Surface acoustic wave (SAW) sensors are widely employed for detecting dimethyl methylphosphonate (DMMP, a simulant of the chemical warfare agent sarin) due to their wireless and passive monitoring capability, digital output, and cost-effectiveness. Zirconium dioxide (ZrO2) nanoparticles are considered one of the most promising sensing materials for DMMP detection owing to their unique and strong surface interactions with phosphorus-containing compounds, as well as their excellent chemical and thermal stability. However, the practical deployment of ZrO2 SAW sensors faces significant challenges, as atmospheric humidity severely degrades their performance, causing substantial sensitivity drift and even polarity reversal. This work reports a strategy involving the modification of ZrO2 nanoparticle surfaces with hydrophobic functional groups (-Si(CH3)3). This approach successfully transformed the inherently superhydrophilic ZrO2 material (water contact angle, WCA = 19°) into a hydrophobic state (WCA = 136°). For SAW sensors based on this hydrophobized ZrO2, the initial frequency drift induced by humidity was suppressed by 92.6 at 85% relative humidity (RH). More importantly, across the dynamic humidity range of 20-85% RH, the DMMP response remained stable at approximately -325 Hz/ppm (fluctuation <6%). This performance is significantly superior to that of unmodified ZrO2 SAW sensors, whose responses fluctuated drastically between -1030 Hz/ppm and +1141 Hz/ppm under identical conditions. The mechanisms underlying the humidity-induced sensitivity drift in ZrO2 SAW sensors were elucidated using in situ infrared absorption spectroscopy and X-ray photoelectron spectroscopy techniques. This study not only provides a straightforward strategy for imparting hydrophobicity to ZrO2 but also offers novel insights for addressing the issue of frequency drift in SAW sensors caused by atmospheric moisture.
{"title":"Achieving Humidity-Independent Dimethyl Methylphosphonate Response in Surface Acoustic Wave Sensors through ZrO2 Surface Hydrophobization.","authors":"Yihao Guo,Shengyu Wen,Xinhui Gu,Jiangping Lei,Ersen Hu,Jianhui Cao,Renxing Wu,Hui Chen,Lin Shi,Jian Zhou","doi":"10.1021/acssensors.6c00223","DOIUrl":"https://doi.org/10.1021/acssensors.6c00223","url":null,"abstract":"Surface acoustic wave (SAW) sensors are widely employed for detecting dimethyl methylphosphonate (DMMP, a simulant of the chemical warfare agent sarin) due to their wireless and passive monitoring capability, digital output, and cost-effectiveness. Zirconium dioxide (ZrO2) nanoparticles are considered one of the most promising sensing materials for DMMP detection owing to their unique and strong surface interactions with phosphorus-containing compounds, as well as their excellent chemical and thermal stability. However, the practical deployment of ZrO2 SAW sensors faces significant challenges, as atmospheric humidity severely degrades their performance, causing substantial sensitivity drift and even polarity reversal. This work reports a strategy involving the modification of ZrO2 nanoparticle surfaces with hydrophobic functional groups (-Si(CH3)3). This approach successfully transformed the inherently superhydrophilic ZrO2 material (water contact angle, WCA = 19°) into a hydrophobic state (WCA = 136°). For SAW sensors based on this hydrophobized ZrO2, the initial frequency drift induced by humidity was suppressed by 92.6 at 85% relative humidity (RH). More importantly, across the dynamic humidity range of 20-85% RH, the DMMP response remained stable at approximately -325 Hz/ppm (fluctuation <6%). This performance is significantly superior to that of unmodified ZrO2 SAW sensors, whose responses fluctuated drastically between -1030 Hz/ppm and +1141 Hz/ppm under identical conditions. The mechanisms underlying the humidity-induced sensitivity drift in ZrO2 SAW sensors were elucidated using in situ infrared absorption spectroscopy and X-ray photoelectron spectroscopy techniques. This study not only provides a straightforward strategy for imparting hydrophobicity to ZrO2 but also offers novel insights for addressing the issue of frequency drift in SAW sensors caused by atmospheric moisture.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"195 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147383461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-11DOI: 10.1021/acssensors.5c03553
K. T. Savio,Amisha Mishra,Aniket K. Pandey,Shivam Kumar Singh,Sajana S.,Chandranath Adak,Rajendra P. Shukla,Vinayak B. Kamble
Detection of trace levels of volatile organic compounds (VOCs) has widespread applications, including wearable diagnostics, IoTs, and indoor air quality control. Although metal oxide semiconductors (MOS) arguably offer the best sensitivity for a wide range of VOCs, their poor selectivity limits their performance. Here, we demonstrate a machine learning (ML)-based analysis and framework using a single, non-selective MOS sensor made of RF-sputtered nickel oxide thin film with gold contacts, aiming to achieve VOC classification and concentration prediction with a high degree of accuracy (>90%) and eliminate biases. Both time-independent and time-dependent features were evaluated using classifiers and regressors, including ensemble methods, artificial neural networks, and recurrent architectures (LSTMs and GRUs). The features identified as excluding time reference (response, its gradient, and Laplacian) were highly effective for baseline classification, achieving near-ideal accuracies (98%) with ensemble models. On the other hand, the time-dependent features (continuous, discrete, and time-sliced) complement the analysis by capturing dynamic adsorption-desorption kinetics via sequential models, leading to accuracies of 94% and above. Regression analysis techniques enhance the predictive capabilities of ensemble and neural approaches, yielding higher R2 values and lower RMSE. Thus, the methods adopted in this work highlight the complementary approach of ML-based modeling with that of material innovation to achieve an important performance metric, namely, selectivity of MOS-based sensors, as a way forward for scalable, real-time VOC monitoring in a complex background of other gases. This approach is highly scalable for other toxic gases, pollutants, and biomarkers for relevant applications.
{"title":"Data-Driven Approach toward the Quantification of Gases in a Complex Mixture Using a Non-Selective Single Metal Oxide Gas Sensor","authors":"K. T. Savio,Amisha Mishra,Aniket K. Pandey,Shivam Kumar Singh,Sajana S.,Chandranath Adak,Rajendra P. Shukla,Vinayak B. Kamble","doi":"10.1021/acssensors.5c03553","DOIUrl":"https://doi.org/10.1021/acssensors.5c03553","url":null,"abstract":"Detection of trace levels of volatile organic compounds (VOCs) has widespread applications, including wearable diagnostics, IoTs, and indoor air quality control. Although metal oxide semiconductors (MOS) arguably offer the best sensitivity for a wide range of VOCs, their poor selectivity limits their performance. Here, we demonstrate a machine learning (ML)-based analysis and framework using a single, non-selective MOS sensor made of RF-sputtered nickel oxide thin film with gold contacts, aiming to achieve VOC classification and concentration prediction with a high degree of accuracy (>90%) and eliminate biases. Both time-independent and time-dependent features were evaluated using classifiers and regressors, including ensemble methods, artificial neural networks, and recurrent architectures (LSTMs and GRUs). The features identified as excluding time reference (response, its gradient, and Laplacian) were highly effective for baseline classification, achieving near-ideal accuracies (98%) with ensemble models. On the other hand, the time-dependent features (continuous, discrete, and time-sliced) complement the analysis by capturing dynamic adsorption-desorption kinetics via sequential models, leading to accuracies of 94% and above. Regression analysis techniques enhance the predictive capabilities of ensemble and neural approaches, yielding higher R2 values and lower RMSE. Thus, the methods adopted in this work highlight the complementary approach of ML-based modeling with that of material innovation to achieve an important performance metric, namely, selectivity of MOS-based sensors, as a way forward for scalable, real-time VOC monitoring in a complex background of other gases. This approach is highly scalable for other toxic gases, pollutants, and biomarkers for relevant applications.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"53 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147383812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-11DOI: 10.1021/acssensors.5c03995
Zhuoru Huang,Yuzi Zeng,Shiqi Tu,Guohan Zheng,Shichao Tian,Zhejia Li,Ping Wang,Hao Wan
Room-temperature ionic liquids (RTILs), owing to their nonvolatility and excellent electrochemical properties, have emerged as promising alternatives to conventional aqueous electrolytes in electrochemical gas sensors. However, their intrinsic fluidity complicates device packaging and long-term stability, which significantly limits their applications. To overcome these challenges, this study introduced polymeric ionic liquid (PIL) into the ionic liquid (IL), solidifying it to form a robust membrane for miniaturized and high-performance electrochemical gas sensing. The hybrid electrolyte exhibits superior ionic conductivity, thermal stability, and electrochemical performance compared with conventional polymer-based electrolytes. The PIL/IL electrolyte was implemented on two typical planar sensor platforms: screen-printed electrodes for electrolyte formulation optimization and sensing validation, and flexible porous substrates (polyethylene terephthalate and polytetrafluoroethylene) with backside-permeable structures to facilitate gas diffusion and for sensing characterization. With hydrogen as the target analyte, the resulting sensors achieved excellent sensitivity, stability, and rapid response at room temperature. By developing a novel solid-state electrolyte and its integrated electrode architecture, this work establishes a scalable, easily fabricated strategy for high-performance, miniaturized electrochemical gas sensors with broad applicability.
{"title":"Robust Polymeric Ionic Liquid/Ionic Liquid Solid-State Electrolyte Membrane for Miniaturized and High-Performance Electrochemical Gas Sensing","authors":"Zhuoru Huang,Yuzi Zeng,Shiqi Tu,Guohan Zheng,Shichao Tian,Zhejia Li,Ping Wang,Hao Wan","doi":"10.1021/acssensors.5c03995","DOIUrl":"https://doi.org/10.1021/acssensors.5c03995","url":null,"abstract":"Room-temperature ionic liquids (RTILs), owing to their nonvolatility and excellent electrochemical properties, have emerged as promising alternatives to conventional aqueous electrolytes in electrochemical gas sensors. However, their intrinsic fluidity complicates device packaging and long-term stability, which significantly limits their applications. To overcome these challenges, this study introduced polymeric ionic liquid (PIL) into the ionic liquid (IL), solidifying it to form a robust membrane for miniaturized and high-performance electrochemical gas sensing. The hybrid electrolyte exhibits superior ionic conductivity, thermal stability, and electrochemical performance compared with conventional polymer-based electrolytes. The PIL/IL electrolyte was implemented on two typical planar sensor platforms: screen-printed electrodes for electrolyte formulation optimization and sensing validation, and flexible porous substrates (polyethylene terephthalate and polytetrafluoroethylene) with backside-permeable structures to facilitate gas diffusion and for sensing characterization. With hydrogen as the target analyte, the resulting sensors achieved excellent sensitivity, stability, and rapid response at room temperature. By developing a novel solid-state electrolyte and its integrated electrode architecture, this work establishes a scalable, easily fabricated strategy for high-performance, miniaturized electrochemical gas sensors with broad applicability.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"7 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147383811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-11DOI: 10.1021/acssensors.5c04591
Zetao Zhang,Xiaokang Li,Xiatong Pan,Wei Wang,Lei Zhang,Junxiu Lu,Jun Chen,Fei Liu,Li Wang
Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, underscoring the need for advanced in vitro models that closely mimic native cardiac function. Traditional models, such as single-cell cultures and 2D monolayers, fail to replicate the complex mechanoelectrical coupling of human myocardium, limiting insights into disease mechanisms and pharmacological responses. Recent advances in tissue engineering have enabled the fabrication of 3D cardiac constructs that better capture the structural and functional intricacies of the heart. Central to this progress are hydrogel scaffolds, which provide cell-adhesive, biocompatible matrices with tunable mechanics and extracellular matrix-like properties, supporting cell adhesion, proliferation, and differentiation. These constructs are increasingly integrated with biosensing platforms capable of real-time, in situ monitoring of cardiac dynamics. Innovations, such as conductive hydrogel pillars, engineered cardiac patches, and thin-film microelectrode arrays, offer high-resolution, high-throughput interrogation of electrophysiological and mechanical signals while mitigating sensor−tissue impedance mismatches. Here, we review the recent progress in hydrogel-based tissue engineering and biosensing technologies for 3D cardiac models. We highlight key advances, identify persistent challenges, and outline future directions toward synchronized mechanoelectrical monitoring. This integrated strategy offers a powerful framework for elucidating CVD pathophysiology, improving drug screening, and advancing precision cardiovascular medicine.
{"title":"Hydrogel Cardiac Tissue Integrated with Biosensors for Monitoring Cardiac Dysfunction","authors":"Zetao Zhang,Xiaokang Li,Xiatong Pan,Wei Wang,Lei Zhang,Junxiu Lu,Jun Chen,Fei Liu,Li Wang","doi":"10.1021/acssensors.5c04591","DOIUrl":"https://doi.org/10.1021/acssensors.5c04591","url":null,"abstract":"Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, underscoring the need for advanced in vitro models that closely mimic native cardiac function. Traditional models, such as single-cell cultures and 2D monolayers, fail to replicate the complex mechanoelectrical coupling of human myocardium, limiting insights into disease mechanisms and pharmacological responses. Recent advances in tissue engineering have enabled the fabrication of 3D cardiac constructs that better capture the structural and functional intricacies of the heart. Central to this progress are hydrogel scaffolds, which provide cell-adhesive, biocompatible matrices with tunable mechanics and extracellular matrix-like properties, supporting cell adhesion, proliferation, and differentiation. These constructs are increasingly integrated with biosensing platforms capable of real-time, in situ monitoring of cardiac dynamics. Innovations, such as conductive hydrogel pillars, engineered cardiac patches, and thin-film microelectrode arrays, offer high-resolution, high-throughput interrogation of electrophysiological and mechanical signals while mitigating sensor−tissue impedance mismatches. Here, we review the recent progress in hydrogel-based tissue engineering and biosensing technologies for 3D cardiac models. We highlight key advances, identify persistent challenges, and outline future directions toward synchronized mechanoelectrical monitoring. This integrated strategy offers a powerful framework for elucidating CVD pathophysiology, improving drug screening, and advancing precision cardiovascular medicine.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"7 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147383765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-11DOI: 10.1021/acssensors.5c03074
Jeewan C Ranasinghe,Stephen K Sanders,Ziyang Wang,Jaanita Mehrani,Wenjing Wu,Edgar Dimitrov,Xielin Wang,Allen M Minns,Randall M Rossi,Scott E Lindner,Mauricio Terrones,Alessandro Alabastri,Shengxi Huang
Surface-enhanced Raman spectroscopy (SERS) offers high sensitivity for biomolecular detection, but its performance is often constrained by noise arising from signal non-uniformity across substrates. Here, we introduce a noise-management-oriented design strategy for hybrid SERS substrates composed of gold nanoparticles (AuNP) and two-dimensional (2D) materials (graphene, MoS2, and WSe2). Compared with conventional AuNP substrates, the hybrids exhibit markedly improved spectral uniformity and signal-to-noise ratio (SNR), with the AuNP/graphene platform reducing noise by ∼67% and increasing SNR by ∼279%. Full-wave simulations based on Maxwell's equations corroborated the experimental results and reveal that optical constants of the 2D material and nanoparticle distribution jointly govern noise characteristics. SNR dependence on nanoparticle density distributions, refractive index (n), and extinction coefficient (k) is further established. As a practical demonstration, the AuNP/graphene substrate enabled detection of the receptor binding domain protein at a limit of detection (LOD) of 10-9 M, representing a ten-fold improvement over the 10-8 M LOD of AuNP substrates. These results establish AuNP/2D hybrids as effective platforms for noise-managed SERS, offering enhanced sensitivity for biosensing.
表面增强拉曼光谱（SERS）为生物分子检测提供了高灵敏度，但其性能通常受到基底上信号不均匀性引起的噪声的限制。在这里，我们介绍了一种面向噪声管理的设计策略，用于由金纳米颗粒（AuNP）和二维（2D）材料（石墨烯，MoS2和WSe2）组成的混合SERS衬底。与传统的AuNP衬底相比，这种杂化材料表现出明显改善的光谱均匀性和信噪比（SNR），其中AuNP/石墨烯平台的噪声降低了67%，信噪比提高了279%。基于麦克斯韦方程组的全波模拟证实了实验结果，揭示了二维材料的光学常数和纳米颗粒的分布共同决定了噪声特性。进一步建立了信噪比与纳米粒子密度分布、折射率(n)和消光系数(k)的关系。作为实际演示，AuNP/石墨烯底物能够以10-9 M的检测限（LOD）检测受体结合域蛋白，比AuNP底物的10-8 M LOD提高了10倍。这些结果建立了AuNP/2D杂交种作为噪声管理SERS的有效平台，为生物传感提供了更高的灵敏度。
{"title":"Noise Management of Surface-Enhanced Raman Spectroscopy Using Two-Dimensional Materials.","authors":"Jeewan C Ranasinghe,Stephen K Sanders,Ziyang Wang,Jaanita Mehrani,Wenjing Wu,Edgar Dimitrov,Xielin Wang,Allen M Minns,Randall M Rossi,Scott E Lindner,Mauricio Terrones,Alessandro Alabastri,Shengxi Huang","doi":"10.1021/acssensors.5c03074","DOIUrl":"https://doi.org/10.1021/acssensors.5c03074","url":null,"abstract":"Surface-enhanced Raman spectroscopy (SERS) offers high sensitivity for biomolecular detection, but its performance is often constrained by noise arising from signal non-uniformity across substrates. Here, we introduce a noise-management-oriented design strategy for hybrid SERS substrates composed of gold nanoparticles (AuNP) and two-dimensional (2D) materials (graphene, MoS2, and WSe2). Compared with conventional AuNP substrates, the hybrids exhibit markedly improved spectral uniformity and signal-to-noise ratio (SNR), with the AuNP/graphene platform reducing noise by ∼67% and increasing SNR by ∼279%. Full-wave simulations based on Maxwell's equations corroborated the experimental results and reveal that optical constants of the 2D material and nanoparticle distribution jointly govern noise characteristics. SNR dependence on nanoparticle density distributions, refractive index (n), and extinction coefficient (k) is further established. As a practical demonstration, the AuNP/graphene substrate enabled detection of the receptor binding domain protein at a limit of detection (LOD) of 10-9 M, representing a ten-fold improvement over the 10-8 M LOD of AuNP substrates. These results establish AuNP/2D hybrids as effective platforms for noise-managed SERS, offering enhanced sensitivity for biosensing.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"1 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147383438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-10DOI: 10.1021/acssensors.5c04395
Hyun Shin,Junhyeok Yoon,Yumin Kim,Cheulhee Jung
Point-of-care nucleic acid diagnostics demand rapid, instrument-free detection with high sensitivity and specificity. While loop-mediated isothermal amplification (LAMP) enables rapid amplification, conventional colorimetric indicators generate false positives by responding to any DNA synthesis, not just target-specific products. We developed a dual-gated G-quadruplex DNAzyme-LAMP that integrates G-quadruplex DNAzyme formation into the loop primer architecture while blocking non-specific activation through locked nucleic acidstabilized probe design. This approach gates colorimetric signal generation to occur only when target amplicons displace a 3'-blocking strand, enabling sequence-specific positive signaling without sacrificing amplification kinetics. When tested with Hepatitis A virus, the assay detected as few as 12 copies per reaction, matching RT-qPCR sensitivity while providing unambiguous positive colorimetric readouts. Specificity was maintained even in the presence of a 109-fold excess non-target DNA. Importantly, the platform requires only inexpensive hemin and chromogenic substrates, avoiding the protein reagents, custom oligonucleotides, and cold-chain logistics that constrain existing sequence-specific platforms. By exploiting the universally adopted loop primer element, this platform offers a generalizable framework for reliable colorimetric detection suitable for resource-limited outbreak settings.
{"title":"Dual-Gated G-Quadruplex DNAzyme-LAMP for Sequence-Specific and Positive Colorimetric Nucleic Acid Detection.","authors":"Hyun Shin,Junhyeok Yoon,Yumin Kim,Cheulhee Jung","doi":"10.1021/acssensors.5c04395","DOIUrl":"https://doi.org/10.1021/acssensors.5c04395","url":null,"abstract":"Point-of-care nucleic acid diagnostics demand rapid, instrument-free detection with high sensitivity and specificity. While loop-mediated isothermal amplification (LAMP) enables rapid amplification, conventional colorimetric indicators generate false positives by responding to any DNA synthesis, not just target-specific products. We developed a dual-gated G-quadruplex DNAzyme-LAMP that integrates G-quadruplex DNAzyme formation into the loop primer architecture while blocking non-specific activation through locked nucleic acidstabilized probe design. This approach gates colorimetric signal generation to occur only when target amplicons displace a 3'-blocking strand, enabling sequence-specific positive signaling without sacrificing amplification kinetics. When tested with Hepatitis A virus, the assay detected as few as 12 copies per reaction, matching RT-qPCR sensitivity while providing unambiguous positive colorimetric readouts. Specificity was maintained even in the presence of a 109-fold excess non-target DNA. Importantly, the platform requires only inexpensive hemin and chromogenic substrates, avoiding the protein reagents, custom oligonucleotides, and cold-chain logistics that constrain existing sequence-specific platforms. By exploiting the universally adopted loop primer element, this platform offers a generalizable framework for reliable colorimetric detection suitable for resource-limited outbreak settings.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"66 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147381404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-10DOI: 10.1021/acssensors.5c04269
Jie Li,Kuiwei Shi,Lu Wang,Yanpu Yao,Yuang Wang,Zhikang Li,Kaifei Wang,Libo Zhao,Pengyi Wang
Artificial Intelligence of Things (AIoT) enables convenient human health monitoring but consumes massive data and energy. Traditional power supplies and single-sensor setups struggle to reconcile this wireless convenience and multimodal data transmission. A hybrid knee-bending energy harvester is designed, integrating two frequency-up electromagnetic generators (EMGs) and two flexible contact-separate triboelectric nanogenerators (TENGs). The maximum EMG output power is 1.09 W at a frequency of 1.5 Hz and an angle of 180°. A two-stage capacitor scheme is adopted for the cointegration of power generation and sensing. One optimized capacitor stores energy and can wake the wireless system via a single undervoltage lockout (UVLO) discharge. The other capacitor regards linearly charging voltage as angle sensing. The TENG voltage reflects flexible pressure, while motion frequency is derived from the reciprocal of wireless data reception intervals. A custom web-based Bluetooth host computer displays motion data in real time. This system supports long-distance remote monitoring of knee-bending states, facilitating wireless knee health tracking and clinical rehabilitation between patients and clinicians.
{"title":"Self-Powered Multisensor with Electromagnetic and Triboelectric Energy Harvesting for Wireless Monitoring in Every Knee Joint Motion.","authors":"Jie Li,Kuiwei Shi,Lu Wang,Yanpu Yao,Yuang Wang,Zhikang Li,Kaifei Wang,Libo Zhao,Pengyi Wang","doi":"10.1021/acssensors.5c04269","DOIUrl":"https://doi.org/10.1021/acssensors.5c04269","url":null,"abstract":"Artificial Intelligence of Things (AIoT) enables convenient human health monitoring but consumes massive data and energy. Traditional power supplies and single-sensor setups struggle to reconcile this wireless convenience and multimodal data transmission. A hybrid knee-bending energy harvester is designed, integrating two frequency-up electromagnetic generators (EMGs) and two flexible contact-separate triboelectric nanogenerators (TENGs). The maximum EMG output power is 1.09 W at a frequency of 1.5 Hz and an angle of 180°. A two-stage capacitor scheme is adopted for the cointegration of power generation and sensing. One optimized capacitor stores energy and can wake the wireless system via a single undervoltage lockout (UVLO) discharge. The other capacitor regards linearly charging voltage as angle sensing. The TENG voltage reflects flexible pressure, while motion frequency is derived from the reciprocal of wireless data reception intervals. A custom web-based Bluetooth host computer displays motion data in real time. This system supports long-distance remote monitoring of knee-bending states, facilitating wireless knee health tracking and clinical rehabilitation between patients and clinicians.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"237 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147383448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The development of a H2S gas sensor that exhibits high response and a low detection limit remains a highly anticipated goal in the field. In this work, Li-doped CuO nanoparticles compounded on graphene were successfully prepared by the solvothermal method for efficient H2S gas detection. The lattice structure, microstructure, elemental distribution, and chemical states of rGO-CuO-Li were systematically characterized by XRD, SEM, EDS, and XPS. The results confirmed the successful synthesis of Li-doped CuO nanoparticles compounded on graphene. The gas sensing test results demonstrated that 4 mol % rGO-CuO-10 mol % Li (CCuLi-2) exhibited excellent gas sensing performance for H2S gas. At room temperature, the CCuLi-2 nanocomposite material exhibited a remarkably high response value of 220.1 to 10 ppm H2S gas, which was 30.6 times that of pure CuO. In addition, the sensor achieved a breakthrough in its detection limit, enabling it to detect 1 ppb H2S gas with a response value of 1.54. Meanwhile, the CCuLi-2 demonstrated high selectivity and superior long-term stability for H2S detection. This research provides a novel reference for the design and development of H2S sensors with low detection limits and high sensitivity.
{"title":"Ppb-Level H2S Gas Sensor Based on Li-Doped CuO Nanoparticles Compounded on Graphene at Room Temperature.","authors":"Huai Wang,Fangling Zhou,Renze Zhang,Zhenyu Yuan,Zhongming Guo,Zhuangzhuang Mu,Tianyao Qi,Hanyang Ji,Yanbai Shen,Fanli Meng","doi":"10.1021/acssensors.5c04153","DOIUrl":"https://doi.org/10.1021/acssensors.5c04153","url":null,"abstract":"The development of a H2S gas sensor that exhibits high response and a low detection limit remains a highly anticipated goal in the field. In this work, Li-doped CuO nanoparticles compounded on graphene were successfully prepared by the solvothermal method for efficient H2S gas detection. The lattice structure, microstructure, elemental distribution, and chemical states of rGO-CuO-Li were systematically characterized by XRD, SEM, EDS, and XPS. The results confirmed the successful synthesis of Li-doped CuO nanoparticles compounded on graphene. The gas sensing test results demonstrated that 4 mol % rGO-CuO-10 mol % Li (CCuLi-2) exhibited excellent gas sensing performance for H2S gas. At room temperature, the CCuLi-2 nanocomposite material exhibited a remarkably high response value of 220.1 to 10 ppm H2S gas, which was 30.6 times that of pure CuO. In addition, the sensor achieved a breakthrough in its detection limit, enabling it to detect 1 ppb H2S gas with a response value of 1.54. Meanwhile, the CCuLi-2 demonstrated high selectivity and superior long-term stability for H2S detection. This research provides a novel reference for the design and development of H2S sensors with low detection limits and high sensitivity.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"226 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147381224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Flexible wearable biochemical sensors hold great promise for personalized health monitoring. However, achieving ultrahigh molecular sensitivity, conformal skin adhesion, and efficient sweat handling within a single device remains a critical challenge. Here, we present a fully integrated wearable sweat-sensing platform that seamlessly combines a biocompatible adhesive hydrogel, an ultrasensitive sandwich-structured surface-enhanced Raman scattering (SERS) architecture, and microfluidic sweat-collection channels for non-invasive monitoring of dopamine, a key biomarker associated with depression. The central component of the system is a dual-layer heterogeneous superstructure. Specifically, a highly ordered Au nanoparticle (Au NP) superlattice forms the bottom layer, offering uniform and dense plasmonic hotspots, while the top layer is based on double-shelled hollow Au@Au-Ag nanocages functionalized with Raman reporters and aptamer sequences. Furthermore, DNA-guided hybridization forms a robust "nanolock" junction that ensures strong interparticle coupling and provides excellent specificity. This configuration yields an exceptional SERS enhancement factor of 1.57 × 1011, enabling nanomole-level dopamine detection (limit of detection: 3.78 × 10-14 M) with excellent reproducibility (RSD = 9.02%) and high chemical specificity. To adapt the sensing unit for on-body use, the SERS chip is embedded within an adhesive, deformable, and biocompatible polyethylene glycol hydrogel. Featuring engineered microfluidic channels, this hydrogel autonomously transports sweat to the sensing area, thereby guaranteeing precise detection alongside consistent conformal contact and comfort. This multifunctional, integrated platform has the potential to overcome longstanding limitations in sensitivity, stability, biocompatibility, and sweat management that hinder conventional wearable sensors. It provides a powerful route toward a versatile design framework for next-generation wearable bioelectronics.
{"title":"Skin-Conformal Sandwich-Structured SERS Superlattice Platform for Non-Invasive Depression Detection.","authors":"Hangzhe Shao,Shuangshuang Wu,Lingli Zhang,Bohang Ye,Qiaoyun Luo,Kanzhen Tong,Liping Song,Youju Huang","doi":"10.1021/acssensors.5c04789","DOIUrl":"https://doi.org/10.1021/acssensors.5c04789","url":null,"abstract":"Flexible wearable biochemical sensors hold great promise for personalized health monitoring. However, achieving ultrahigh molecular sensitivity, conformal skin adhesion, and efficient sweat handling within a single device remains a critical challenge. Here, we present a fully integrated wearable sweat-sensing platform that seamlessly combines a biocompatible adhesive hydrogel, an ultrasensitive sandwich-structured surface-enhanced Raman scattering (SERS) architecture, and microfluidic sweat-collection channels for non-invasive monitoring of dopamine, a key biomarker associated with depression. The central component of the system is a dual-layer heterogeneous superstructure. Specifically, a highly ordered Au nanoparticle (Au NP) superlattice forms the bottom layer, offering uniform and dense plasmonic hotspots, while the top layer is based on double-shelled hollow Au@Au-Ag nanocages functionalized with Raman reporters and aptamer sequences. Furthermore, DNA-guided hybridization forms a robust \"nanolock\" junction that ensures strong interparticle coupling and provides excellent specificity. This configuration yields an exceptional SERS enhancement factor of 1.57 × 1011, enabling nanomole-level dopamine detection (limit of detection: 3.78 × 10-14 M) with excellent reproducibility (RSD = 9.02%) and high chemical specificity. To adapt the sensing unit for on-body use, the SERS chip is embedded within an adhesive, deformable, and biocompatible polyethylene glycol hydrogel. Featuring engineered microfluidic channels, this hydrogel autonomously transports sweat to the sensing area, thereby guaranteeing precise detection alongside consistent conformal contact and comfort. This multifunctional, integrated platform has the potential to overcome longstanding limitations in sensitivity, stability, biocompatibility, and sweat management that hinder conventional wearable sensors. It provides a powerful route toward a versatile design framework for next-generation wearable bioelectronics.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"6 1","pages":"XXX"},"PeriodicalIF":8.9,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147381405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Whole-cell biosensors (WCBs) capable of sensitively detecting trace amounts of analytes hold great potential for in situ detection of pollutants, toxins, or synthetic products. As the terminal signal actuator, the reporter gene directly influences the ultimate sensitivity of WCBs. Although fluorescent proteins (FPs) have been widely used as reporters, their reporting sensitivity is generally lower than that of enzymatic reporters, which often limits the sensitivity and response speed of FP-based sensors in practical applications. Here, we developed an ultrasensitive FP reporter via a noninvasive N-terminal peptide fusion strategy. By adding an N-terminal decapeptide obtained from a high-throughput screening, we constructed an NGFP4 variant that retains the inherent advantages of sfGFP while exhibiting superior reporter gene characteristics, such as rapid expression and robust intracellular stability. These properties enhanced the single-cell fluorescence intensity of NGFP4 by 6.4- to 28-fold in four typical microbial hosts, including E. coli (28-fold), Bacillus subtilis (15.5-fold), Pichia pastoris (9.1-fold), and Saccharomyces cerevisiae (6.4-fold). When applied to WCBs, the NGFP4 reporter greatly shortened the detection time to 1 h for salicylic acid (LOD of 0.36 μM) and 2-chlorobiphenyl (LOD of 18.2 μM), representing the fastest detection time for such sensors. Therefore, our work provides a cross-species compatible FP reporter that enables sensitive detection of microbial cell-based biosensors and other bioanalytical systems, facilitating their field deployment with minimal genetic manipulation and shorter detection time.
{"title":"Bright Single-Cell Fluorescent Reporter Enables Ultrasensitive Target Detection for Microbial Cell-Based Biosensors.","authors":"Faying Zhang,Xuting Sun,Hui Zheng,Meng Mei,Li Yi,Guimin Zhang","doi":"10.1021/acssensors.5c03132","DOIUrl":"https://doi.org/10.1021/acssensors.5c03132","url":null,"abstract":"Whole-cell biosensors (WCBs) capable of sensitively detecting trace amounts of analytes hold great potential for in situ detection of pollutants, toxins, or synthetic products. As the terminal signal actuator, the reporter gene directly influences the ultimate sensitivity of WCBs. Although fluorescent proteins (FPs) have been widely used as reporters, their reporting sensitivity is generally lower than that of enzymatic reporters, which often limits the sensitivity and response speed of FP-based sensors in practical applications. Here, we developed an ultrasensitive FP reporter via a noninvasive N-terminal peptide fusion strategy. By adding an N-terminal decapeptide obtained from a high-throughput screening, we constructed an NGFP4 variant that retains the inherent advantages of sfGFP while exhibiting superior reporter gene characteristics, such as rapid expression and robust intracellular stability. These properties enhanced the single-cell fluorescence intensity of NGFP4 by 6.4- to 28-fold in four typical microbial hosts, including E. coli (28-fold), Bacillus subtilis (15.5-fold), Pichia pastoris (9.1-fold), and Saccharomyces cerevisiae (6.4-fold). When applied to WCBs, the NGFP4 reporter greatly shortened the detection time to 1 h for salicylic acid (LOD of 0.36 μM) and 2-chlorobiphenyl (LOD of 18.2 μM), representing the fastest detection time for such sensors. Therefore, our work provides a cross-species compatible FP reporter that enables sensitive detection of microbial cell-based biosensors and other bioanalytical systems, facilitating their field deployment with minimal genetic manipulation and shorter detection time.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"1 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147383446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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