Sensors International最新文献_第2页

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

High-sensitivity terahertz metasensor for cervical cancer Diagnosis: Graphene modulation and XGBoost-Assisted optimization 用于宫颈癌诊断的高灵敏度太赫兹元传感器：石墨烯调制和xgboost辅助优化

Sensors International

Pub Date : 2025-08-17 DOI: 10.1016/j.sintl.2025.100350

Vaijayanthimala J , Vaishnavi K , Arun Kumar U , Dhivya R

Cervical cancer remains a major cause of mortality, particularly in low-resource settings where traditional cytology-based screening faces challenges such as limited infrastructure and trained personnel. To address this, we present a terahertz (THz) graphene-enhanced metasurface biosensor enabling rapid, label-free detection of cervical cancer biomarkers without complex sample preparation or expensive labs. Using finite element method (FEM) simulations, we demonstrate that tuning graphene's chemical potential from 0.1 to 0.9 eV significantly modulates peak absorption from 0.223 to 1.316, providing a wide dynamic range for sensitive detection across varying sample concentrations. The sensor exhibits robust angular stability, with absorption increasing from 0.546 to 1.306 as the incident light angle shifts from 0° to 80°, ensuring reliable performance without precise optical alignment. Refractive index sensing experiments reveal frequency shifts of 50 GHz and consistently high absorption (55.16 %–56.54 %), achieving a sensitivity of 300 GHz per refractive index unit (RIU) and a figure of merit of 12 RIU⁻¹. To enhance diagnostic accuracy, we integrated an XGBoost machine learning algorithm that analyzes the complex spectral data, achieving 86 % prediction accuracy with low error rates. This combination of advanced sensing and AI-assisted analysis offers a promising, cost-effective solution for cervical cancer screening in resource-limited environments.

宫颈癌仍然是导致死亡的一个主要原因，特别是在资源匮乏的环境中，传统的基于细胞学的筛查面临着基础设施和训练有素的人员有限等挑战。为了解决这个问题，我们提出了一种太赫兹（THz）石墨烯增强的超表面生物传感器，可以快速、无标记地检测宫颈癌生物标志物，而无需复杂的样品制备或昂贵的实验室。利用有限元方法（FEM）模拟，我们证明了将石墨烯的化学势从0.1至0.9 eV调节到0.223至1.316的峰值吸收，为不同样品浓度的敏感检测提供了广泛的动态范围。该传感器具有强大的角稳定性，当入射光角从0°变化到80°时，吸收从0.546增加到1.306，确保了可靠的性能，无需精确的光学对准。折射率传感实验显示频率漂移50 GHz，持续高吸收（55.16% - 56.54%），每个折射率单位（RIU）的灵敏度为300 GHz，品质系数为12 RIU−1。为了提高诊断的准确性，我们集成了一个XGBoost机器学习算法来分析复杂的光谱数据，实现了86%的预测准确率和低错误率。这种先进传感和人工智能辅助分析的结合为资源有限环境中的宫颈癌筛查提供了一种有前景的、具有成本效益的解决方案。

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引用次数: 0

A novel DHP-NH2 fluorescent dye for the determination of water content in organic solvents, rice, and aspirin: DFT calculations 一种新型DHP-NH2荧光染料，用于测定有机溶剂、大米和阿司匹林中的水分含量：DFT计算

Sensors International

Pub Date : 2025-08-09 DOI: 10.1016/j.sintl.2025.100349

Kittiporn Nakprasit , Panyakorn Taweechat , Pornthep Sompornpisut , Mongkol Sukwattanasinitt , Waroton Paisuwan , Anawat Ajavakom

A novel aminodihydropyridine derivative (DHP-NH₂) was synthesized from hydrazine via a tandem cyclotrimerization of methyl propiolate. DHP-NH₂ distinguishably exhibited either strong fluorescence in aprotic solvents or weak fluorescence in protic solvents. Its fluorescence quenching in THF and MeCN was quantitatively determined in the presence of water content, demonstrating the limit of detection (LOD) of 0.036 %wt and 0.014 %wt in THF and MeCN, respectively. The critical hydrogen-bonding interactions between water molecules and the amino group of DHP-NH₂ were found to stabilize its excited state, supporting a quenching mechanism as confirmed by DFT/TDDFT calculations. To apply this DHP-NH₂ probe for on-site analysis, smartphone-based photography together with the ImageJ program was employed for the moisture detection with the LOD of 0.28 %wt in MeCN. Moreover, the trace amount of moisture in organic solvents and solid samples (rice and aspirin) was successfully detected by using this developed method. In addition, we successfully immobilized the DHP derivative onto the cellulose paper to be used as a portable test strip for determining water content in MeCN by naked-eye detection.

以丙酸甲酯为原料，通过串联环三聚化反应合成了一种新的氨基二氢吡啶衍生物（DHP-NH2）。DHP-NH2在非质子溶剂中表现出强荧光，在质子溶剂中表现出弱荧光。在有水存在的情况下，定量测定了其在THF和MeCN中的荧光猝灭，其在THF和MeCN中的检出限（LOD）分别为0.036% wt和0.014% wt。发现水分子与DHP-NH2氨基之间的临界氢键相互作用稳定了其激发态，支持DFT/TDDFT计算证实的猝灭机制。为了将该DHP-NH2探针应用于现场分析，采用智能手机摄影结合ImageJ程序对men中的水分进行检测，LOD为0.28% wt。此外，该方法还成功地检测了有机溶剂和固体样品（大米和阿司匹林）中的微量水分。此外，我们成功地将DHP衍生物固定在纤维素纸上，作为裸眼检测MeCN含水量的便携式试纸条。

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引用次数: 0

Review of surface acoustic wave-based gas sensors 基于表面声波的气体传感器研究进展

Sensors International

Pub Date : 2025-07-23 DOI: 10.1016/j.sintl.2025.100348

Qiming Yang , Baile Cui , Jing Jin , Lina Cheng , Xufeng Xue , Yining Yin , Wen Wang

Surface acoustic wave (SAW) gas-based sensors have attracted significant attention as an emerging sensing technology due to their unique micro/nano-scale acoustic sensing structures and multi-physical field coupling mechanisms, which feature high sensitivity, rapid response, wide detection range, and lightweight. This paper systematically reviews the SAW gas sensing effect and mechanisms, sensing device design and fabrication, signal acquisition and processing circuits. Potential applications in fields such as renewable energy, aerospace, defense, industrial control, and intelligent manufacturing are also discussed, followed by an outlook on future development trends.

表面声波（SAW）气体传感器作为一种新兴的传感技术，由于其独特的微纳米尺度声传感结构和多物理场耦合机制，具有灵敏度高、响应速度快、探测范围宽、重量轻等特点而备受关注。本文系统地综述了声表面波气体传感的作用和机理、传感装置的设计与制造、信号采集与处理电路。讨论了该技术在可再生能源、航空航天、国防、工业控制、智能制造等领域的潜在应用，并对未来发展趋势进行了展望。

引用次数: 0

Zinc oxide-nickel oxide-copper oxide mixed nanocomposite thin films for ammonia gas sensor applications 用于氨气体传感器的氧化锌-氧化镍-氧化铜混合纳米复合薄膜

Sensors International

Pub Date : 2025-07-01 DOI: 10.1016/j.sintl.2025.100346

Sameena Begum , P. Nagaraju , S. Sarika Yadav , M. Swathi

Mixed metal oxides are emerging materials in the gas-sensing industry because of their superior gas-sensing characteristics. ZnO-based ternary mixed-metal oxide nanocomposites were sprayed on glass substrates using the spray pyrolysis method with optimized deposition conditions by changing NiO and CuO molar concentrations. Microstructural, topographical, and chemical studies of synthesised thin films were conducted using XRD, Raman spectroscopy, TEM, FESEM, and XPS, respectively. The XRD studies showed that ZnO is hexagonal, NiO particles are cubic, and CuO has monoclinic structures. Using the Scherrer formula, the crystallite sizes of the nanocomposites were calculated and found to be in the range of 8 nm–10 nm. FESEM results indicate that the synthesised films show a uniform distribution of particles with a good porous nature. Raman spectroscopy and TEM results agree with the studies of XRD. XPS analysis also confirms the formation of ZnO-NiO-CuO composites. Using a static method, gas sensing studies were conducted towards different ammonia concentrations, starting from 5 ppm to 20 ppm, at room temperature. A ternary composite sprayed with a molar concentration of 50 wt% ZnO – 30 wt% NiO- 20 wt% CuO showed superior gas sensing properties compared to other samples with response and recovery times of 59 s and 66 s, respectively, towards 5 ppm of ammonia at room temperature due to uniformly distributed spherical nanoparticles with a highly porous and rough surface made it strong interparticle interactions, making it ideal for ammonia sensing applications.

混合金属氧化物因其优越的气敏特性而成为气敏行业的新兴材料。采用喷雾热解法，通过改变NiO和CuO的摩尔浓度，优化沉积条件，制备了zno基三元混合金属氧化物纳米复合材料。利用XRD、拉曼光谱、TEM、FESEM和XPS对合成薄膜进行了微观结构、形貌和化学研究。XRD研究表明，ZnO为六方结构，NiO为立方结构，CuO为单斜结构。利用Scherrer公式计算了纳米复合材料的晶粒尺寸，发现晶粒尺寸在8 nm ~ 10 nm之间。FESEM结果表明，合成膜颗粒分布均匀，具有良好的多孔性。拉曼光谱和透射电镜的结果与XRD的研究结果一致。XPS分析也证实了ZnO-NiO-CuO复合材料的形成。使用静态方法，在室温下对不同的氨浓度（从5ppm到20ppm）进行了气敏研究。在室温条件下，以摩尔浓度为50 wt% ZnO - 30 wt% NiO- 20 wt% CuO喷涂的三元复合材料对5 ppm氨气的响应时间和恢复时间分别为59 s和66 s，这是由于均匀分布的球形纳米颗粒具有高度多孔性和粗糙的表面，使其具有强的颗粒间相互作用，使其成为理想的氨气传感应用。

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引用次数: 0

Wearable sensors in Industry 4.0: Preventing work-related musculoskeletal disorders 工业4.0中的可穿戴传感器：预防与工作相关的肌肉骨骼疾病

Sensors International

Pub Date : 2025-06-27 DOI: 10.1016/j.sintl.2025.100343

Morteza Jalali Alenjareghi, Firdaous Sekkay, Camelia Dadouchi, Samira Keivanpour

Work-related musculoskeletal disorders (WMSDs) are a global health and economic challenge, particularly in industrialized nations, accounting for up to 2 % of GDP losses due to disability and productivity reduction. Wearable sensors, driven by Industry 4.0 advancements, offer transformative potential for real-time ergonomic assessment and injury prevention. This systematic review analyzes 40 peer-reviewed studies (2013–2024) to evaluate the application of inertial measurement units (IMUs), electromyography (EMG) sensors, and pressure sensors in mitigating WMSD risks. Findings demonstrate that wearable technologies enhance workplace safety through real-time feedback, reducing ergonomic risks and improving productivity. Despite promising advancements, challenges such as scalability, user comfort, and data privacy persist. This review emphasizes the need for standardized protocols, ethical frameworks, and deeper integration with machine learning to optimize sensor accuracy and usability. Future research directions include advancing AI-driven predictive ergonomics, addressing privacy concerns, and improving sensor design for widespread industrial adoption. This study provides actionable insights to bridge the gap between academic research and practical deployment in diverse industrial settings.

与工作有关的肌肉骨骼疾病（WMSDs）是全球健康和经济挑战，特别是在工业化国家，由于残疾和生产力下降造成的GDP损失高达2%。在工业4.0的推动下，可穿戴传感器为实时人体工程学评估和伤害预防提供了革命性的潜力。本系统综述分析了40项同行评议的研究（2013-2024），以评估惯性测量单元（imu）、肌电（EMG）传感器和压力传感器在减轻WMSD风险方面的应用。研究结果表明，可穿戴技术通过实时反馈增强了工作场所的安全性，降低了人体工程学风险，提高了生产率。尽管取得了很大的进步，但诸如可扩展性、用户舒适度和数据隐私等挑战仍然存在。这篇综述强调了标准化协议、伦理框架以及与机器学习的更深层次集成的必要性，以优化传感器的准确性和可用性。未来的研究方向包括推进人工智能驱动的预测人体工程学，解决隐私问题，以及改进传感器设计以实现广泛的工业应用。本研究提供了可操作的见解，以弥合学术研究与不同工业环境中的实际部署之间的差距。

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引用次数: 0

Dual electrochemical approaches for rapid gonorrhea DNA diagnosis 双重电化学方法用于淋病DNA快速诊断

Sensors International

Pub Date : 2025-06-27 DOI: 10.1016/j.sintl.2025.100345

Abdulhadee Yakoh , Anaïs Charles , Panisak Boonamnaj , Sudkate Chaiyo , Sirirat Rengpipat

Gonorrhea, caused by Neisseria gonorrhoeae, requires rapid diagnostics, especially with the post-pandemic surge in cases. Traditional PCR methods need specialized equipment and trained personnel, underscoring the need for alternative tools. Electrochemical biosensors offer a sensitive, portable solution but have limited reporting for gonorrhea detection. This study develops two electrochemical methods: label-free (signal-off) and labeling (signal-on). The label-free approach uses two DNA sequences and the [Fe(CN)₆]^3-/^4- (potassium ferricyanide/ferrocyanide) redox indicator. The labeling method employs a molecularly amplified DNA sandwich assay with ferrocene-labeled helpers for signal amplification. The label-free method achieved a limit of detection (LOD) of 2.1 nM and a linear dynamic range (LDR) of 10–500 nM, while the labeling method showed an LOD of 4.8 pM and an LDR of 0.5–1000 nM. To enhance practicality, Near Field Communication (NFC)-enabled sensing was used during non-invasive urine sample testing, enabling real-time, wireless detection without sophisticated instruments. This confirmed the superior performance of the labeling method. Molecular dynamics simulations provided insights into structural dynamics, linking experimental data with computational models. This integrated approach highlights the importance of selecting methods based on sensitivity, cost, and ease of use, advancing gonorrhea DNA biosensing technologies.

由淋病奈瑟菌引起的淋病需要快速诊断，特别是在大流行后病例激增的情况下。传统的PCR方法需要专门的设备和训练有素的人员，因此需要替代工具。电化学生物传感器提供了一种敏感、便携的解决方案，但对淋病检测的报道有限。本研究开发了两种电化学方法：无标记（信号关闭）和标记（信号打开）。无标记方法使用两个DNA序列和[Fe(CN)6]3-/4-（铁氰化钾/亚铁氰化钾）氧化还原指示剂。标记方法采用分子扩增DNA夹心法，二茂铁标记辅助物用于信号扩增。无标记法的检出限（LOD）为2.1 nM，线性动态范围（LDR）为10 ~ 500 nM，而标记法的LOD为4.8 pM，线性动态范围（LDR）为0.5 ~ 1000 nM。为了提高实用性，在非侵入性尿样检测中使用了近场通信（NFC）传感技术，无需复杂的仪器即可实现实时无线检测。这证实了标记方法的优越性能。分子动力学模拟提供了对结构动力学的见解，将实验数据与计算模型联系起来。这种综合方法强调了基于灵敏度、成本和易用性选择方法的重要性，促进了淋病DNA生物传感技术的发展。

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引用次数: 0

Self-healing graphene-based composite hydrogels for motion Sensing: Source, fabrication, and applications in assistive technologies – A review 用于运动传感的自修复石墨烯基复合水凝胶：来源，制造和在辅助技术中的应用-综述

Sensors International

Pub Date : 2025-01-01 DOI: 10.1016/j.sintl.2025.100338

Munasir , Aditya Prapanca , Mohamad Fikri Aliansah , Frizky Audis Paramudhita , Nuhaa Faaizatunnisa , Muhammad Naufal Ariesta , Ahmad Taufiq

Graphene-based self-healing hydrogels represent a significant advancement in motion sensing technologies, particularly for assistive applications aimed at improving the quality of life for individuals with disabilities. The use of renewable biomass as a feedstock for graphene production addresses environmental concerns related to traditional fossil fuel-derived methods, promoting sustainability. Unlike previous reviews that focus on general graphene or hydrogel sensors, this review specifically explores self-healing graphene-based hydrogels for wearable strain sensing in assistive technologies, with an emphasis on structure–property–performance relationships and design considerations. The review examines the conductive properties of graphene and compares production techniques, highlighting their influence on sensor performance. The role of hydrogel polymers as substrates is also discussed, with a focus on how their chemical composition and physical properties affect graphene integration and the self-healing capabilities of the composites. Fabrication and characterization methodologies are contrasted to assess their impact on material performance and sensor efficacy. Practical applications are evaluated based on sensitivity, response time, durability, and long-term stability. The review concludes with a discussion on ongoing challenges and future research directions, aiming to further advance the development of biomass-derived graphene-based motion sensing technologies.

基于石墨烯的自修复水凝胶代表了运动传感技术的重大进步，特别是在旨在提高残疾人生活质量的辅助应用方面。使用可再生生物质作为石墨烯生产的原料，解决了与传统化石燃料衍生方法相关的环境问题，促进了可持续性。与以往的综述不同的是，本综述专门探讨了用于辅助技术中可穿戴应变传感的自修复石墨烯水凝胶，重点是结构-性能-性能关系和设计考虑。这篇综述考察了石墨烯的导电性能，并比较了生产技术，强调了它们对传感器性能的影响。还讨论了水凝胶聚合物作为衬底的作用，重点讨论了它们的化学成分和物理性质如何影响石墨烯的集成和复合材料的自修复能力。制造和表征方法进行对比，以评估其对材料性能和传感器效能的影响。根据灵敏度、响应时间、耐久性和长期稳定性对实际应用进行评估。最后，对当前面临的挑战和未来的研究方向进行了讨论，旨在进一步推动基于生物质的石墨烯运动传感技术的发展。

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引用次数: 0