Pub Date : 2026-03-19DOI: 10.1021/acssensors.5c03614
Jinlan Yang, Chushi Chen, Yu Yan, Meng Wang, Li Yang
The copper(I)-catalyzed azide-alkyne cycloaddition (CuAAC) reaction, a widely used click chemistry reaction, is utilized to develop a robust analytical strategy for non-invasive and accurate quantification of extremely low-amount biomarkers in human body fluids. A specially designed dual-functionalized liposome is proposed for specific target recognition at the membrane surface and encapsulation of a large amount of Cu2+ inside the liposome. Explosive release of a large amount of cooper catalysts occurs once the liposome membrane is disrupted, leading to a rapid CuAAC reaction to induce fluorescence resonance energy transfer between fluorescent DNA signal probes. The strategy can significantly improve sensitivity without tedious sample pretreatment, thanks to signal amplification via the click reaction by introducing catalysts in an explosive manner. Moreover, the strategy is proven to be a versatile tool and is used for accurate determination of nucleic acids, proteins, and small molecules in human body fluids, owing to the capability of the liposome for facile modification with various recognition molecules. Our method provides a straightforward signal amplification approach based on click chemistry, which is simple and universal for ultrasensitive analysis of different kinds of biomarkers, with the advantages of design flexibility, and thus would have valuable applications in non-invasive targeting of various biomarkers in human body fluids.
{"title":"Explosive-Copper-Liposome-Based Click Amplification for Non-Invasive Quantification of Trace Biomarkers","authors":"Jinlan Yang, Chushi Chen, Yu Yan, Meng Wang, Li Yang","doi":"10.1021/acssensors.5c03614","DOIUrl":"https://doi.org/10.1021/acssensors.5c03614","url":null,"abstract":"The copper(I)-catalyzed azide-alkyne cycloaddition (CuAAC) reaction, a widely used click chemistry reaction, is utilized to develop a robust analytical strategy for non-invasive and accurate quantification of extremely low-amount biomarkers in human body fluids. A specially designed dual-functionalized liposome is proposed for specific target recognition at the membrane surface and encapsulation of a large amount of Cu<sup>2+</sup> inside the liposome. Explosive release of a large amount of cooper catalysts occurs once the liposome membrane is disrupted, leading to a rapid CuAAC reaction to induce fluorescence resonance energy transfer between fluorescent DNA signal probes. The strategy can significantly improve sensitivity without tedious sample pretreatment, thanks to signal amplification via the click reaction by introducing catalysts in an explosive manner. Moreover, the strategy is proven to be a versatile tool and is used for accurate determination of nucleic acids, proteins, and small molecules in human body fluids, owing to the capability of the liposome for facile modification with various recognition molecules. Our method provides a straightforward signal amplification approach based on click chemistry, which is simple and universal for ultrasensitive analysis of different kinds of biomarkers, with the advantages of design flexibility, and thus would have valuable applications in non-invasive targeting of various biomarkers in human body fluids.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"6 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147478579","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 : 2026-03-18DOI: 10.1021/acssensors.5c04723
Yupu Zhang, Donghao Han, Yujue Wang, Xinyu Li, Liangshutong Zhang, Shuchang Xu, Fan Ma, Wei Zhai, Jianyuan Wang
Flexible acoustic devices have advantages of high flexibility and large sound output area, capable of adhering to the surface of the skin or clothing, which shows great potential in the field of wearable electronics. However, the design of acoustic material structures and their functional applications are still difficult. Here, we fabricated a porous laser-induced graphene (LIG) microarray layer on a polyimide (PI) film by laser direct writing. Subsequently, we uniformly coated the few-layer MXene nanosheets onto the LIG surface to obtain an MXene/LIG@PI film featuring low specific heat capacity per unit area, large interlayer spacing, excellent electrical conductivity, and high thermal conductivity. Meanwhile, the MXene/LIG@PI-based acoustic device composed of flexible copper electrodes exhibits excellent acoustic performance with a high sound pressure level of 77.6 dB and maintained a stable acoustic spectrum as the frequency increased from 20.0 Hz to 20.0 kHz. Finally, the portable acoustic alarm device composed of the piezoelectric module and the MXene/LIG@PI-based acoustic module was designed, which can be worn on various parts of the human body clothing, to provide audible alarm reminders in case of accidental falls or drops during outdoor activities. This study provides a novel approach for designing new flexible acoustic materials and devices.
{"title":"Wearable Flexible Acoustic Alarm Device Based on MXene/Laser-Induced Graphene@Polyimide Thermoacoustic Film","authors":"Yupu Zhang, Donghao Han, Yujue Wang, Xinyu Li, Liangshutong Zhang, Shuchang Xu, Fan Ma, Wei Zhai, Jianyuan Wang","doi":"10.1021/acssensors.5c04723","DOIUrl":"https://doi.org/10.1021/acssensors.5c04723","url":null,"abstract":"Flexible acoustic devices have advantages of high flexibility and large sound output area, capable of adhering to the surface of the skin or clothing, which shows great potential in the field of wearable electronics. However, the design of acoustic material structures and their functional applications are still difficult. Here, we fabricated a porous laser-induced graphene (LIG) microarray layer on a polyimide (PI) film by laser direct writing. Subsequently, we uniformly coated the few-layer MXene nanosheets onto the LIG surface to obtain an MXene/LIG@PI film featuring low specific heat capacity per unit area, large interlayer spacing, excellent electrical conductivity, and high thermal conductivity. Meanwhile, the MXene/LIG@PI-based acoustic device composed of flexible copper electrodes exhibits excellent acoustic performance with a high sound pressure level of 77.6 dB and maintained a stable acoustic spectrum as the frequency increased from 20.0 Hz to 20.0 kHz. Finally, the portable acoustic alarm device composed of the piezoelectric module and the MXene/LIG@PI-based acoustic module was designed, which can be worn on various parts of the human body clothing, to provide audible alarm reminders in case of accidental falls or drops during outdoor activities. This study provides a novel approach for designing new flexible acoustic materials and devices.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"44 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147478582","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}
Electroretinography (ERG) is extensively employed to measure the electrical activity of the retinal tissue, and it requires corneal interfaces that are soft, conformal, stable, and low impedance. However, commercial rigid electrodes cause discomfort and are sensitive to eye motion. Many soft designs, such as graphene and hydrogel contact lenses, still suffer from high and unstable interfacial impedance. Here, we report a soft and stable ERG contact lens with liquid metal (LM) composite electrodes coated with silver nanowire/sodium alginate (AgNWs-SA). The wiring electrodes are patterned by direct writing of fumed silica nanoparticles/copper powder/liquid metal (FCL) composite ink onto a sodium alginate interlayer on a curved polydimethylsiloxane (PDMS) substrate, which have a high conductivity of ∼105 S m−1. The electrode surface in contact with the cornea is modified by dripping AgNWs-SA, effectively suppressing low-frequency impedance fluctuation to achieve stable signal acquisition while preventing leakage of the FCL ink, and the cell viability across the entire electrode exceeds 95%. The lens exhibits a lower electrochemical impedance of ∼806 Ω@100 Hz and greater stability than a commercial gold ring electrode. In vivo, it records full-field ERG with larger amplitudes, clearer oscillatory potentials, and improved 30 Hz flicker responses. A five-electrode array resolves center-to-periphery corneal potential gradients and maintains waveform consistency in semi-awake animals. Thus, the ERG contact lens enables high-fidelity single- and multi-electrode detection of ERG and paves a new path toward fabricating wearable ocular sensors.
视网膜电图（ERG）被广泛用于测量视网膜组织的电活动，它要求角膜界面柔软、适形、稳定和低阻抗。然而，商用硬电极会引起不适，而且对眼球运动很敏感。许多软性设计，如石墨烯和水凝胶隐形眼镜，仍然受到高而不稳定的界面阻抗的困扰。在这里，我们报道了一种柔软稳定的ERG隐形眼镜，该隐形眼镜采用涂有银纳米线/海藻酸钠（AgNWs-SA）的液态金属（LM）复合电极。通过将气相二氧化硅纳米颗粒/铜粉/液态金属（FCL）复合墨水直接写入到弯曲的聚二甲基硅氧烷（PDMS）衬底上的海藻酸钠中间层上，从而形成布线电极的图案，PDMS衬底具有高导电性（~ 105 S m−1）。通过滴注AgNWs-SA修饰与角膜接触的电极表面，有效抑制低频阻抗波动，实现稳定的信号采集，同时防止FCL墨水泄漏，整个电极的细胞活力超过95%。该透镜具有较低的电化学阻抗（~ 806 Ω@100 Hz）和比商用金环电极更高的稳定性。在体内，它记录的全视野ERG振幅更大，振荡电位更清晰，30hz闪烁反应得到改善。一个五电极阵列解决中心到周围角膜电位梯度和保持波形一致性在半清醒的动物。因此，ERG隐形眼镜实现了ERG的高保真单电极和多电极检测，为制造可穿戴式眼传感器铺平了新的道路。
{"title":"Wearable Contact Lens for Electroretinography Signal Detection via Liquid Metal Composite Electrodes Coated with Silver Nanowire/Sodium Alginate","authors":"Yiyi Zhang, Qibin Zhuang, Lianjie Lu, Lifan Yang, Yating Qiu, Minjie Zhang, Moran Li, Qiongjing Yang, Shiying Li, Dezhi Wu","doi":"10.1021/acssensors.5c04968","DOIUrl":"https://doi.org/10.1021/acssensors.5c04968","url":null,"abstract":"Electroretinography (ERG) is extensively employed to measure the electrical activity of the retinal tissue, and it requires corneal interfaces that are soft, conformal, stable, and low impedance. However, commercial rigid electrodes cause discomfort and are sensitive to eye motion. Many soft designs, such as graphene and hydrogel contact lenses, still suffer from high and unstable interfacial impedance. Here, we report a soft and stable ERG contact lens with liquid metal (LM) composite electrodes coated with silver nanowire/sodium alginate (AgNWs-SA). The wiring electrodes are patterned by direct writing of fumed silica nanoparticles/copper powder/liquid metal (FCL) composite ink onto a sodium alginate interlayer on a curved polydimethylsiloxane (PDMS) substrate, which have a high conductivity of ∼10<sup>5</sup> S m<sup>−1</sup>. The electrode surface in contact with the cornea is modified by dripping AgNWs-SA, effectively suppressing low-frequency impedance fluctuation to achieve stable signal acquisition while preventing leakage of the FCL ink, and the cell viability across the entire electrode exceeds 95%. The lens exhibits a lower electrochemical impedance of ∼806 Ω@100 Hz and greater stability than a commercial gold ring electrode. In vivo, it records full-field ERG with larger amplitudes, clearer oscillatory potentials, and improved 30 Hz flicker responses. A five-electrode array resolves center-to-periphery corneal potential gradients and maintains waveform consistency in semi-awake animals. Thus, the ERG contact lens enables high-fidelity single- and multi-electrode detection of ERG and paves a new path toward fabricating wearable ocular sensors.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"303 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147471719","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 : 2026-03-18DOI: 10.1021/acssensors.6c00988
I recently visited Pacific Northwest National Laboratory, home to one of the largest and most capable multi-user facilities for molecular science: the Environmental Molecular Sciences Laboratory (EMSL). During the visit, I toured an area where an entire wing of the facility is being converted into robotic laboratories capable of carrying out experiments remotely and at high throughput. The vision is striking: autonomous experimental platforms generating vast quantities of data, enabling new modes of discovery driven by artificial intelligence and machine learning. Later that evening, over a perfectly cooked salmon dinner, my hosts described another challenge that accompanies this technological shift. Many samples analyzed at national laboratories undergo multiple advanced characterization techniques, each producing large datasets. Yet much of the information contained in these datasets is never fully integrated. “So much data is wasted,” one colleague remarked. The emerging goal is not simply to collect more data but to connect data streams from multiple experiments, building a more complete understanding of complex systems and preserving the scientific record of both successful and unsuccessful experiments. Experiences like this raise fundamental questions as the scientific enterprise pivots toward artificial intelligence (AI)-enabled research. My colleague Baskar Ganapathysubramanian, co-director of the Translational AI Center at Iowa State University, often frames these questions succinctly: <i>“How do we measure what matters?”</i> and <i>“What is our data layer?”</i> The latter refers to a critical foundation of any AI-driven research effort: the structured body of experimental observations on which models are trained and decisions are made. These questions are increasingly reflected in national science policy. In November 2025, the United States announced the Genesis Mission, an initiative aimed at accelerating scientific discovery through artificial intelligence, large-scale scientific datasets, and automated experimentation platforms. The initiative envisions integrating high-performance computing, robotic laboratories, and extensive federal data resources to train scientific foundation models and accelerate hypothesis generation and testing. While much of the discussion surrounding such efforts focuses on computational capabilities and AI algorithms, their success ultimately depends on the quality, structure, and accessibility of the experimental data that underpin them. Ultimately, the design of this data layer is driven by knowledge gaps, especially those that shape decision-making and enable real-time automation. In many cases, this means generating data that are spatially resolved, temporally resolved, and sufficiently high throughput to capture complex and dynamic processes. Arrayed sensing platforms, mapping approaches, and high-throughput measurements are therefore becoming increasingly valuable. However, collecting data alone is n
我最近访问了太平洋西北国家实验室，这里拥有分子科学领域最大、能力最强的多用户设施之一：环境分子科学实验室（EMSL）。在访问期间，我参观了一个地区，在那里，该设施的整个侧翼正在被改造成机器人实验室，能够进行远程和高通量的实验。这一愿景令人震惊：自主实验平台产生大量数据，实现由人工智能和机器学习驱动的新发现模式。那天晚上晚些时候，在一顿煮得很好的鲑鱼晚餐上，我的主人描述了伴随这种技术转变而来的另一个挑战。在国家实验室分析的许多样品都采用了多种先进的表征技术，每种技术都会产生大型数据集。然而，这些数据集中包含的许多信息从未得到充分整合。“这么多数据被浪费了，”一位同事评论道。新出现的目标不是简单地收集更多的数据，而是连接来自多个实验的数据流，建立对复杂系统的更完整的理解，并保存成功和不成功实验的科学记录。随着科学企业转向支持人工智能（AI）的研究，这样的经历引发了一些根本性的问题。我的同事Baskar Ganapathysubramanian是爱荷华州立大学（Iowa State University）翻译人工智能中心（Translational AI Center）的联合主任，他经常将这些问题简洁地概括为：“我们如何衡量什么是重要的？”以及“我们的数据层是什么？”后者指的是任何人工智能驱动的研究工作的关键基础：训练模型和做出决策的结构化实验观察。这些问题越来越多地反映在国家科学政策中。2025年11月，美国宣布了创世纪任务，这是一项旨在通过人工智能、大规模科学数据集和自动化实验平台加速科学发现的倡议。该计划设想集成高性能计算、机器人实验室和广泛的联邦数据资源，以训练科学基础模型并加速假设生成和测试。虽然围绕这些努力的讨论主要集中在计算能力和人工智能算法上，但它们的成功最终取决于支撑它们的实验数据的质量、结构和可访问性。最终，这个数据层的设计是由知识差距驱动的，特别是那些影响决策和实现实时自动化的知识差距。在许多情况下，这意味着生成空间解析、时间解析和足够高的吞吐量以捕获复杂和动态过程的数据。因此，阵列传感平台、测绘方法和高通量测量变得越来越有价值。然而，仅仅收集数据是不够的。数据必须以已知的保真度高效、严格地收集。人工智能和机器学习模型的可靠性取决于支撑它们的测量数据，而在低质量数据上训练算法在计算工作量、能源消耗和环境影响方面会带来实际成本。随着人工智能计算需求的扩大，这一点变得越来越重要。大规模机器学习模型需要大量的能源和计算资源。在这种背景下，“绿色科学”必须超越材料和制造方法，包括我们如何有效地生成和使用数据。捕获最相关变量的高质量测量可以减少对大量数据集的需求，并实现更有效的计算发现。传感器定义了支撑人工智能发现的科学数据层。它们不仅决定了我们可以测量什么，还决定了我们可以在哪里进行测量，以及收集测量的频率。当今许多最紧迫的挑战反映了需要持续或频繁观察的动态系统。真正的个性化医疗、关键矿物质的回收、大规模清洁水的可靠输送以及环境污染物的缓解，都涉及到随着时间的推移而演变的过程，而且往往发生在复杂的环境中。这些环境很少是传感技术的理想环境。血浆、废水流、工业反应器或北极水域在污染、稳定性和选择性方面都面临着巨大的挑战。然而，理解这些系统需要在这些复杂的矩阵中进行精确的测量。因此，下一代传感技术的设计不仅要考虑分析性能，还要考虑在具有挑战性的环境中的鲁棒性。另一个根本性的挑战是将传感器安置在需要的地方。 能够跨大空间尺度或在复杂系统内运行的分布式传感网络，对于捕获为人工智能驱动的发现和决策提供信息所需的数据至关重要。同样重要的是有效地将分析物传递到传感器的系统，无论是通过微流体处理，富集策略还是采样架构，都可以弥合现实世界环境和分析测量之间的差距。随着围绕人工智能加速发现的倡议不断扩大，测量科学的重要性变得更加明显。传感器社区有机会塑造科学数据层的基础，这将为这些新的研究模式提供动力。通过设计能够生成高保真、高价值数据集的传感技术，同时在复杂和动态环境中稳健运行，我们可以确保数据驱动科学的下一个时代建立在真正捕获重要信息的测量之上。这篇文章尚未被其他出版物引用。
{"title":"Artificial Intelligence Needs Sensors: Building the Data Layer for Artificial Intelligence-Accelerated Discovery","authors":"","doi":"10.1021/acssensors.6c00988","DOIUrl":"https://doi.org/10.1021/acssensors.6c00988","url":null,"abstract":"I recently visited Pacific Northwest National Laboratory, home to one of the largest and most capable multi-user facilities for molecular science: the Environmental Molecular Sciences Laboratory (EMSL). During the visit, I toured an area where an entire wing of the facility is being converted into robotic laboratories capable of carrying out experiments remotely and at high throughput. The vision is striking: autonomous experimental platforms generating vast quantities of data, enabling new modes of discovery driven by artificial intelligence and machine learning. Later that evening, over a perfectly cooked salmon dinner, my hosts described another challenge that accompanies this technological shift. Many samples analyzed at national laboratories undergo multiple advanced characterization techniques, each producing large datasets. Yet much of the information contained in these datasets is never fully integrated. “So much data is wasted,” one colleague remarked. The emerging goal is not simply to collect more data but to connect data streams from multiple experiments, building a more complete understanding of complex systems and preserving the scientific record of both successful and unsuccessful experiments. Experiences like this raise fundamental questions as the scientific enterprise pivots toward artificial intelligence (AI)-enabled research. My colleague Baskar Ganapathysubramanian, co-director of the Translational AI Center at Iowa State University, often frames these questions succinctly: <i>“How do we measure what matters?”</i> and <i>“What is our data layer?”</i> The latter refers to a critical foundation of any AI-driven research effort: the structured body of experimental observations on which models are trained and decisions are made. These questions are increasingly reflected in national science policy. In November 2025, the United States announced the Genesis Mission, an initiative aimed at accelerating scientific discovery through artificial intelligence, large-scale scientific datasets, and automated experimentation platforms. The initiative envisions integrating high-performance computing, robotic laboratories, and extensive federal data resources to train scientific foundation models and accelerate hypothesis generation and testing. While much of the discussion surrounding such efforts focuses on computational capabilities and AI algorithms, their success ultimately depends on the quality, structure, and accessibility of the experimental data that underpin them. Ultimately, the design of this data layer is driven by knowledge gaps, especially those that shape decision-making and enable real-time automation. In many cases, this means generating data that are spatially resolved, temporally resolved, and sufficiently high throughput to capture complex and dynamic processes. Arrayed sensing platforms, mapping approaches, and high-throughput measurements are therefore becoming increasingly valuable. However, collecting data alone is n","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"4 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147471721","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 : 2026-03-17DOI: 10.1021/acssensors.5c03014
Yunkuan Wei, Lunchao Zhong, Defeng Chen, Qinhua Gao, Yuntao Yang, Ming Li, Hai Liu
The chemiresistive properties of oxide materials are critical to their electrical performance, which originate from the interfacial phenomena involving gaseous species and the solid substrate, e.g., adsorption and charge-transfer processes. However, their fundamental mechanisms are still insufficiently understood. In this study, we investigated the sensing behavior of p-type delafossite AgNiO2 nanoparticles to a series of gaseous alcohols based on the chemiresistive effect, which presented a trend that the response increases with the growing carbon chain from methanol to n-pentanol but decreases from n-hexanol to n-nonanol. Combining the first-principles calculations and experimental data, we proposed a novel mechanism to elucidate this phenomenon. The growing carbon chain may alter the adsorption configuration to facilitate the supplementary electron transfer routes, which eventually boosted the chemiresistive effect. However, further elongation of the carbon chain in an alcohol can bring about the steric hindrance effect, which, in turn, suppressed the charge transfer. These findings provided new insights into the fundamental design of the functional oxide materials for advanced electrical applications.
{"title":"Mechanism for Alcohol Sensing Properties of p-Type AgNiO2 Nanoparticles: Adsorption Configuration and Charge-Transfer Effects","authors":"Yunkuan Wei, Lunchao Zhong, Defeng Chen, Qinhua Gao, Yuntao Yang, Ming Li, Hai Liu","doi":"10.1021/acssensors.5c03014","DOIUrl":"https://doi.org/10.1021/acssensors.5c03014","url":null,"abstract":"The chemiresistive properties of oxide materials are critical to their electrical performance, which originate from the interfacial phenomena involving gaseous species and the solid substrate, e.g., adsorption and charge-transfer processes. However, their fundamental mechanisms are still insufficiently understood. In this study, we investigated the sensing behavior of p-type delafossite AgNiO<sub>2</sub> nanoparticles to a series of gaseous alcohols based on the chemiresistive effect, which presented a trend that the response increases with the growing carbon chain from methanol to n-pentanol but decreases from n-hexanol to n-nonanol. Combining the first-principles calculations and experimental data, we proposed a novel mechanism to elucidate this phenomenon. The growing carbon chain may alter the adsorption configuration to facilitate the supplementary electron transfer routes, which eventually boosted the chemiresistive effect. However, further elongation of the carbon chain in an alcohol can bring about the steric hindrance effect, which, in turn, suppressed the charge transfer. These findings provided new insights into the fundamental design of the functional oxide materials for advanced electrical applications.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"44 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147465920","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 rational design of high-performance metal oxide gas sensors is often limited by an insufficient understanding of the gas−solid interface interaction mechanisms. This study employs headspace gas chromatography−mass spectrometry (GC−MS) to dynamically investigate surface reaction between aniline vapor and Cu-doped SnO2 nanoparticles. The GC−MS results suggest that Cu ion doping facilitates the oxidation of aniline to produce azobenzene, which is not detected on pristine SnO2 under identical conditions. This special catalytic reaction is likely associated with the enhanced selectivity and response value of Cu-SnO2 toward aniline vapor. Crucially, a positive correlation is identified between the aniline oxidation rate, quantified by GC−MS, and the sensor’s response value. This mechanistic insight is leveraged to rationally optimize the Cu doping concentration, yielding a Cu-doped SnO2 sensing material with an optimal composition. The resulting sensor exhibits an outstanding aniline sensing performance of high response (4.5@10 ppm), low detection limit (80 ppb), rapid response time (∼25s), and good selectivity. This work not only demonstrates a viable approach for metal-catalyzed selective detection of volatile organic compounds (VOCs) but also provides a general methodology for quantitatively correlating gas−solid reaction processes with gas sensing performance, providing critical theoretical and technical support for the rational design of advanced gas sensors.
{"title":"Understanding Enhanced Aniline Sensing with Cu-Doped SnO2 via GC−MS Analysis","authors":"Kuan Tian, Wei Zhao, Zhenxing Li, Zhuolin Li, Yixi Jiang, Wanru Wang, Yu’an Sun, Ming Li, Pengcheng Xu","doi":"10.1021/acssensors.5c04590","DOIUrl":"https://doi.org/10.1021/acssensors.5c04590","url":null,"abstract":"The rational design of high-performance metal oxide gas sensors is often limited by an insufficient understanding of the gas−solid interface interaction mechanisms. This study employs headspace gas chromatography−mass spectrometry (GC−MS) to dynamically investigate surface reaction between aniline vapor and Cu-doped SnO<sub>2</sub> nanoparticles. The GC−MS results suggest that Cu ion doping facilitates the oxidation of aniline to produce azobenzene, which is not detected on pristine SnO<sub>2</sub> under identical conditions. This special catalytic reaction is likely associated with the enhanced selectivity and response value of Cu-SnO<sub>2</sub> toward aniline vapor. Crucially, a positive correlation is identified between the aniline oxidation rate, quantified by GC−MS, and the sensor’s response value. This mechanistic insight is leveraged to rationally optimize the Cu doping concentration, yielding a Cu-doped SnO<sub>2</sub> sensing material with an optimal composition. The resulting sensor exhibits an outstanding aniline sensing performance of high response (4.5@10 ppm), low detection limit (80 ppb), rapid response time (∼25s), and good selectivity. This work not only demonstrates a viable approach for metal-catalyzed selective detection of volatile organic compounds (VOCs) but also provides a general methodology for quantitatively correlating gas−solid reaction processes with gas sensing performance, providing critical theoretical and technical support for the rational design of advanced gas sensors.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"21 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147465923","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 : 2026-03-17DOI: 10.1021/acssensors.5c04649
Santiago Mendoza-Silva, Farbod Alijani, Le-Vaughn Naarden, Roxan Broer, Leo Smeets, Tabea Riepe, Irek Roslon, Aleksandre Japaridze
Rapid and accurate identification of bacterial infections and their resistance to antibiotics is critical to effective clinical decision-making and combating antimicrobial resistance. However, current diagnostic approaches are typically segmented: techniques such as MALDI-TOF provide species identification but cannot assess antibiotic susceptibility, while standard antimicrobial susceptibility (AST) tests are time-consuming and lack concurrent identification capability. In this study, we overcome these limitations by integrating single-cell nanomotion detection using graphene drums with machine learning (ML) algorithms to perform both tasks simultaneously within a single measurement. Nanomotion signals, nanoscale vibrations from single living cells, are recorded in real time and transformed into time-frequency spectrograms, which serve as inputs to ML models trained for robust pattern recognition. Our framework enables the differentiation of Escherichia coli, Staphylococcus aureus, and Klebsiella pneumoniae while simultaneously distinguishing resistant and susceptible strains with 98% precision. By coupling highly sensitive graphene nanomotion sensors with advanced ML tools, our approach delivers label-free bacterial diagnostics, offering both identification and susceptibility profiling at the single-cell level within a couple of hours.
{"title":"Single-Cell Nanomotion and Machine Learning for Parallel Bacterial Identification and Antibiotic Screening","authors":"Santiago Mendoza-Silva, Farbod Alijani, Le-Vaughn Naarden, Roxan Broer, Leo Smeets, Tabea Riepe, Irek Roslon, Aleksandre Japaridze","doi":"10.1021/acssensors.5c04649","DOIUrl":"https://doi.org/10.1021/acssensors.5c04649","url":null,"abstract":"Rapid and accurate identification of bacterial infections and their resistance to antibiotics is critical to effective clinical decision-making and combating antimicrobial resistance. However, current diagnostic approaches are typically segmented: techniques such as MALDI-TOF provide species identification but cannot assess antibiotic susceptibility, while standard antimicrobial susceptibility (AST) tests are time-consuming and lack concurrent identification capability. In this study, we overcome these limitations by integrating single-cell nanomotion detection using graphene drums with machine learning (ML) algorithms to perform both tasks simultaneously within a single measurement. Nanomotion signals, nanoscale vibrations from single living cells, are recorded in real time and transformed into time-frequency spectrograms, which serve as inputs to ML models trained for robust pattern recognition. Our framework enables the differentiation of <i>Escherichia coli</i>, <i>Staphylococcus aureus</i>, and <i>Klebsiella pneumoniae</i> while simultaneously distinguishing resistant and susceptible strains with 98% precision. By coupling highly sensitive graphene nanomotion sensors with advanced ML tools, our approach delivers label-free bacterial diagnostics, offering both identification and susceptibility profiling at the single-cell level within a couple of hours.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"26 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147465924","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}
Liquid-metal textile electronics exhibit exceptional electrical conductivity, with breathability and wearer comfort unmatched by traditional patches. However, the intrinsically high surface tension of liquid metals promotes interfacial failure during sustained sweating, rubbing, and deformation, resulting in severe signal degradation. This problem is further exacerbated on cotton substrates with better sweat absorption and skin compatibility, as the dense lint layer hinders uniform wetting and integration. To address this, we engineered the wettability and surface functionality of eutectic gallium−indium liquid metals using biogenic inositol hexaphosphate and applied mechano-chemical treatment to anchor the liquid-metal conductive micronetworks onto cotton fibers via hydrogen-coordination bonds. This yields interfaces stable through 15,000 mechanical deformation cycles, 7-day water/sweat immersion, and 120 min of high-speed laundering. In electrophysiological monitoring, the signal-to-noise ratio remains at 22.82 dB after repeated wear, exposure, and contamination, outperforming commercial gel electrodes (12.70 dB). In endurance and strength training, the device captures precise electrophysiological features and anomalies, demonstrating strong potential for future real-time physiological risk assessment in dynamic athletic settings.
{"title":"Mechano-Chemical Interfaces Enabling Permeable, Durable Liquid-Metal Textile Electronics for Athletic Electrophysiology","authors":"Xiaosen Pan, Yi Niu, Yuheng Lv, Jia Zhao, Xueyong Xie, Ruiming Liu, Zhao Wei, Lili Han, Feng Xu, Yunsheng Fang","doi":"10.1021/acssensors.5c03757","DOIUrl":"https://doi.org/10.1021/acssensors.5c03757","url":null,"abstract":"Liquid-metal textile electronics exhibit exceptional electrical conductivity, with breathability and wearer comfort unmatched by traditional patches. However, the intrinsically high surface tension of liquid metals promotes interfacial failure during sustained sweating, rubbing, and deformation, resulting in severe signal degradation. This problem is further exacerbated on cotton substrates with better sweat absorption and skin compatibility, as the dense lint layer hinders uniform wetting and integration. To address this, we engineered the wettability and surface functionality of eutectic gallium−indium liquid metals using biogenic inositol hexaphosphate and applied mechano-chemical treatment to anchor the liquid-metal conductive micronetworks onto cotton fibers via hydrogen-coordination bonds. This yields interfaces stable through 15,000 mechanical deformation cycles, 7-day water/sweat immersion, and 120 min of high-speed laundering. In electrophysiological monitoring, the signal-to-noise ratio remains at 22.82 dB after repeated wear, exposure, and contamination, outperforming commercial gel electrodes (12.70 dB). In endurance and strength training, the device captures precise electrophysiological features and anomalies, demonstrating strong potential for future real-time physiological risk assessment in dynamic athletic settings.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"50 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147465921","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 : 2026-03-16DOI: 10.1021/acssensors.5c04648
Yueru Jiang,Yu Wang,Tianshuang Wang,Liupeng Zhao,Dan Li,Xueying Kou,Peng Sun,Geyu Lu
Recent advances in flexible metal-organic framework (MOF) films have injected momentum into the development of wearable gas sensors. However, current MOF-based wearable sensors suffer from mutual interference and often compromise in power consumption and wearing comfort, limiting their suitability for skin-interfaced applications. Here, we report a wireless, battery-free, wearable gas sensor patch based on a flexible inductance-capacitance (LC) resonator. This sensor features a bilayer flexible film composed of a 2D bimetallic Cu/Co-HHTP conjugate MOF (c-MOF) sensing layer and a Pd/SSZ-13 zeolite overlayer. Specifically, the zeolite overlayer functions as an NO2-adsorbing interface that captures incoming NO2 molecules, thereby preventing them from reacting with the underlying 2D c-MOF sensing layer. Accordingly, the wireless sensor achieves linear and interference-resistant detection of low concentrated NH3 even in the presence of NO2, while maintaining excellent mechanical flexibility, cyclic stability, and negligible baseline drift, exhibiting less than 6.2% response attenuation after repeated bending at 120°. The performance of the device is further validated through a skin-adherent, wireless, passive sensing system capable of continuous NH3 monitoring in complex environments. The proposed wireless wearable MOF-based sensor patch is highly transformative, offering benefits for various wearable applications. Device performance under high-humidity conditions is still constrained, indicating that further optimization is necessary.
{"title":"Wireless Wearable MOF-Based NH3 Gas Sensor Patch with a Zeolite Overlayer for Suppressing NO2 Interference","authors":"Yueru Jiang,Yu Wang,Tianshuang Wang,Liupeng Zhao,Dan Li,Xueying Kou,Peng Sun,Geyu Lu","doi":"10.1021/acssensors.5c04648","DOIUrl":"https://doi.org/10.1021/acssensors.5c04648","url":null,"abstract":"Recent advances in flexible metal-organic framework (MOF) films have injected momentum into the development of wearable gas sensors. However, current MOF-based wearable sensors suffer from mutual interference and often compromise in power consumption and wearing comfort, limiting their suitability for skin-interfaced applications. Here, we report a wireless, battery-free, wearable gas sensor patch based on a flexible inductance-capacitance (LC) resonator. This sensor features a bilayer flexible film composed of a 2D bimetallic Cu/Co-HHTP conjugate MOF (c-MOF) sensing layer and a Pd/SSZ-13 zeolite overlayer. Specifically, the zeolite overlayer functions as an NO2-adsorbing interface that captures incoming NO2 molecules, thereby preventing them from reacting with the underlying 2D c-MOF sensing layer. Accordingly, the wireless sensor achieves linear and interference-resistant detection of low concentrated NH3 even in the presence of NO2, while maintaining excellent mechanical flexibility, cyclic stability, and negligible baseline drift, exhibiting less than 6.2% response attenuation after repeated bending at 120°. The performance of the device is further validated through a skin-adherent, wireless, passive sensing system capable of continuous NH3 monitoring in complex environments. The proposed wireless wearable MOF-based sensor patch is highly transformative, offering benefits for various wearable applications. Device performance under high-humidity conditions is still constrained, indicating that further optimization is necessary.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"20 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147462259","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 : 2026-03-16DOI: 10.1021/acssensors.5c04533
Qikun Wei,Qianyu Wang,Águeda Molinero-Fernández,Daniel Rojas,Rubén Zapata-Pérez,Åsa Konradsson-Geuken,Gastón A. Crespo,María Cuartero
Herein, we have developed a microneedle-based oxygen sensor wearable patch (O2 MN) designed for real-time, minimally invasive detection of dermal ISF oxygen levels. This work pioneers the use of platinum nanoparticles as the sensing element for oxygen detection within a microneedle platform, enabling high electrochemical sensitivity at a mild applied potential. The wearable patch integrates the nanoparticle-based microneedle as the working electrode and a Ag/AgCl ink-modified microneedle as the counter/reference electrode, operating at an applied potential of −0.3 V to detect a wide range of oxygen (10–254 μM) with high sensitivity (−0.51 nA μM−1) and a rapid response time (9 s). The analytical assessment revealed excellent performance, including high reversibility (RSD = 3.4%), repeatability (RSD = 5.2%), medium-term stability (1.9% deviation over 90 min), acceptable reproducibility (6.6%), and mechanical reliability during skin insertion. Notably, to the best of our knowledge, this study represents the first comprehensive evaluation of the performance of an oxygen microneedle sensor, including systematic in vitro, on-body, and in vivo experiments. The sensor’s accuracy was validated with a Pearson correlation coefficient of 0.99 for in vitro tests, and on-body oxygen measurements in euthanized rats highlighted the reliability of the O2 MN patch for dermal ISF oxygen detection. In vivo studies further revealed a strong positive correlation (Pearson correlation coefficient = 0.83) between dermal ISF and blood oxygen levels, underscoring the O2 MN patch’s potential for biomedical applications through real-time, minimally invasive monitoring.
{"title":"Oxygen Detection in Dermal Interstitial Fluid with Microneedles Based on Platinum Nanoparticles","authors":"Qikun Wei,Qianyu Wang,Águeda Molinero-Fernández,Daniel Rojas,Rubén Zapata-Pérez,Åsa Konradsson-Geuken,Gastón A. Crespo,María Cuartero","doi":"10.1021/acssensors.5c04533","DOIUrl":"https://doi.org/10.1021/acssensors.5c04533","url":null,"abstract":"Herein, we have developed a microneedle-based oxygen sensor wearable patch (O2 MN) designed for real-time, minimally invasive detection of dermal ISF oxygen levels. This work pioneers the use of platinum nanoparticles as the sensing element for oxygen detection within a microneedle platform, enabling high electrochemical sensitivity at a mild applied potential. The wearable patch integrates the nanoparticle-based microneedle as the working electrode and a Ag/AgCl ink-modified microneedle as the counter/reference electrode, operating at an applied potential of −0.3 V to detect a wide range of oxygen (10–254 μM) with high sensitivity (−0.51 nA μM−1) and a rapid response time (9 s). The analytical assessment revealed excellent performance, including high reversibility (RSD = 3.4%), repeatability (RSD = 5.2%), medium-term stability (1.9% deviation over 90 min), acceptable reproducibility (6.6%), and mechanical reliability during skin insertion. Notably, to the best of our knowledge, this study represents the first comprehensive evaluation of the performance of an oxygen microneedle sensor, including systematic in vitro, on-body, and in vivo experiments. The sensor’s accuracy was validated with a Pearson correlation coefficient of 0.99 for in vitro tests, and on-body oxygen measurements in euthanized rats highlighted the reliability of the O2 MN patch for dermal ISF oxygen detection. In vivo studies further revealed a strong positive correlation (Pearson correlation coefficient = 0.83) between dermal ISF and blood oxygen levels, underscoring the O2 MN patch’s potential for biomedical applications through real-time, minimally invasive monitoring.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"47 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147462260","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：