Advanced Sensor Research最新文献

Achieving accurate reconstruction of spatial pressure distributions remains a challenge for flexible robotic sensor arrays due to issues such as signal crosstalk and spatial ambiguity. This study presents a flexible sensor array based on eutectic gallium-indium (EGaIn) liquid metal microchannels, which enables high-fidelity shape reconstruction through a combined theoretical and algorithmic framework. We establish a resistance-sum model integrated with a bipartite graph mapping to theoretically analyze and guarantee uniqueness in pressure localization. Experimental and simulation results demonstrate that single-point and continuous multi-point pressures can be uniquely localized, whereas discrete distributions may exhibit ambiguity when pressure points lack row or column continuity, such as in cross-row or cross-column patterns, due to multiple equivalent edge sets in the bipartite graph. Furthermore, we develop a threshold-based reconstruction method that significantly enhances the restoration of complex morphologies, including squares, square rings, and circles. This work provides a robust foundation for high-fidelity shape reconstruction in flexible tactile sensing practices.

The rapid evolution of neuroscience and bioelectronics has intensified the demand for highly sensitive, selective, and miniaturized biosensors capable of monitoring neurochemical activity with high spatial and temporal resolution. Among these, microfabricated thin-film biosensors have emerged as a powerful platform for the detection of neurotransmitters and small molecules, owing to their ultrathin form factor, mechanical flexibility, and compatibility with implantable systems. Design strategies, material innovations, and functional surface chemistries are now central to enabling real-time, in vivo monitoring with minimal tissue disruption and long-term stability. This review covers the recent progress in microfabricated biosensors, focusing on electrochemical, optical, acoustic, and magnetic modalities for the detection of key neurotransmitters, such as dopamine, serotonin, glutamate, and acetylcholine, as well as biologically relevant small molecules, including glucose, lactate, hydrogen peroxide, and nitric oxide. The integration of thin-film sensors for inflammatory and neurodegenerative disease biomarkers, such as cytokines (e.g., IL-6, TNF-α), amyloid-β, and tau proteins, is also discussed. Key challenges such as drift, biofouling, and signal specificity are critically examined alongside emerging solutions. Finally, current and future applications ranging from fundamental neuroscience and brain-machine interfaces to personalized medicine emphasize the potential of thin-film biosensing technologies in real-world biomedical scenarios.

Glycoprotein 88 (GP88) is a secreted biomarker overexpressed in various cancers, as well as neurological and inflammatory diseases. In this study, we introduce the first disposable electrochemical immunosensor for GP88 detection that is built on a screen-printed carbon electrode modified with carboxylated multi-walled carbon nanotubes. Surface carboxyl groups are activated using EDC/NHS chemistry, followed by covalent attachment of streptavidin to facilitate the capture of a biotinylated anti-GP88 antibody. When exposed to GP88, the sensor shows a 19% increase in charge-transfer resistance, used as the sensor's response parameter, indicating a binding between GP88 and its biorecognition element. Reproducibility is confirmed with a relative standard deviation (RSD) of 4.05% across multiple trials, demonstrating reliable sensor fabrication. The limit of detection was estimated at 52 ng/mL, with a linear range of 25500 ng/mL. The specificity of the sensor is verified by exposing the bio-electrode to a human serum albumin control, which causes negligible signal changes. We have also concluded that maintaining streptavidin hydration during bio-electrode assembly is critical for preserving biotin-binding activity. To our knowledge, this is the first reported electrochemical platform for direct quantification of GP88, providing groundwork for further optimization of GP88 detection in an electroanalytical manner.

Novel cryptocyanine-based DNA-binding fluorescent probes were developed by introducing side chains with varying polarity to the dye scaffold. This structural modification improves water solubility, reduces aggregation in aqueous media, and enhances DNA binding affinity. Upon binding to DNA, the derivatives exhibit a high increase in fluorescence quantum yield, demonstrating their potential as fluorogenic DNA probes. The photophysical behavior of the dyes is systematically investigated using spectroscopic techniques, focusing on their environment-sensitive emission properties. These results highlight the importance of environmentally responsive dye scaffolds in the development of fluorogenic tools for nucleic acid detection and diagnostic applications.

A major challenge in point-of-care (PoC) diagnostics is developing low-cost, scalable sensing platforms that provide high sensitivity, multiplexing capability, and intelligent data interpretation—without dependence on bulky instrumentation. In this perspective, we focus on pattern-recognition-based printable on-paper PoC sensors, rather than conventional lock-and-key receptor-specific systems, as a more practical and adaptable strategy for cellulose substrates. Paper's intrinsic properties—biodegradability, capillarity, and affordability—combined with its limited molecular selectivity make it ideally suited for cross-reactive sensor arrays, where analyte discrimination arises from collective response patterns rather than single-site binding. We discuss how these systems leverage compatibility with scalable printing techniques and explore surface modifications and material strategies to overcome challenges such as roughness, thermal instability, and moisture sensitivity. The Perspective further reviews key printing methods spanning accessible prototyping to high-throughput fabrication and highlights the shift toward array-based sensing coupled with machine learning (ML) for data interpretation. Core ML approaches—including preprocessing, classification, clustering, and regression—are discussed in the context of multidimensional signal analysis and model validation. Together, these insights outline a pathway toward intelligent, scalable, and REASSURED-aligned PoC diagnostic platforms.

Indoor mold infestations lead to adverse effects on air quality and thus pose significant health risks to humans. Traditional methods for mold detection and identification are time-consuming and costly. In this study, the application of an electronic nose as a highly reliable tool for detecting and identifying mold is explored. Two common indoor mold species, Stachybotrys chartarum and Chaetomium globosum, each separately grown on two different substrates, are investigated. Our e-nose uses vapor-liquid-solid-grown, UV-activated SnO₂ nanowires as the chemiresistive sensing material. Linear discriminant analysis (LDA) is used for classification. Moreover, novelty detection is enabled by default using decision boundaries. While the conventional LDA only shows mediocre classification results, improved versions can achieve an average F1-score of 98.37%. Therefore, our results demonstrate that the e-nose can not only detect but also identify different mold genera, and thus making a significant step toward fast, objective, and cost-effective indoor air quality monitoring.

Sialic acid is an important biomarker for oral diseases, including cancer. We show that electropolymerization of aminophenylboronic acid onto laser-induced graphene substrate in the presence of sialic acid results in the formation of a molecularly imprinted polymer. Removal of the template sialic acid makes the film capable of subsequent recognition of this analyte. Interaction of the sensor film with the analyte is then tracked using electrochemical approaches in the presence of an external redox-couple, differential pulse voltammetry showing the clearest analytical signal (sensitivity of 14.113 µA/mm). The studies comparing the imprinted and non-imprinted samples show that the effect of imprinting is indeed the cause of the selective detection capabilities of the electropolymerized film, exhibiting an average imprinting factor of around 12.72. It is demonstrated that the sensor can measure sialic acid in a clinically relevant range of salivary concentrations (LOD = 0.598 mm), being able to recognize threshold levels associated with cancerous processes. The sensor shows good selectivity to the chosen SA analyte in the tests with common saliva interferents: proteins and glucose. While performance in real samples of unstimulated whole saliva is lacking, the developed sensor shows potential for use in lab and point-of-care assessments.

Sialic acid is an important biomarker for oral diseases, including cancer. We show that electropolymerization of aminophenylboronic acid onto laser-induced graphene substrate in the presence of sialic acid results in the formation of a molecularly imprinted polymer. Removal of the template sialic acid makes the film capable of subsequent recognition of this analyte. Interaction of the sensor film with the analyte is then tracked using electrochemical approaches in the presence of an external redox-couple, differential pulse voltammetry showing the clearest analytical signal (sensitivity of 14.113 µA/mm). The studies comparing the imprinted and non-imprinted samples show that the effect of imprinting is indeed the cause of the selective detection capabilities of the electropolymerized film, exhibiting an average imprinting factor of around 12.72. It is demonstrated that the sensor can measure sialic acid in a clinically relevant range of salivary concentrations (LOD = 0.598 mm), being able to recognize threshold levels associated with cancerous processes. The sensor shows good selectivity to the chosen SA analyte in the tests with common saliva interferents: proteins and glucose. While performance in real samples of unstimulated whole saliva is lacking, the developed sensor shows potential for use in lab and point-of-care assessments.

Nanocomposites

An electrochemical platinum microelectrode is decorated with carbon nanotubes bearing redox-active orange polyoxovanadate octahedra. Each octahedron anchors ribbon-like aptamer chains that capture target protein biomolecules, illustrating molecular detection from a fluid sample. More details can be found in the Research Article by Kirill Monakhov and co-workers (DOI: 10.1002/adsr.202500080). Cover artwork created by Eric Vogelsberg