Advanced Sensor Research最新文献_第3页

Issue Information (Adv. Sensor Res. 9/2026) 发布信息（Adv. Sensor Res. 9/2026）

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Advanced Sensor Research Pub Date : 2026-08-31 DOI: 10.1002/adsr.70201

引用次数: 0

Discrimination of Truffles and Truffle Oils by a Metal–Organic-Framework-Based Electronic Nose 金属-有机框架电子鼻对松露和松露油的鉴别

IF 5

Advanced Sensor Research Pub Date : 2026-08-31 DOI: 10.1002/adsr.70198

Salih Okur, Taher Al Najjar, Qiao Wang, Anemar Bruno Kanj, Hans-Georg Pfüller, Ulrich Stobbe, Markus Antonius Mayer, Christof Wöll, Lars Heinke

{"title":"Discrimination of Truffles and Truffle Oils by a Metal–Organic-Framework-Based Electronic Nose","authors":"Salih Okur, Taher Al Najjar, Qiao Wang, Anemar Bruno Kanj, Hans-Georg Pfüller, Ulrich Stobbe, Markus Antonius Mayer, Christof Wöll, Lars Heinke","doi":"10.1002/adsr.70198","DOIUrl":"https://doi.org/10.1002/adsr.70198","url":null,"abstract":"Truffles are valuable gourmet fungi with complex aromas, but their scarcity and high cost make them frequent targets of adulteration, often through the use of synthetic compounds such as dimethyl sulfide (DMS). Current laboratory-based detection methods are accurate but impractical for field applications. In this study, a portable electronic nose (e-nose) system based on quartz crystal microbalance (QCM) sensors coated with seven different chiral and achiral metal-organic framework (MOF) thin films are presented. These films are grown directly on the substrate, mainly in a layer-by-layer fashion, resulting in surface-mounted MOFs (SURMOFs). The MOF-e-nose successfully classifies various fresh truffles as well as self-made and commercial truffle oils. In addition, oil samples adulterated with DMS are clearly distinguished from authentic truffle oils. Using simple machine learning algorithms such as k-nearest neighbors (kNN) and linear discriminant analysis (LDA), the sensor array achieves classification accuracies of up to 100%. The study shows that a MOF-based e-nose can be a fast, low-cost, and reliable tool for truffle authentication and quality control.","PeriodicalId":100037,"journal":{"name":"Advanced Sensor Research","volume":"5 9","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adsr.70198","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148860216","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 Optimized Electrochemical Biosensor for Real-Time Monitoring of Lactate in Human Saliva With Enhanced Sensitivity, Stability, and Reproducibility 一种优化的电化学生物传感器，用于实时监测人唾液中的乳酸，具有更高的灵敏度，稳定性和可重复性

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Advanced Sensor Research Pub Date : 2026-08-31 DOI: 10.1002/adsr.70199

Gylxhane Kastrati, Leif Riemenschneider, Torsten Sterzenbach, Yutong Wu, Carballo Torres Dimas, Luis Antonio Panes-Ruiz, Abdallh Herbawe, Michael Geiger-Hoffmann, Kristin Hille, Stephanie Klinghammer, Christian Hannig, Gianaurelio Cuniberti

{"title":"An Optimized Electrochemical Biosensor for Real-Time Monitoring of Lactate in Human Saliva With Enhanced Sensitivity, Stability, and Reproducibility","authors":"Gylxhane Kastrati, Leif Riemenschneider, Torsten Sterzenbach, Yutong Wu, Carballo Torres Dimas, Luis Antonio Panes-Ruiz, Abdallh Herbawe, Michael Geiger-Hoffmann, Kristin Hille, Stephanie Klinghammer, Christian Hannig, Gianaurelio Cuniberti","doi":"10.1002/adsr.70199","DOIUrl":"https://doi.org/10.1002/adsr.70199","url":null,"abstract":"Non-invasive lactate monitoring in saliva holds considerable potential for disease diagnostics and personalized oral healthcare. However, the complex salivary matrix, characterized by high protein content, pellicle formation, and elevated viscosity, poses major challenges for electrochemical biosensors, including biofouling, signal interference, and limited stability. Here, we present an electrochemical lactate biosensor rationally engineered for reliable operation in untreated human saliva. A multilayer surface architecture comprising Prussian Blue, lactate oxidase, bovine serum albumin (BSA), and a zwitterionic polydopamine–MPC (pDA/MPC) coating minimizes nonspecific adsorption while preserving substrate accessibility. The optimized sensor exhibits a sensitivity of −0.48 µA/ mM−1 and a linear range up to 2.5 mM in phosphate buffer at an operating potential of +0.055 V. In untreated human saliva, the sensor accurately quantified endogenous lactate and detected up to an additional 1 mM lactate before reaching saturation, covering the physiologically relevant concentration range. The multilayer architecture further provided stable and reproducible responses with negligible interference from glucose, uric acid, and ascorbic acid. Cytotoxicity studies using human gingival fibroblasts confirmed the biocompatibility of the modified sensor surface. These results demonstrate that rational multilayer surface engineering enables robust electrochemical lactate sensing in saliva and represents a promising strategy for future intraoral biosensing applications.","PeriodicalId":100037,"journal":{"name":"Advanced Sensor Research","volume":"5 9","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adsr.70199","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148860218","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

Smart Sensing Systems For Agricultural Plant Health Monitoring: Current State and Prospects 智能传感系统用于农业植物健康监测：现状与展望

IF 5

Advanced Sensor Research Pub Date : 2026-08-25 DOI: 10.1002/adsr.70196

Frank Efe Erukainure, Abhilash K. Chandel

{"title":"Smart Sensing Systems For Agricultural Plant Health Monitoring: Current State and Prospects","authors":"Frank Efe Erukainure, Abhilash K. Chandel","doi":"10.1002/adsr.70196","DOIUrl":"https://doi.org/10.1002/adsr.70196","url":null,"abstract":"Timely and reliable assessment of plant health is essential for resilient and sustainable agriculture, yet diagnostic practice remains divided between accurate but laboratory-bound assays and emerging field-deployable technologies. Herein, we adopt a plant-centric and systems-level perspective to synthesize advances in smart sensing for plant health monitoring reported between 2000 and 2026. Rather than surveying individual devices in isolation, we organize the literature around how sensing technologies are fabricated, integrated, and translated into actionable agronomic insights. Our synthesis reveals a clear shift toward multimodal, minimally invasive sensing architectures that combine material and fabrication innovations with contact and non-contact modalities spanning organ, canopy, and landscape scales. We find that the most impactful progress arises not from individual sensors alone, but from integrated pipelines that couple sensing hardware with edge intelligence, cross-scale data fusion, and explainable analytics. Furthermore, persistent barriers, including calibration transfer, long-term stability, power autonomy, dataset bias, and cybersecurity, continue to impede widespread adoption. Based on these findings, we outline design principles and research priorities needed to accelerate translation, emphasizing standardized validation against biological benchmarks, energy-autonomous and environmentally responsible sensor systems, and artificial intelligence (AI) frameworks capable of robust generalization across crops and environments. Looking ahead, we argue that plant health monitoring will increasingly be defined by closed-loop systems that directly link plant physiological or pathological signals to adaptive management, positioning smart sensing as a cornerstone of data-driven and climate-resilient agriculture.","PeriodicalId":100037,"journal":{"name":"Advanced Sensor Research","volume":"5 8","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adsr.70196","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148849132","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

Front Cover: A Sensor-to-Algorithm Framework for Respiration Monitoring: Stretchable Strain Sensors Coupled With Machine Learning Feature Optimization (Adv. Sensor Res. 8/2026) 封面：呼吸监测的传感器到算法框架：可拉伸应变传感器与机器学习特征优化相结合（ad . Sensor Res. 8/2026）

IF 5

Advanced Sensor Research Pub Date : 2026-08-21 DOI: 10.1002/adsr.70197

Youngjun Lee, Seokkyoon Hong, Jinheon Jeong, Dong Rip Kim, Chi Hwan Lee, Rachel K. Surowiec

引用次数: 0

Hybrid-Printed Single-ChemFET Electronic Nose Enabled by Machine Learning 基于机器学习的混合打印单化学场效应晶体管电子鼻

IF 5

Advanced Sensor Research Pub Date : 2026-08-21 DOI: 10.1002/adsr.70194

Hankun Yang, Martin Sommer, Surya Abhishek Singaraju, Pooja Arya, Gabriel Cadilha Marques, Jan Fessler, Jasmin Aghassi-Hagmann, Uli Lemmer

{"title":"Hybrid-Printed Single-ChemFET Electronic Nose Enabled by Machine Learning","authors":"Hankun Yang, Martin Sommer, Surya Abhishek Singaraju, Pooja Arya, Gabriel Cadilha Marques, Jan Fessler, Jasmin Aghassi-Hagmann, Uli Lemmer","doi":"10.1002/adsr.70194","DOIUrl":"https://doi.org/10.1002/adsr.70194","url":null,"abstract":"We present an electronic nose sensor based on a single chemically sensitive field-effect transistor (ChemFET). A novel hybrid printing process that combines the advantages of inkjet and aerosol jet printing is used to fabricate the ChemFET with a semiconducting sub-10 nm In2O3 thin-film channel. The sensor was first electrically characterized, showing an on/off ratio of 2.3 · 105 and a threshold voltage of 12.67 V. Three gases at 100 ppm concentration—isopropyl alcohol, benzene, and carbon monoxide–are used to test the sensing capability. We show that a single ChemFET generates gas-specific features across different drain-source (VDS) and gate-source voltages (VGS). Two classification algorithms, linear discriminant analysis (LDA) and random forest (RF), are evaluated using leave-one-out cross-validation. Both algorithms can classify reference air and carbon monoxide without errors, but RF classifies isopropyl alcohol and benzene with higher precision and recall. The feature importance analysis reveals a correlation with VGS and not with VDS. After feature importance-based feature selection, LDA and RF achieve F1-scores of 0.85 and 0.94, respectively. Our findings indicate that the printed single ChemFET-based sensor is a promising candidate for gas-sensing applications.","PeriodicalId":100037,"journal":{"name":"Advanced Sensor Research","volume":"5 8","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adsr.70194","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148784582","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

Repurposing a Lipid Droplet-Associated Algal Protein as a Biosensor for Phosphatidic Acid 脂滴相关藻蛋白作为磷脂酸生物传感器的重新利用

IF 5

Advanced Sensor Research Pub Date : 2026-08-14 DOI: 10.1002/adsr.70185

Bilge Ercan, Nian Kee Tan, Julia Lin, Jingyao You, Stephen M. Butler, Katrina A. Jolliffe

{"title":"Repurposing a Lipid Droplet-Associated Algal Protein as a Biosensor for Phosphatidic Acid","authors":"Bilge Ercan, Nian Kee Tan, Julia Lin, Jingyao You, Stephen M. Butler, Katrina A. Jolliffe","doi":"10.1002/adsr.70185","DOIUrl":"https://doi.org/10.1002/adsr.70185","url":null,"abstract":"Phosphatidic acid (PA) is an essential signaling lipid in eukaryotic cells. Despite its importance, biosensors recognizing PA-rich membranes are in short supply, partly because there is no known consensus motif for detecting PA. Here, we demonstrate that a lipid droplet-associated protein domain from Chlamydomonas reinhardtii can be repurposed as a biosensor for PA-rich lipid membranes. We found that the lipid-binding domain of Delayed in TAG Hydrolysis 1 (DTH1LBD) of Chlamydomonas reinhardtii binds to PA-rich phospholipid bilayers in vitro. Cysteine mutagenesis coupled with covalent incorporation of various environment-sensitive fluorophores and fluorescent confocal microscopy imaging of PA-containing giant unilamellar vesicles showed that the N-terminal amphipathic helices of DTH1LBD are sufficient to recognize PA-containing membranes. Accordingly, we observed that binding of N-terminal amphipathic helices to PA-enriched membranes is sensitive to PA-induced membrane lipid packing defects. Our findings demonstrate that the N-terminal amphipathic helices of DTH1LBD recognize PA-rich membranes through lipid headgroup and membrane packing defects imparted by the unique structure of PA. Thus, the amino acid sequences forming the N-terminal amphipathic helices of DTH1LBD could potentially inform the design of next-generation PA-binding peptides.","PeriodicalId":100037,"journal":{"name":"Advanced Sensor Research","volume":"5 8","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adsr.70185","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148753496","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

Quasi-Standard Platform of AlScN Piezoelectric Integrated MEMS Technology (PIMT) For Multi-Project Wafer Fabrication 用于多项目晶圆制造的AlScN压电集成MEMS技术准标准平台

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Advanced Sensor Research Pub Date : 2026-08-14 DOI: 10.1002/adsr.70191

Yongquan Su, Yuqiang Hu, Xingwang Zhu, Wenli Xue, Hao Huang, Yichen Liu, Jiachen Han, Anna Li, Cheng Zhang, Wanzhu Qiao, Jiaqi Huang, Peng Ding, Qianying Sun, Huan Liu, Tao Wu, Lihao Wang, Yang Wang, Hao Chen, Zhenyu Wu

{"title":"Quasi-Standard Platform of AlScN Piezoelectric Integrated MEMS Technology (PIMT) For Multi-Project Wafer Fabrication","authors":"Yongquan Su, Yuqiang Hu, Xingwang Zhu, Wenli Xue, Hao Huang, Yichen Liu, Jiachen Han, Anna Li, Cheng Zhang, Wanzhu Qiao, Jiaqi Huang, Peng Ding, Qianying Sun, Huan Liu, Tao Wu, Lihao Wang, Yang Wang, Hao Chen, Zhenyu Wu","doi":"10.1002/adsr.70191","DOIUrl":"https://doi.org/10.1002/adsr.70191","url":null,"abstract":"Piezoelectric MEMS devices are a key branch of MEMS technology, valued for high integration, miniaturization, stability, and reliability. However, existing standardized manufacturing struggles to meet diverse design and R&D needs. This paper presents an 8-inch quasi-standard Piezoelectric Integrated MEMS Technology (PIMT) platform for Multi-Project Wafer (MPW) fabrication, integrating core processes and supporting additional ones to adapt to different device requirements. After three tape-out iterations, the platform now centers on three core processes with supplementary ones. This paper details all the process modules, process windows, and design rules in PIMT. Through process control monitoring (PCM), it ensures that key process steps are accurately processed. It also presents the key performance of different types of MEMS devices produced by the PIMT platform in three rounds and elaborates on the influence of the most influential process steps on device performance. This platform accelerates R&D prototyping efficiently.","PeriodicalId":100037,"journal":{"name":"Advanced Sensor Research","volume":"5 8","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adsr.70191","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148753497","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

Cortisol Recognition by a Conformationally Responsive DNA Aptamer 构象反应性DNA适体对皮质醇的识别

IF 5

Advanced Sensor Research Pub Date : 2026-08-06 DOI: 10.1002/adsr.70190

Lakshitha Jasin Arachchige, Nayoon Kwon, Isoo Youn, Chang-Seuk Lee, Tiffany R. Walsh

{"title":"Cortisol Recognition by a Conformationally Responsive DNA Aptamer","authors":"Lakshitha Jasin Arachchige, Nayoon Kwon, Isoo Youn, Chang-Seuk Lee, Tiffany R. Walsh","doi":"10.1002/adsr.70190","DOIUrl":"https://doi.org/10.1002/adsr.70190","url":null,"abstract":"Cortisol-binding DNA aptamers have emerged as promising recognition elements for non-invasive cortisol biosensing. However, the molecular basis of cortisol recognition and signal generation remains poorly understood. Here, we investigate the structural dynamics and cortisol binding behavior of the widely used 85-nucleotide DNA aptamer, Apt15-1, using all-atom molecular dynamics simulations. The free aptamer supports two distinct conformational states, an open-like state and a compact closed-like state, which differ mainly in their tertiary structural organization while preserving the core secondary structure. These two conformations also exhibit distinct local ionic environments, suggesting a possible connection between conformational redistribution and signal generation in a biosensing context. As a result, cortisol binding is strongly dependent on aptamer conformation, and specific binding geometries influence the transition between the two states, thereby biasing the pre-existing conformational equilibrium. Such redistribution of the conformational ensemble offers a plausible molecular basis for signal generation by altering the local ionic environment at the sensor interface. NMR measurements support the molecular dynamics simulation predictions, indicating a stable binding interaction between cortisol and the 85mer. These findings demonstrate how the full-length 85mer aptamer architecture couples cortisol recognition to conformational and ionic changes relevant to signal generation.","PeriodicalId":100037,"journal":{"name":"Advanced Sensor Research","volume":"5 8","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adsr.70190","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148752824","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

Gold Nano Biosensing Technologies for Early Breast Cancer Diagnosis: Recent Progress and Future Perspectives 早期乳腺癌诊断的金纳米生物传感技术：最新进展和未来展望

IF 5

Advanced Sensor Research Pub Date : 2026-08-06 DOI: 10.1002/adsr.70189

Akanksha Pawar, Muskan Leharwani, Deena Mohammed Bukhary, Garima Gupta, Khang Wen Goh, Amirhossein Sahebkar, Prashant Kesharwani

{"title":"Gold Nano Biosensing Technologies for Early Breast Cancer Diagnosis: Recent Progress and Future Perspectives","authors":"Akanksha Pawar, Muskan Leharwani, Deena Mohammed Bukhary, Garima Gupta, Khang Wen Goh, Amirhossein Sahebkar, Prashant Kesharwani","doi":"10.1002/adsr.70189","DOIUrl":"https://doi.org/10.1002/adsr.70189","url":null,"abstract":"Breast cancer remains one of the foremost causes of cancer-related mortality among women worldwide, where survival outcomes are strongly dictated by the timeliness and precision of diagnosis. In this review, we present gold nanomaterial-driven biosensors as a transformative frontier in ultrasensitive breast cancer detection. Owing to their unique physicochemical attributes including localized surface plasmon resonance, superior electrical conductivity, large surface-to-volume ratio, and robust Au-S surface chemistry. Gold nanostructures enable stable biomolecule immobilization, accelerated electron transfer, and powerful signal amplification across multiple sensing modalities. We comprehensively examine recent advances in gold nanostructure-based electrochemical, SPR, SERS, fluorescent, and dual-mode biosensors, highlighting their capability to detect clinically significant biomarkers such as HER2, CA15-3, CEA, CD44, miR-122, miR-21, BRCA1/2, BIRC5 mRNA, FEN1, circulating tumor cells, and tumor-derived exosomes. Particular attention is given to the structural diversity of gold nanomaterials including nanoparticles, nanorods, nanostars, and core-shell architectures, which enables finely tunable plasmonic and electrochemical performance, achieving femtomolar to attomolar detection limits. Collectively, this review underscores the strategic role of gold nanomaterials as the central nano structural backbone of next-generation biosensing systems, paving the way toward minimally invasive, real-time, and precision breast cancer diagnostics with strong translational potential.","PeriodicalId":100037,"journal":{"name":"Advanced Sensor Research","volume":"5 8","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adsr.70189","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148752787","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