Potassium Concentrations Using Nernstian and AI Models 使用Nernstian和AI模型测量农业氮和钾浓度的全打印离子传感器阵列

IF 3.5

Advanced Sensor Research Pub Date : 2025-02-20 DOI: 10.1002/adsr.202400121

Payton Goodrich, Nithila Poongovan, Elliot Strand, Carolyn Schwendeman, Lucas Lahann, Sophia Koh, Yuting Cai, Carol Baumbauer, Anju Toor, Gregory Whiting, Ana Claudia Arias

{"title":"Fully-Printed Ion Sensor Arrays for Measuring Agricultural Nitrogen and Potassium Concentrations Using Nernstian and AI Models","authors":"Payton Goodrich, Nithila Poongovan, Elliot Strand, Carolyn Schwendeman, Lucas Lahann, Sophia Koh, Yuting Cai, Carol Baumbauer, Anju Toor, Gregory Whiting, Ana Claudia Arias","doi":"10.1002/adsr.202400121","DOIUrl":"10.1002/adsr.202400121","url":null,"abstract":"The chemical composition of growing media is a key factor for plant growth, impacting agricultural yield and sustainability. However, there is a lack of affordable chemical sensors for ubiquitous nutrient ion monitoring in agricultural applications. This work investigates using fully printed ion-sensor arrays to measure the concentrations of nitrate, ammonium, and potassium in mixed-electrolyte media. Ion sensor arrays composed of nitrate, ammonium, and potassium ion-selective electrodes and a printed silver-silver chloride (Ag/AgCl) reference electrode are fabricated and characterized in aqueous solutions in a range of concentrations that encompass what is typical for agricultural growing media (0.01 mm –1 m). The sensors are also tested in mixed-electrolyte solutions of NaNO3, NH4Cl, and KCl of varying concentrations, and the recorded potentials are input into Nernstian and artificial neural network models to compare the prediction accuracy of the models against ground truth. The artificial neural network models demonstrated higher accuracy over the Nernstian model, and the model using only ion-sensor inputs is 7.5% more accurate than the Nernstian model under the same conditions. By enabling more precise and efficient fertilizer application, these sensor arrays coupled to computational models can help increase crop yields, optimize resource use, and reduce environmental impact.","PeriodicalId":100037,"journal":{"name":"Advanced Sensor Research","volume":"4 4","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adsr.202400121","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

In Situ Growth of The Interpenetrating Structure UiO-66-NH2/MWCNTs-OH for The Detection of Phosphoproteins in Human Sweat UiO-66-NH2/MWCNTs-OH互穿结构原位生长检测人体汗液中磷酸化蛋白

IF 3.5

Advanced Sensor Research Pub Date : 2025-02-15 DOI: 10.1002/adsr.202400130

Zhiye Ying, Ce Bian, Lijuan Qiao, Bingxin Liu, Li Gao

{"title":"In Situ Growth of The Interpenetrating Structure UiO-66-NH2/MWCNTs-OH for The Detection of Phosphoproteins in Human Sweat","authors":"Zhiye Ying, Ce Bian, Lijuan Qiao, Bingxin Liu, Li Gao","doi":"10.1002/adsr.202400130","DOIUrl":"10.1002/adsr.202400130","url":null,"abstract":"Phosphorylated proteins in human sweat are found to be closely associated with neurodegenerative diseases, including Alzheimer's disease. Real-time, non-invasive detection of changes in the types and levels of phosphorylated proteins in sweat is of significant clinical value for the prevention and diagnosis of these diseases. This research introduces an electrochemical sensor based on an in situ-grown interpenetrating network structure of UiO-66-NH2/MWCNTs-OH, specifically designed for detecting phosphorylated proteins in sweat. The sensor is tested with common phosphorylated and non-phosphorylated proteins, demonstrating excellent selectivity, repeatability, reproducibility, and stability, with a limit of detection as low as 0.28 µmol L−1. Additionally, biotoxicity experiments conducted on SD rats and volunteers show that UiO-66-NH2/MWCNTs-OH is biologically safe, making it suitable for use as a biosensor. Finally, the fabrication of the electrochemical sensing module provides a foundation for the development of subsequent wearable sensors.","PeriodicalId":100037,"journal":{"name":"Advanced Sensor Research","volume":"4 4","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adsr.202400130","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Portable and Low-Cost Single Board Computer-Based Spectrophotometric Platform for Optical Analysis in the UV and Visible Range 一种便携式、低成本的基于单片机的紫外和可见光光谱分析平台

IF 3.5

Advanced Sensor Research Pub Date : 2025-02-14 DOI: 10.1002/adsr.202400163

Alessandro Tonelli, Anna Tortone, Alessandro Grazioli, Francesco Pasquali, Michele Sozzi, Alessandro Candiani, Luca Capelli, Alessandro Bertucci

{"title":"A Portable and Low-Cost Single Board Computer-Based Spectrophotometric Platform for Optical Analysis in the UV and Visible Range","authors":"Alessandro Tonelli, Anna Tortone, Alessandro Grazioli, Francesco Pasquali, Michele Sozzi, Alessandro Candiani, Luca Capelli, Alessandro Bertucci","doi":"10.1002/adsr.202400163","DOIUrl":"10.1002/adsr.202400163","url":null,"abstract":"The growing ability of high-performance consumer electronics is fostering innovation in prototyping and research. Although the Raspberry Pi single-board computer (SBC) is widely used across various fields, including diagnostics, applications involving UV-based reading remain underexplored. In this study, a simple, low-cost (less than 100 euros), and portable device for UV–vis measurements based on Raspberry Pi is presented. The system integrates the AS7341 multi-channel multispectral digital sensor, offering analytical performance comparable to two commercial spectrophotometers – one benchtop and one portable – in terms of linearity, limit of detection, quantitation, and repeatability. Furthermore, the device demonstrates reliable performance both in analyzing real wine samples using two different commercial enzymatic kits and in quantifying different concentrations of synthetic DNA oligonucleotides. By providing a ready-to-use, portable, and affordable platform for UV–vis diagnostics, this prototype is well-suited for resource-limited settings, educational environments, and IoT applications where numerous distributed sensors are required for specific diagnostic tasks.","PeriodicalId":100037,"journal":{"name":"Advanced Sensor Research","volume":"4 4","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adsr.202400163","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Computer-Aided Design of Integrated Digital Strain Sensors for Hardware-Based Recognition and Quantification of Human Movements 基于硬件识别和量化人体运动的集成数字应变传感器的计算机辅助设计

IF 3.5

Advanced Sensor Research Pub Date : 2025-02-14 DOI: 10.1002/adsr.202400146

Hudson Gasvoda, Mengchu Li, Andrea Pader, Rana Altay, Nick Cmager, Tripti Pandey, Tsun-Ming Tseng, Ismail Emre Araci

{"title":"Computer-Aided Design of Integrated Digital Strain Sensors for Hardware-Based Recognition and Quantification of Human Movements","authors":"Hudson Gasvoda, Mengchu Li, Andrea Pader, Rana Altay, Nick Cmager, Tripti Pandey, Tsun-Ming Tseng, Ismail Emre Araci","doi":"10.1002/adsr.202400146","DOIUrl":"10.1002/adsr.202400146","url":null,"abstract":"An integrated strain sensor system that has a unique response to a specific (set of) human movement(s) has the potential to impact various musculoskeletal health tracking applications akin to the step counter's impact on physical activity tracking. It is determined that an open circuit state of a sensor can be used as such a unique response. With this consideration, a digital strain sensor (DigSS) that exhibits a binary (i.e., ON/OFF) response when a threshold strain level is exceeded is developed. The channel geometry dependence of the corner flow in capillaric strain sensors (CSS) resulting in an electrofluidic switch is used. It is demonstrated that through the coalescence and breakup of a liquid meniscus, DigSS operates for hundreds of cycles with a strain limit of detection of 0.0026. To facilitate integration, a linear optimization-based computer-aided design tool for the integrated DigSS (iDigSS) is created. Experimental validation shows that the iDigSS distinguishes a target strain-field profile from 35 of 36 theoretically distinguishable profiles without requiring signal processing. Human subject trials demonstrate the system's ability to differentiate a specific shoulder movement from five others and to wirelessly record wrist extension counts and durations.","PeriodicalId":100037,"journal":{"name":"Advanced Sensor Research","volume":"4 4","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adsr.202400146","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Complementary Cost-Effective Electrochemical Platforms for Point-Of-Use Biosensing (Adv. Sensor Res. 2/2025) 用于点生物传感的互补的具有成本效益的电化学平台（ad . Sensor Res. 2/2025）

IF 3.5

Advanced Sensor Research Pub Date : 2025-02-10 DOI: 10.1002/adsr.202570004

Mason Monaco, Marjon Zamani, Ava Sarram, Chao-Chi Kuo, Chathurika Abeyrathne, Miaosi Li, Ariel L. Furst

引用次数: 0

Issue Information (Adv. Sensor Res. 2/2025) 发布信息（Adv. Sensor Res. 2/2025）

IF 3.5

Advanced Sensor Research Pub Date : 2025-02-10 DOI: 10.1002/adsr.202570005

引用次数: 0