Sensors International最新文献

A simple V-shaped microdevice for high-performance, wide-range vacuum and multifunctional sensing applications 一个简单的v形微器件，用于高性能，宽范围真空和多功能传感应用

Sensors International

Pub Date : 2025-12-04 DOI: 10.1016/j.sintl.2025.100370

Mohamed Hemid, Hamid Nawaz, Nouha Alcheikh

This study presents a V-shaped microelectromechanical systems (MEMS) device designed to harness mode localization and nonlinear dynamic effects for high-performance pressure and/or multifunctional sensing. Three V-shaped devices with different geometric configurations were fabricated and tested to evaluate their pressure-sensing performance and anti-crossing behavior under pressure. The latter is particularly beneficial for sensing applications, as it ensures the device remains unaffected by pressure variations, eliminating the need for an additional packaging system. By exploiting mode coupling between the frequencies of symmetric and anti-symmetric modes, the sensors exhibited significant frequency and amplitude shifts across a pressure range of 0.1–760 Torr. One device demonstrated a sensitivity of up to 508.4 ppm/Torr near ambient pressure, while another achieved an ultra-high sensitivity of 7460 ppm/Torr in the medium-vacuum range and 1205.4 ppm/Torr in the low-vacuum range, showcasing excellent sensitivity and linearity. The third device showed a robustness against pressure variations, with one mode selectively insensitive to pressure but responsive to other stimuli, enabling multimodal sensing capabilities. Moreover, the device has been tested under temperature environmental variation, showing a low sensitivity of 20.4 ppm/⁰C. Comparative analysis with existing MEMS pressure sensors underscores the proposed design's advantages in structural simplicity, compact size, and high sensitivity, particularly in low-vacuum environments, positioning it as a promising solution for advanced sensing applications in biomedical, environmental, and industrial domains.

本研究提出了一种v形微机电系统（MEMS）器件，旨在利用模式定位和非线性动态效应来实现高性能压力和/或多功能传感。制作了三种不同几何形状的v形装置，并对其进行了压敏性能和抗压过交性能测试。后者对于传感应用特别有益，因为它确保设备不受压力变化的影响，从而消除了对额外包装系统的需要。通过利用对称和反对称模式频率之间的模式耦合，传感器在0.1-760 Torr的压力范围内表现出显著的频率和幅度变化。其中一种器件在环境压力下的灵敏度高达508.4 ppm/Torr，而另一种器件在中真空范围内达到7460 ppm/Torr的超高灵敏度，在低真空范围内达到1205.4 ppm/Torr，具有出色的灵敏度和线性度。第三种装置显示出对压力变化的鲁棒性，其中一种模式对压力不敏感，但对其他刺激有反应，从而实现了多模态传感能力。此外，该装置已在温度环境变化下进行了测试，显示出20.4 ppm/0C的低灵敏度。与现有MEMS压力传感器的比较分析强调了所提出的设计在结构简单，尺寸紧凑和灵敏度高方面的优势，特别是在低真空环境中，将其定位为生物医学，环境和工业领域先进传感应用的有前途的解决方案。

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引用次数: 0

The role of chemisorption and physisorption in Fe-doped SnO2 acetone sensors 化学吸附和物理吸附在掺铁SnO2丙酮传感器中的作用

Sensors International

Pub Date : 2025-11-08 DOI: 10.1016/j.sintl.2025.100359

Yernar Shynybekov , Baktiyar Soltabayev , Almagul Mentbayeva , Amanzhol Turlybekuly

The gas sensing mechanism is one of the most important parameters of chemiresistive gas sensors, and distinguishing them opens the possibility of manipulating sensor performance. In this study, we introduced the concept of adsorption-type contribution to the gas-sensing performance that could further enhance the fundamental understanding of gas-sensing mechanisms and aid future sensor development. The proposed concept was applied for the examination of Fe-doped SnO₂ gas sensors ionic obtained through the successive layer adsorption and reaction (SILAR) method. The 0.5 mol.% Fe-doped SnO₂ sensor demonstrated a sensing response of 118 % to 25 ppm acetone at a relatively low optimal working temperature of 175 °C, and a temperature-induced p–n junction shift at around 50 °C. It had an LOD of approximately 250 ppb and a linear sensing range that extended to 25 ppm. Notably, the sensor had a response time of approximately 52 s and a recovery time of around 14 s. These results suggest the potential of Fe-doped SnO₂ sensors for acetone detection relevant to self-diagnosis and health monitoring.

气敏机理是化学电阻式气体传感器最重要的参数之一，研究其机理为控制传感器性能提供了可能。在本研究中，我们引入了吸附型对气敏性能贡献的概念，这可以进一步增强对气敏机制的基本理解，并有助于未来传感器的发展。将所提出的概念应用于通过连续层吸附反应（SILAR）法获得的掺铁SnO2气体传感器离子的检测。在相对较低的175℃的最佳工作温度下，掺铁量为0.5 mol.%的SnO2传感器对25 ppm丙酮的传感响应为118%，在50℃左右出现温度诱导的p-n结位移。它的LOD约为250 ppb，线性传感范围扩展到25 ppm。值得注意的是，传感器的响应时间约为52秒，恢复时间约为14秒。这些结果表明，铁掺杂SnO2传感器在丙酮检测方面具有与自我诊断和健康监测相关的潜力。

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引用次数: 0

The impact of cable length on the mobility performance of a remotely operated underwater vehicle (ROV) 电缆长度对遥控水下航行器（ROV）移动性能的影响

Sensors International

Pub Date : 2025-11-07 DOI: 10.1016/j.sintl.2025.100358

Sarawuth Srinakaew , Jenjira sukmanee , Ramil Kesvarakul

This study examines the impact of tether length on the mobility performance of a Remotely Operated Vehicle (ROV) in calm-water conditions. Field studies were executed at Laem Chabang Port, during which the ROV was utilized to navigate a 300-m trajectory while consistently documenting velocity and power usage. Results show that as the tether length increases, vehicle speed consistently decreases while power usage increases, indicating the effect of tether-induced hydrodynamic drag. Specifically, the velocity declined from 0.6706 m/s at the start to approximately 0.5500 m/s at 300 m, while power consumption rose from 0.7414 kW to around 0.778 kW. Linear regression was utilized to quantify these patterns, yielding two empirical models: V(x) = 0.6706−0.0003x and P(x) = 0.7414+(8 × 10−5)x, with x representing the tether length in meters. The models gave coefficients of determination of R² = 0.5834 and R² = 0.5965, respectively. This research presents one of the first empirical frameworks derived from in-field experimental trials to quantify performance degradation due to tether drag, thereby providing practical tools for energy budgeting and motion forecasting of stationary underwater vehicles in real-time operational planning. Unlike prior works relying mainly on simulations or analytical models, our study delivers regression-based predictive equations validated across different test sites. This contribution not only enhances operational readiness but also establishes a solid foundation for future investigations into nonlinear modeling and the development of adaptive control systems that incorporate tether dynamics to further improve predictive accuracy.

本研究考察了在平静水域条件下，系绳长度对远程操作车辆（ROV）移动性能的影响。在Laem Chabang港口进行了现场研究，在此期间，ROV被用于导航300米的轨迹，同时持续记录速度和功率使用情况。结果表明，随着系绳长度的增加，车辆的速度持续降低，而功率的使用则不断增加，这表明系绳引起的水动力阻力的影响。具体来说，速度从开始时的0.6706 m/s下降到300 m时的约0.5500 m/s，而功耗从0.7414 kW上升到0.778 kW左右。利用线性回归对这些模式进行量化，得到两个经验模型：V(x) = 0.6706−0.0003x和P(x) = 0.7414+(8 × 10−5)x，其中x以米为单位表示系绳长度。模型的决定系数分别为R2 = 0.5834和R2 = 0.5965。本研究提出了第一个从现场实验试验中得出的经验框架之一，用于量化系绳阻力导致的性能下降，从而为静止水下航行器在实时作战规划中的能量预算和运动预测提供实用工具。与以往主要依赖于模拟或分析模型的工作不同，我们的研究提供了基于回归的预测方程，并在不同的测试地点进行了验证。这一贡献不仅提高了作战准备，而且为未来非线性建模和自适应控制系统的研究奠定了坚实的基础，这些系统包括系绳动力学，以进一步提高预测精度。

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引用次数: 0

Simulation-driven dual-band Graphene–Silver terahertz metasurface biosensor integrated with machine learning for mode-resolved hemoglobin detection 模拟驱动的双波段石墨烯银太赫兹超表面生物传感器与机器学习集成，用于模式分辨血红蛋白检测

Sensors International

Pub Date : 2025-11-04 DOI: 10.1016/j.sintl.2025.100357

Gunasekaran Thangavel , V. Joseph Michael Jerard , K. Manivannan , A.N. Sasikumar , Vairaprakash Selvaraj , Manjunathan Alagarsamy

Accurate hemoglobin measurement is essential for diagnosing hematological disorders and monitoring cardiovascular health. This study introduces a terahertz metasurface biosensor combined with machine learning algorithms for rapid and non-invasive hemoglobin detection in clinical settings. The metasurface exhibits dual-band resonance in 2 THz regions, achieving a sensitivity of 450 GHz/RIU within a refractive index range of 1.34–1.43 RIU, with corresponding frequency shifts of 40 GHz and 30 GHz. Machine learning models, including Random Forest, Support Vector Machines, and Neural Networks, enhance the sensor's analytical capability. Across four clinical categories—normal, mild anemia, moderate anemia, and severe anemia—the models attain 96.5 percent classification accuracy, with recall and precision scores above 0.94. Ensemble learning reduces the root mean square error to 0.28 g/dL, while denoising methods increase the signal-to-noise ratio by 16.3 dB. The biosensor supports real-time analysis, requires minimal sample volume, and eliminates complex preparation, making it suitable for continuous hemoglobin monitoring and cardiovascular health management.

准确的血红蛋白测量对于诊断血液病和监测心血管健康至关重要。本研究介绍了一种结合机器学习算法的太赫兹超表面生物传感器，用于临床环境中的快速非侵入性血红蛋白检测。该超表面在2太赫兹区域呈现双频共振，在1.34-1.43 RIU的折射率范围内实现了450 GHz/RIU的灵敏度，相应的频移为40 GHz和30 GHz。机器学习模型，包括随机森林、支持向量机和神经网络，增强了传感器的分析能力。在四个临床类别中——正常、轻度贫血、中度贫血和严重贫血——该模型达到了96.5%的分类准确率，召回率和准确率得分高于0.94。集成学习将均方根误差降低到0.28 g/dL，而去噪方法将信噪比提高了16.3 dB。该生物传感器支持实时分析，需要最小的样本量，并消除了复杂的制备，使其适用于连续血红蛋白监测和心血管健康管理。

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引用次数: 0

Real-Time Fault Detection in Robotic Manufacturing Using High-Bandwidth Event Vision-Based Tactile Sensing 基于高带宽事件视觉触觉传感的机器人制造实时故障检测

Sensors International

Pub Date : 2025-11-01 DOI: 10.1016/j.sintl.2025.100355

Eslam Sherif , Akram Khairi , Hussain Sajwani , Abdullah Solayman , Abdallah Mohammad Alkilany , Ahmed Awadalla , Mohamad Halwani , Laith AbuAssi , Dewald Swart , Abdulla Ayyad , Yahya Zweiri

Early detection of machining faults is critical to avoid damage to high-value workpieces, prevent tool failure, and mitigate safety risks in automated manufacturing environments. While robotic automation has advanced across manufacturing, aerospace machining remains difficult to automate due to strict quality requirements and the lack of intelligent, real-time fault monitoring. During machining, skilled human operators rely on their tactile perception to detect subtle faults such as tool wear, misalignment, or insufficient feed force through vibration cues. Replicating this level of high-resolution tactile fidelity in robotic systems remains a key challenge. We present an event Vision-Based Tactile Sensor (EVBTS) that enables robots to perceive and interpret machining vibrations with a human-like sense of touch. The sensor uses an event camera to observe a deformable, marker-embedded membrane, capturing fine-grained spatiotemporal deformation patterns with microsecond latency. This high-fidelity, biomimetic signal stream allows robotic systems to detect faults in machining dynamics. We evaluate EVBTS on a robotic drilling setup for aerospace nutplate installation, spanning 12 distinct machining conditions. A lightweight convolutional neural network, integrated into a real-time pipeline with Exponential Moving Average (EMA) filtering, achieves 98.56% classification test accuracy, a 98.11% test F1 score, and

<

100 ms inference latency. This pipeline demonstrates closed-loop feedback, successfully halting faulty operations mid-process to prevent defects. These results demonstrate that EVBTS enables real-time, high-resolution fault detection and intervention, allowing for early correction, much like a skilled human operator, supporting safer, more precise, and autonomous manufacturing.

在自动化制造环境中，早期检测加工故障对于避免高价值工件的损坏、防止刀具故障和降低安全风险至关重要。虽然机器人自动化在整个制造业中取得了进步，但由于严格的质量要求和缺乏智能、实时故障监控，航空航天加工仍然难以实现自动化。在加工过程中，熟练的操作人员依靠他们的触觉感知来检测细微的故障，如刀具磨损、不对中或通过振动提示进给力不足。在机器人系统中复制这种高分辨率的触觉保真度仍然是一个关键的挑战。我们提出了一种基于事件视觉的触觉传感器（EVBTS），使机器人能够以类似人类的触觉感知和解释加工振动。该传感器使用事件相机来观察可变形的嵌入标记的膜，以微秒延迟捕捉细粒度的时空变形模式。这种高保真的仿生信号流允许机器人系统检测加工动力学中的故障。我们在航空航天nutplate安装的机器人钻孔装置上评估了EVBTS，跨越了12种不同的加工条件。将轻量级卷积神经网络集成到具有指数移动平均（EMA）滤波的实时管道中，实现了98.56%的分类测试准确率，98.11%的测试F1分数和100毫秒的推理延迟。该管道演示了闭环反馈，成功地在过程中停止错误操作以防止缺陷。这些结果表明，EVBTS可以实现实时，高分辨率的故障检测和干预，允许早期纠正，就像熟练的人工操作员一样，支持更安全，更精确和自主的制造。

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引用次数: 0

A novel system to record pulses, thrills, and bruit sounds generated by arteriovenous fistulas 一种记录动静脉瘘产生的脉冲、震颤和声音的新系统

Sensors International

Pub Date : 2025-10-31 DOI: 10.1016/j.sintl.2025.100356

Jessica Centracchio , Eliana Cinotti , Salvatore Parlato , Paolo Bifulco , Pasquale Zamboli , Rosalba Liguori , Giuseppe Longo , Massimo Punzi , Annalisa Liccardo , Francesco Bonavolontà , Giovanna Capolongo , Emilio Andreozzi

Arteriovenous fistulas (AVFs) are the preferred vascular accesses for hemodialysis and are made by anastomosing an artery and a vein. The arterial blood flowing into the anastomosed vein results in abnormal infrasonic and audible vibrations of venous walls, which produce tactile and audible sensations known as thrill and bruit sounds. Physical examination of AVFs is instrumental for early detection of stenoses, but it is operator-dependent. Several measurement systems have been proposed for quantitative analysis of bruit sounds, and only a few focused on thrill. However, none of these has demonstrated that the signals acquired correspond to the thrill and bruit sounds perceived by physicians.

This study presents, for the first time in literature, a novel AVF monitoring system that simultaneously records sphygmic pulses, thrills, and bruit sounds signals, also demonstrating that they share the same behaviors of tactile and audible sensations perceived by physicians. The proposed system is based on a small, non-invasive force sensor that captures both infrasonic and audible vibrations, and an ad hoc signal processing that accurately separates sphygmic pulses from thrills and bruit sounds. Experimental tests were carried out on 18 patients to assess two common behaviors observed during medical routine examinations. In particular, recordings were acquired on 3 measurement sites along the anastomosed vein, to verify the progressive amplitude reduction of thrill and bruit sounds from the anastomosis, and also their brisk amplitude reduction during vein occlusion tests. One-tailed Wilcoxon rank sum tests confirmed the expected amplitude reductions in both tests (p < 0.00001). In conclusion, the proposed AVF monitoring system accurately captures all vibrations produced by AVFs, which could be used to quantitatively evaluate the health status of patients and improve their surveillance.

动静脉瘘（AVFs）是血液透析首选的血管通道，由动脉和静脉吻合而成。流入吻合静脉的动脉血导致静脉壁产生异常的次声和可听振动，从而产生触觉和听觉感觉，即震颤声和杂音。avf的体格检查有助于早期发现狭窄，但这取决于操作者。已经提出了几种测量系统来定量分析物体的声音，但只有少数关注于刺激。然而，这些都没有证明所获得的信号与医生所感知到的兴奋和声音相对应。这项研究首次在文献中提出了一种新颖的AVF监测系统，该系统可以同时记录血压计、震颤和声音信号，并证明它们具有医生感知到的触觉和听觉的相同行为。该系统基于一个小型的、非侵入性的力传感器，可以捕获次声和可听振动，以及一个特殊的信号处理，可以准确地将脉搏从震颤和杂音中分离出来。对18例患者进行了实验测试，以评估医学常规检查中观察到的两种常见行为。特别地，我们在吻合静脉的3个测量点进行了记录，以验证吻合处的震颤音和bruit音的幅度逐渐降低，以及在静脉闭塞试验中它们的幅度急剧降低。单尾Wilcoxon秩和检验证实了两项检验的预期幅度降低（p < 0.00001）。综上所述，所提出的动静脉f监测系统能够准确捕获动静脉f产生的所有振动，可用于定量评估患者的健康状况，提高对患者的监测水平。

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引用次数: 0

A review on recent developments in materials and methodologies for metal oxide semiconductor liquefied petroleum gas sensors operating at room temperature 综述了室温下金属氧化物半导体液化气传感器材料和方法的最新进展

Sensors International

Pub Date : 2025-10-18 DOI: 10.1016/j.sintl.2025.100354

B.V. Sreenivasappa , A.R. Shashikala

In this paper, a review on recent developments in materials and methodologies for metal oxide semiconductor liquefied petroleum gas sensors operating at room temperature is presented. The goal of this review is to identify various types of gas sensors, LPG sensing materials, preparation and fabrication methods, characterization to study on the properties of the materials and analysis on parameters at room temperature. The review also investigates advanced hybrid nanostructured materials, elemental modifications and doping processes to improve LPG sensor performance. Surface reactivity of the sensing material could be accelerated by the use of appropriate catalyst. The morphology of a material can be improved by various methods, including changing the synthesis conditions, adding additives to alter the material properties and functionality by modifying its size, shape, and structure at the nanoscale. This review also emphasizes the role of suitable dopants in changing bandgap of the materials.

本文综述了室温下工作的金属氧化物半导体液化气传感器材料和方法的最新进展。本文综述了各种类型的气体传感器、液化石油气传感材料、制备和制造方法、表征、材料性能研究和室温参数分析。该综述还研究了先进的混合纳米结构材料、元素修饰和掺杂工艺，以提高LPG传感器的性能。使用合适的催化剂可以加速传感材料的表面反应性。材料的形态可以通过各种方法来改善，包括改变合成条件，添加添加剂来改变材料的性质和功能，通过在纳米尺度上改变其尺寸，形状和结构。本文还强调了合适的掺杂剂在改变材料带隙中的作用。

引用次数: 0

Development of a standalone software application for the simulation and optimization of surface plasmon resonance-based biosensors 开发用于模拟和优化基于表面等离子体共振的生物传感器的独立软件应用程序

Sensors International

Pub Date : 2025-10-16 DOI: 10.1016/j.sintl.2025.100352

Innocent Kadaleka Phiri , Mohssin Zekriti , Tijani Bounahmidi

Surface Plasmon Resonance (SPR) has emerged as a powerful biosensing technique, enabling real-time, label-free detection of target biomolecules with high sensitivity. However, the design and optimization of SPR-based biosensors remain challenging, requiring both theoretical expertise and access to specialized simulation tools. The growing demand for these biosensors highlights the need for advanced features and capabilities, such as automated computation of key biosensing metrics, user interactivity, real-time visualization, and dataset generation for machine learning applications. These capabilities are often lacking or scattered across different existing simulation platforms. To address this gap, we developed ‘SPR-Soft’, a new, standalone, PC-based software application for SPR biosensor simulation and optimization. Based on the Transfer Matrix Method (TMM), SPR-Soft features a user-friendly graphical interface that allows real-time input adjustments, live visualization of reflectivity/transmissivity curves, and automated computation of key performance metrics including sensitivity, Full Width at Half Maximum (FWHM), Detection Accuracy (DA), Figure of Merit (FoM), minimum reflectivity (R_min), and Field Enhancement (FE). Additionally, the software includes a dataset generation module to support machine learning-based applications in biosensor design. SPR-Soft's accuracy was validated through comparison with published simulation data and benchmarked against existing tools. A case study is also presented, demonstrating the software's capabilities by optimizing a gold-silver alloy-based SPR biosensor, achieving enhanced performance: sensitivity of 342°/RIU, FoM of 53.12/RIU, and R_min of 0.017 a.u. This development addresses long-standing limitations in biosensor modelling tools, improves research efficiency, enhances accessibility for non-expert users, and ultimately, supports the United Nations Sustainable Development Goals (SDGs #3 and #9).

表面等离子体共振（SPR）已经成为一种强大的生物传感技术，能够实时、无标记地检测目标生物分子，具有很高的灵敏度。然而，基于spr的生物传感器的设计和优化仍然具有挑战性，既需要理论知识，也需要专业的模拟工具。对这些生物传感器不断增长的需求凸显了对先进特性和功能的需求，例如关键生物传感指标的自动计算、用户交互性、实时可视化和机器学习应用的数据集生成。这些功能通常缺乏或分散在不同的现有仿真平台上。为了解决这一差距，我们开发了“SPR- soft”，这是一种新的，独立的，基于pc的软件应用程序，用于SPR生物传感器模拟和优化。基于传递矩阵法（TMM）， SPR-Soft具有用户友好的图形界面，允许实时输入调整，反射率/透射率曲线的实时可视化，以及关键性能指标的自动计算，包括灵敏度，半最大全宽度（FWHM），检测精度（DA），优异值（FoM），最小反射率（Rmin）和场增强（FE）。此外，该软件还包括一个数据集生成模块，以支持生物传感器设计中基于机器学习的应用。通过与已发布的仿真数据进行比较，并与现有工具进行基准测试，验证了SPR-Soft的准确性。本文还介绍了一个案例研究，通过优化基于金银合金的SPR生物传感器，展示了该软件的功能，实现了更高的性能：灵敏度为342°/RIU， FoM为53.12/RIU， Rmin为0.017 a.u。该开发解决了生物传感器建模工具长期存在的局限性，提高了研究效率，增强了非专业用户的可访问性，并最终支持了联合国可持续发展目标（SDGs #3和#9）。

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引用次数: 0

Design and implementation of a microwave microstrip sensor with convolutional neural network for real-time milk spoilage detection 基于卷积神经网络的微波微带传感器的设计与实现

Sensors International

Pub Date : 2025-10-16 DOI: 10.1016/j.sintl.2025.100353

Ali Khoshchehre , Mohammad Amir Sattari , Umer Hameed Shah , Gholam Hossein Roshani

Milk spoilage detection plays a pivotal role in safeguarding food safety and minimizing waste within the dairy sector, although conventional chemical assays remain labor-intensive, invasive, and expensive. The present investigation introduces a non-invasive microwave microstrip sensor coupled with a convolutional neural network (CNN) for real-time assessment of milk spoilage progression. The sensor, modeled and optimized using Advanced Design System (ADS) software to exhibit dual passbands (1807–2466 MHz and 3604–4426 MHz), was fabricated on an RT/Duroid 4003 substrate and evaluated using 10 commercial milk samples (3 % fat) procured sequentially over 10 days and maintained at 21 °C. Measurements of the S21 transmission parameter (101 frequency points per spectrum, with five replicates per sample yielding 50 spectra in total) demonstrated a substantial amplitude disparity, notably at 2166 MHz, where the difference between the freshest (day 10) and most spoiled (day 1) samples attained 7.02 dB—equivalent to approximately 105 times the mean standard deviation (0.067 dB)—facilitating robust differentiation of dielectric alterations attributable to microbial degradation. A one-dimensional CNN was trained on preprocessed spectral data augmented fivefold with white Gaussian noise using five variable standard deviations (σ = 0.20–0.60 dB) to simulate real-world measurement fluctuations, expanding the dataset from 50 to 250 spectra and attaining a training accuracy of 95.5 % and a validation accuracy of 90 %. This hybrid methodology surpasses traditional approaches in terms of rapidity and non-destructiveness, providing a viable framework for milk quality surveillance with applicability to other perishable commodities.

尽管传统的化学检测仍然是劳动密集型、侵入性和昂贵的，但牛奶腐败检测在保障食品安全和最大限度地减少乳制品行业的浪费方面发挥着关键作用。本研究介绍了一种非侵入性微波微带传感器与卷积神经网络（CNN）相结合，用于实时评估牛奶变质过程。该传感器使用Advanced Design System （ADS）软件建模和优化，具有双通带（1807-2466 MHz和3604-4426 MHz），在RT/Duroid 4003衬底上制造，并使用10个商业牛奶样品（3%脂肪）进行评估，这些样品在10天内连续获得，并保持在21°C。S21传输参数的测量（每个频谱101个频率点，每个样品5次重复，总共产生50个光谱）显示了巨大的幅度差异，特别是在2166 MHz，其中最新鲜（第10天）和最变质（第1天）样品之间的差异达到7.02 dB -相当于平均标准偏差（0.067 dB）的105倍-促进了可由微生物降解引起的介电变化的强大区分。利用5个变量标准差（σ = 0.20-0.60 dB）加5倍高斯白噪声的预处理光谱数据对一维CNN进行训练，模拟实际测量波动，将数据集从50个光谱扩展到250个光谱，训练精度达到95.5%，验证精度达到90%。这种混合方法在快速和非破坏性方面超越了传统方法，为牛奶质量监测提供了一个可行的框架，适用于其他易腐商品。

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引用次数: 0

Multimetallic graphene-coated THz metasurface biosensor for high-sensitivity hCG detection in pregnancy testing: A simulation study 多金属石墨烯涂层太赫兹超表面生物传感器用于妊娠试验中hCG的高灵敏度检测：模拟研究

Sensors International

Pub Date : 2025-09-11 DOI: 10.1016/j.sintl.2025.100351

K. Vijayakumar , S. Subha , N.K. Anushkannan , Kumaravel Kaliaperumal , U. Arun Kumar

Conventional pregnancy testing methods face significant limitations including low sensitivity, cross-reactivity issues, and requirement for sophisticated laboratory equipment, particularly in resource-limited settings. This research introduces an innovative terahertz (THz) biosensor using a graphene-metallic hybrid metasurface architecture to improve pregnancy detection by optical sensing of human chorionic gonadotropin (hCG) indicators. The sensor demonstrates remarkable performance with a maximum sensitivity of 1000 GHz/RIU achieved at the optimal resonant frequency of 0.309 THz within the 0.1–0.55 THz frequency band, corresponding to a refractive index of 1.343 RIU. The frequency-dependent sensitivity analysis reveals that the maximum sensitivity of 1000 GHz/RIU is achieved at 0.309 THz, where the electromagnetic field enhancement reaches its peak value. This optimal operating point corresponds to the fundamental resonance mode of the hybrid metasurface structure, where the coupling between the central graphene resonator and the surrounding metallic rings creates the strongest field localization. The sensitivity decreases progressively at frequencies away from this resonant peak, with values of 500 GHz/RIU at 0.310 THz and 200 GHz/RIU at 0.311 THz, demonstrating the critical importance of precise frequency tuning for optimal sensor performance. Comparative analysis shows competitive or superior performance against existing biosensor designs, offering significant potential for point-of-care pregnancy testing applications with enhanced sensitivity, real-time detection capability, and reduced sample preparation requirements.

传统的妊娠检测方法面临着显著的局限性，包括低灵敏度、交叉反应性问题，以及对复杂实验室设备的要求，特别是在资源有限的情况下。本研究介绍了一种创新的太赫兹（THz）生物传感器，该传感器采用石墨烯-金属混合超表面结构，通过光学传感人类绒毛膜促性腺激素（hCG）指标来改进妊娠检测。在0.1-0.55 THz频段内，在0.309 THz的最佳谐振频率下，传感器的最大灵敏度达到1000 GHz/RIU，对应的折射率为1.343 RIU。频率相关的灵敏度分析表明，在0.309太赫兹时达到1000 GHz/RIU的最大灵敏度，此时电磁场增强达到峰值。这个最佳工作点对应于混合超表面结构的基本共振模式，其中中心石墨烯谐振器与周围金属环之间的耦合产生最强的场局域化。在远离该谐振峰的频率处，灵敏度逐渐降低，在0.310太赫兹处灵敏度为500 GHz/RIU，在0.311太赫兹处灵敏度为200 GHz/RIU，这表明精确的频率调谐对于优化传感器性能至关重要。对比分析显示，与现有的生物传感器设计相比，具有竞争力或优越的性能，具有更高的灵敏度、实时检测能力和更低的样品制备要求，为即时妊娠检测应用提供了巨大的潜力。

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引用次数: 0