Advanced Sensor Research最新文献

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.

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

Urea, a nitrogenous organic compound resulting from protein metabolism, is excreted as a waste product in urine. Elevated blood urea levels are associated with severe health conditions, including chronic kidney disease (CKD) and liver failure. Thus, monitoring urea levels is essential for CKD patients and individuals with metabolic disorders that heighten the risk of CKD. While existing diagnostic technologies offer high sensitivity and specificity, they are often expensive, require skilled operators, involve lengthy processing times, and are typically invasive and discontinuous. To address these challenges, researchers have developed various biosensor systems for rapid and cost-effective urea detection. This review provides a comprehensive overview of recent advancements in urea biosensing technologies, highlighting key challenges and potential solutions in biosensor design. It examines enzymatic and non-enzymatic urea biosensors, focusing on electrochemical detection techniques such as amperometry and potentiometry for enzymatic sensors and cyclic voltammetry for non-enzymatic sensors. Additionally, it explores material innovations, technological advancements, and strategies to enhance sensitivity, selectivity, portability, and stability. The integration of biosensors with IoT for real-time monitoring and their applications in medical diagnostics are also discussed.

In this modern era, wearable biosensors have emerged as a significant innovation in specialized personal healthcare. While smartphones and smartwatches today can easily measure vital signs and mobility, a new generation of wearable technology quickly emerges, allowing users to monitor their health metrics at the molecular level. Wearable electrochemical microneedle biosensors show the capability of detecting analytes and metabolites in interstitial fluid with minimal invasiveness. The use of microneedle sensing technology revolutionises biosensing techniques and opens new avenues for advancing current biosensors. In situ extraction, monitoring, and painless injection become possible through microneedle biosensors. However, there remains a need for improvement in detection accuracy and accessibility. This review begins with a discussion on the introduction and a comprehensive background of microneedle technology. It then explores different types of microneedles and fabrication methods. Various sensing modalities for microneedle biosensors, such as electrical, electrochemical, Raman, and colorimetric methods, are also discussed. Finally, the practical applications of wearable microneedle biosensors in various fields are examined, followed by a comprehensive conclusion and prospects.

In this modern era, wearable biosensors have emerged as a significant innovation in specialized personal healthcare. While smartphones and smartwatches today can easily measure vital signs and mobility, a new generation of wearable technology quickly emerges, allowing users to monitor their health metrics at the molecular level. Wearable electrochemical microneedle biosensors show the capability of detecting analytes and metabolites in interstitial fluid with minimal invasiveness. The use of microneedle sensing technology revolutionises biosensing techniques and opens new avenues for advancing current biosensors. In situ extraction, monitoring, and painless injection become possible through microneedle biosensors. However, there remains a need for improvement in detection accuracy and accessibility. This review begins with a discussion on the introduction and a comprehensive background of microneedle technology. It then explores different types of microneedles and fabrication methods. Various sensing modalities for microneedle biosensors, such as electrical, electrochemical, Raman, and colorimetric methods, are also discussed. Finally, the practical applications of wearable microneedle biosensors in various fields are examined, followed by a comprehensive conclusion and prospects.

Terahertz (THz) technology holds great promise in biomedical imaging, non-destructive testing, biosensing, and telecommunications, but its adoption is limited by weak light–matter interactions and strong dissipative losses in conventional metamaterials. To overcome these limitations, a dual strategy is introduced that combines interdigitated electric split-ring resonators (ID-eSRRs) with the complex-frequency wave (CFW) technique. Electrical gating from 0–200 V tunes the graphene Fermi level from 0.3756 to 0.6505 eV, providing a wide and continuous resonance shift for fingerprint-aligned sensing. The CFW method reconstructs loss-compensated spectra from real-frequency data, generating virtual gain and markedly sharpening resonances. Simulations show that the optimized ID-eSRR achieves a refractive index sensitivity of 196 GHz/RIU for 100 nm analytes, while CFW amplification increases the quality factor from 8.54 to 427.96, a 50.1-fold enhancement. This improvement enables reliable discrimination of DNA variants with refractive index differences as small as $$ at $$. The demonstrated approach provides a generalizable route to simultaneously enhance sensitivity and $$-factor, thereby overcoming the long-standing sensitivity–$$ trade-off and advancing the development of high-performance THz sensors for ultrasensitive biomedical diagnostics.

Metal halide perovskites (MHPs) have been proven to have excellent direct X-ray detection properties due to their high carrier lifetime product, strong X-ray absorption ability, a low electron-hole pair creation energy, and excellent charge transport properties. Millimeter-thickness polycrystalline MHPs (MPMHPs) can effectively utilize X-rays and have detection performance comparable to single-crystal MHP, and it is less difficult to synthesize. In this paper, we review the direct X-ray detectors and imagers based on MPMHPs. The basic knowledge of X-ray and direct X-ray detectors is introduced. This review focuses on describing in synthesis methods of MPMHPs and their X-ray detection performance. Furthermore, we summarize the X-ray imaging scheme and imaging application results of MPMHPs. Finally, we discuss future optimization methods in material synthesis, device optimization, and imaging applications. We hope that this review will help readers understand the basics of MPMHPs, improve detection performance, and boost imaging applications.