Search Results (507)

Disease-specific alpha-synuclein (αsyn) strains have been linked to different synucleinopathies. Current αsyn biomarkers are limited to binary detection of pathogenic αsyn in peripheral tissue biopsies or fluids, limiting differential diagnosis. Hence, there is an urgent need for methods that allow strain-specific detection and characterization of αsyn strain architecture. Notably, luminescent conjugated oligothiophenes (LCOs) have been successfully used to detect distinct protein strain conformers in prion diseases and Alzheimer’s disease, highlighting their utility in differentiating disease-specific amyloid structures. Species-dependent differences in αsyn structure are increasingly recognized as one of the critical aspects that shape how fibrils form, propagate and interact with molecular LCO probes. Here, we evaluate the potential of the LCO h-FTAA to differentiate species-specific αsyn strains and conduct a translational investigation using peripheral cardiac tissue of a gut-first synucleinopathy rodent model. Our in vitro data demonstrate strain-specific probe–fibril interactions, reflecting a differential strain architecture and cellular micro-environment. While h-FTAA binds with comparable efficiency to mouse (mo-) and human (hu-) pre-formed fibrils (PFFs), h-FTAA exhibits markedly lower quantum yield when bound to moPFFs versus huPFFs. Spectral imaging revealed h-FTAA-moPFF binding produces blue-shifted maxima (505–550 nm), contrasting with the red-shifted maxima (545–580 nm) of huPFFs. Fluorescence lifetime imaging microscopy confirmed h-FTAA’s intrinsic sensitivity to species-dependent variations through distinct temporal fluorescence signatures (moPFFs: ~0.60–1.5 ns vs. huPFFs: ~0.65–1.0 ns). Our translational investigation showed h-FTAA binding to peripheral cardiac pathology exhibits comparable red-shifted emission, but distinct fluorescence lifetimes of h-FTAA-bound aggregates in moPFF-injected (~1.0–1.4 ns) versus huPFF-injected (~0.69–0.8 ns) rats. Interestingly, we observed distinct blue-shifted emission profiles in a few selected regions of the heart of moPFF-injected rodents, further characterized by extra-long fluorescence decay shifts (~1.5–1.9 ns), reflecting differences in both aggregate conformation and maturity in moPFF-induced compared with huPFF-induced rats. Taken together, our findings underscore the potential of LCO ligands, like h-FTAA, to enable more precise disease staging and diagnosis through peripheral biopsies, complementing existing αsyn biomarker methods. Full article

Developing an ultrasensitive electrochemiluminescence (ECL) detection platform remains challenging due to the limited enrichment efficiency of ECL emitters and co-reactants at the electrode interface, as well as the insufficient catalytic enhancement of co-reactant conversion. Moreover, simultaneous in situ analyte enrichment and efficient anti-interference capability are often difficult to achieve in a single sensing interface. Herein, a new ECL platform was developed based on nanocatalyst-supported nanochannel-confined surfactant micelle (SM) system, which integrates an enhanced luminol-dissolved oxygen (DO) ECL response for the ultrasensitive detection of antibiotic rifampicin (RIF). A nanocomposite comprising nitrogen-doped graphene quantum dots and a molybdenum disulfide nanosheet (NGQDs@MoS₂) was modified on an indium tin oxide (ITO) electrode. This nanocomposite layer catalyzed the oxygen reduction reaction (ORR), boosting the co-reactant efficiency of DO. Vertically ordered mesoporous silica film filled with surfactant micelles (SM@VMSF) was subsequently grown in situ on the NGQDs@MoS₂ surface. The hydrophobic micelles enable the simultaneous enrichment of luminol, DO, and RIF. Integrating the triple-enrichment effect of surfactant micelles with the high electrocatalytic effect of NGQDs@MoS₂ nanocomposite results in significant ECL enhancement of the luminol–DO. SM@VMSF also provides an excellent molecular sieving effect, endowing the sensor with high anti-interference capability and stability. RIF quenches the ECL signal by consuming superoxide anion radicals, enabling sensitive detection. Detection of RIF was established with a high sensitivity (2927 a.u. per nM) wide linear range (10 pM to 10 μM) and a low limit of detection (LOD, 2.5 pM). The fabricated sensor exhibits good selectivity and high fabrication reproducibility (relative standard deviation, RSD, of 1.9%). Additionally, the determination of RIF in eye drops and seawater samples was realized. This work offers new insights for the design of high-performance ECL sensing interfaces and sensitive detection of RIF. Full article

Cs₃Cu₂I₅ single crystals are regarded as promising next-generation scintillators due to their large Stokes shift and low self-absorption characteristics. However, the cost-effective solution growth method faces critical challenges: the instability of colloidal precursors in solutions and the severe oxidation of Cu⁺ during crystal growth. This study innovatively introduces yttrium chloride (YCl₃) as a dual-functional additive to address both issues simultaneously. The hydrolysis of YCl₃ creates a controlled acidic environment, effectively suppressing the oxidation of Cu⁺; meanwhile, it enhances the stability of colloidal precursors by significantly increasing their surface charge and narrowing the particle size distribution. These synergistic effects enable the rapid growth (approximately 100 h) of near-centimeter-sized Cs₃Cu₂I₅ single crystals with high crystallinity, without the need for inert gas protection. The optimized crystals exhibit exceptional performance: a photoluminescence quantum yield (PLQY) of 93.22% ± 0.47%, a scintillation decay time of 210.04 ns, and a light yield of ~738.14 pe/MeV. This YCl₃-mediated growth strategy establishes an efficient approach for the solution-based synthesis of high-quality Cs₃Cu₂I₅ single crystals, holding great significance for advancing high-sensitivity, environment-stable radiation detection applications such as medical diagnostics and nuclear safety monitoring. Full article

Two-dimensional MoTe₂ is applicable for near-infrared photodetection; however, low absorption in the visible range limits its performance. One way to overcome these limitations is by hybridizing with light-absorbing nanomaterials. In this study, we simulate a CdSe/ZnS quantum dot (QD)-sensitized MoTe₂ photodetector at the coupled electromagnetic and device level. COMSOL Multiphysics demonstrates that the heterostructure of MoTe₂/CdSe/ZnS on a SiO₂/Si substrate exhibits a broadband-visible enhancement in absorption due to QD exciton absorption and Fabry–Perot interferences in the silicon dioxide layer. A staggered type-I band alignment of the CdSe/ZnS/MoTe₂ interface was confirmed by COMSOL analysis, which also permits interfacial charge separation. Simulations of QD integration by Silvaco technology computer-aided design reveal that QD integration increases photocurrent through photogating and carrier transfer. The optimized device has a responsivity and detectivity of 1.3 × 10⁻³, 2 × 10⁻³ A/W, 9.4 × 10⁸, and 1.34 × 10⁹ Jones, and an external quantum efficiency of 0.31% and 0.394% at 520 and 630 nm, respectively, which is significantly better than pristine MoTe₂ photodetectors. These results demonstrate the potential of CdSe/ZnS/MoTe₂ heterostructures for high-performance broadband photodetection and establish a framework for correlating multiscale simulations with material properties and device performance. Full article

Carbon quantum dots (CQDs) and stimuli-responsive hydrogels are advanced functional materials whose hybridization yields CQD-enhanced stimuli-sensitive hydrogels, opening new interdisciplinary avenues for smart material applications. This review systematically summarizes the latest advances in these composites, focusing on synthetic strategies, structure–property modulation mechanisms, and practical applications. Distinct from existing reviews that either investigate CQDs or hydrogels independently or discuss their composites in a single research field, this work features core novelties in integration strategy, application scope and critical analysis: it systematically compares the advantages, limitations and applicable scenarios of three typical CQD–hydrogel integration approaches (physical entrapment, in situ synthesis, covalent conjugation), comprehensively covers the multi-field application progress of the composites and conducts in-depth cross-field analysis of their common scientific issues and technical bottlenecks. By incorporating CQDs, the composites achieve remarkable performance optimizations: 40% improved mechanical toughness, sub-ppm-level heavy metal-sensing sensitivity, and over 80% organic dye photocatalytic degradation efficiency, addressing pure hydrogels’ inherent limitations of insufficient strength and single functionality. These enhancements enable sophisticated applications in biomedical field (real-time biosensing, controlled drug delivery), environmental remediation (pollutant detection/degradation), energy storage, and flexible electronics. The synergistic interplay between CQDs and hydrogels facilitates precise single/multi-stimulus responsiveness (pH, temperature, light), a pivotal advance for precision medicine and intelligent environmental monitoring. Despite promising progress, the large-scale practical application of CQD–hydrogel composites still faces prominent challenges: the difficulty in scalable fabrication with the uniform dispersion of CQDs in hydrogel matrices, poor long-term stability of most composites under physiological cyclic stress (service life < 6 months in practical tests), and low accuracy in discriminating multi-stimuli in complex real-world matrices. Future research should prioritize biomass-based eco-friendly CQD synthesis, machine learning-aided multimodal responsive systems, and 3D bioprinting for scalable manufacturing. Full article

The detection of ammonia (NH₃) at room temperature is of significant importance for environmental monitoring, industrial safety and early disease diagnosis. In this work, a novel room-temperature ammonia sensor was developed by combining graphene oxide with WO₃ quantum dots. The as-fabricated sensor exhibited excellent comprehensive sensing performance, including high sensitivity, rapid response, outstanding selectivity, and reliable long-term stability. Specifically, when exposed to 10 ppm NH₃, the sensor based on 1.5% GO@WO₃ nanocomposites achieved a frequency shift of 578 Hz, which was 6.4 times that of the pure WO₃ QDs sensor. The theoretical limit of detection (LOD) of the sensor was calculated to be 60 ppb, enabling ppb-level NH₃ detection. In addition, the sensor demonstrated good long-term stability over a two-week period. The enhanced performance of the GO@WO₃ nanocomposite sensor is attributed to the formation of an ohmic contact between GO and WO₃, which eliminates charge transfer barriers, promotes oxygen adsorption, and amplifies the sensing signal. This work provides a simple, efficient, and practical solution for room-temperature NH₃ detection, offering significant advantages over traditional single-component sensors. Full article

We report the enhancement of organic photodetector (OPD) performance through the incorporation of CsPbBr₃ perovskite nanocrystals (PNCs) into P3HT:PCBM devices. The optimized device (HPD_01) exhibits a maximum responsivity of 0.083 A/W and a specific detectivity of ~4.7 × 10¹⁰ Jones, and a minimum NEP of 5.2 × 10⁻¹² W·Hz^−1/2 at the self-powered operating point (V ≈ 0 V), outperforming the nanoparticle-free reference. Frequency- and distance-dependent measurements under visible light communication conditions demonstrate that the optimized device maintains strong signal detection up to 1 MHz and at distances exceeding 15 cm. Notably, the external quantum efficiency spectra reveal an additional contribution in the 450–575 nm range, which is absent in the reference device. This enhancement is consistent with a radiative absorption–reemission energy-transfer mechanism, supported by quantitative spectral overlap analysis showing that 99.5% of the PNC photoluminescence falls within the 450–575 nm EQE enhancement window and that the maximum differential EQE gain occurs at 519 nm—only 2 nm from the PNC emission peak. Our results suggest that controlled PNC incorporation enables efficient optical energy coupling, leading to high-sensitivity, fast-response OPDs suitable for optical communication applications. Full article

The on-chip detection of circularly polarized light is pivotal for advancing applications in quantum optics, information processing, and spectroscopic sensing. However, conventional chiral metasurfaces often suffer from complex multilayer fabrication, material incompatibility, or modest performance, hindering their integration with photonic circuits. Here, we introduce a monolithic all-silicon metasurface that overcomes these limitations through a singular structural innovation. By strategically truncating four corners of a conventional Z-shaped meta-atom, we induce a hybridization of optical modes that profoundly enhances chiral light–matter interaction. This deliberately engineered perturbation yields a colossal circular dichroism with an extinction ratio exceeding 66 dB, a performance that surpasses existing state-of-the-art designs by approximately three orders of magnitude. Furthermore, the proposed metasurface exhibits remarkable fabrication robustness, owing to its single-layer architecture and CMOS-compatible material. We demonstrate that this exceptional metasurface can be directly integrated with a Mercury Cadmium Telluride (MCT) photodetector to form a highly efficient, compact circular polarization detector. Our work provides a simple yet powerful paradigm for creating high-performance chiral photonic devices, paving the way for their widespread adoption in integrated optoelectronics. Full article

PbS quantum dots (QDs) synthesized with oleic acid (OA) ligands suffer from poor charge transport in solid films, necessitating ligand exchange to shorter halide ligands for optoelectronic applications. This study investigates how ligand-exchange temperature governs OA-to-iodide substitution in PbS QDs. At 40 °C, the QD surface shows maximized halide passivation (I/Pb = 0.60) and minimized oxygen-related species (O/Pb = 0.23), suggesting reduced oxygen-associated defect formation and enabling n-type band alignment and reduced trap-mediated losses. PbS QD photodetectors fabricated from the 40 °C-treated QDs have 52% external quantum efficiency (EQE) at 940 nm (vs. 39% at 25 °C), with a responsivity of 0.394 A/W and an estimated detectivity of 2.1 × 10¹³ Jones. Temperature optimization of ligand-exchange provides a straightforward lever to improve device performance and reproducibility. Full article

Future 6G-enabled smart hospital infrastructures will support latency-critical medical operations such as robotic surgery, autonomous monitoring, and real-time clinical decision systems, which require communication mechanisms that ensure both ultra-low latency and long-term cryptographic security. Existing security solutions either rely on classical cryptographic protocols that are vulnerable to quantum attacks or deploy isolated post-quantum primitives without providing a unified framework for secure real-time medical command transmission. This research presents a latency-aware, multi-layered post-quantum security architecture for 6G-enabled smart hospital environments. The proposed framework establishes an end-to-end secure command transmission pipeline that integrates hardware-rooted device authentication, post-quantum key establishment, hybrid payload protection, dynamic access enforcement, and tamper-evident auditing within a coherent system design. In contrast to existing approaches that focus on individual security mechanisms, the architecture introduces a structured integration of Kyber-based key encapsulation and Dilithium digital signatures with hybrid AES-based encryption and legacy-compatible key transport, while Physical Unclonable Function authentication provides hardware-bound device identity verification. Zero Trust access control, metadata-driven anomaly detection, and blockchain-style audit logging provide continuous verification and traceability, while threshold cryptography distributes cryptographic authority to eliminate single points of compromise. The proposed architecture is evaluated using a discrete-event simulation framework representing adversarial conditions in realistic 6G medical communication scenarios, including replay attacks, payload manipulation, and key corruption attempts. Experimental results demonstrate improved security and operational efficiency, achieving a 48% reduction in detection latency, a 68% reduction in false-positive anomaly detection rate, and a 39% improvement in end-to-end round-trip latency compared to conventional RSA-AES-based architectures. These results demonstrate that the proposed framework provides a practical and scalable approach for achieving post-quantum secure and low-latency command transmission in next-generation 6G smart hospital systems. Full article

The security of continuous-variable quantum key distribution (CVQKD) systems faces severe challenges from quantum hacking attacks in practical deployments. This paper proposes a novel hybrid quantum-classical neural network (HQCNN) architecture for the detection of quantum hacking attacks. This architecture employs a convolutional neural network (CNN) to extract features from raw pulse signals at the receiver and to reduce spatial dimensionality. Subsequently, the extracted features are mapped into a high-dimensional Hilbert space via angle encoding, and a variational quantum circuit (VQC) is utilized as the core classifier for discrimination. In five-class classification experiments involving local oscillator intensity attacks (LOIA), calibration attacks, saturation attacks, hybrid attacks, and the no-attack state, the HQCNN achieves an overall accuracy of 93%, representing a 6% improvement over the classical residual network (ResNet). In addition, the proposed HQCNN architecture exhibits a significant advantage in parameter efficiency compared with classical deep neural networks. This study provides an efficient intelligent detection scheme for enhancing the practical security of CVQKD systems. Full article

Advancing satellite and CubeSat quantum key distribution (QKD) requires receiver-level engineering trade studies, because secure-key feasibility in space is limited by single-photon detectors (SPDs) operating under SWaP, thermal, and radiation constraints. However, the question arises: does the literature provide sufficiently consistent evidence to guide detector selection for space QKD? This systematic evidence map examines how recent research connects SNSPDs, Si SPAD/APD, InGaAs SPAD/APD, and NFAD variants to CubeSat QKD and space-based quantum communication links. To do so, a concept-token methodology identifies mission contexts and detector families through targeted keywords and key phrases, followed by structured extraction of detection efficiency η, dark count rate (DCR), timing jitter, receiver timing window Δt, operating mode, temperature/cooling, and radiation evidence. The results show an upward trend in publications, with many appearing in the last two years. SNSPDs and APD/SPAD families are most regularly discussed, yet key parameters—especially η, jitter, and explicit Δt—are reported unevenly, limiting cross-study comparability. CubeSat-tagged studies emphasize APD/SPAD feasibility and radiation-driven DCR evolution, while SNSPDs remain performance-leading but cryogenics-limited. Standardized reporting of η, DCR, jitter, Δt, temperature, and radiation conditions emerges as a practical avenue for accelerating deployable space-QKD receivers. Full article

This study presents a SCAPS-1D-based numerical optimization of an organic ultraviolet (UV) photodetector employing an FTO/PTB7/Spiro-OMeTAD/Au device architecture. The novelty of this work lies in a simulation-guided, UV-specific optimization strategy that combines thickness engineering, controlled doping, and contact work-function tuning to achieve intrinsic spectral selectivity without external optical filters. We systematically optimize material and device parameters, including active layer thicknesses, donor and acceptor densities, and the metal electrode work function, to enhance responsivity, detectivity, and spectral performance. Simulations identify optimal thicknesses of 1200 nm for PTB7 and 1000 nm for Spiro-OMeTAD, with donor concentrations of 1 × 10²⁰ cm⁻³ and 1 × 10¹⁸ cm⁻³, respectively. A comparative contact analysis demonstrates that replacing aluminum with gold (Au) forms a near-ohmic back contact, leading to improved hole extraction and suppressed dark current due to favorable energy-level alignment. The optimized device achieves a peak external quantum efficiency of approximately 80% in the 300–400 nm ultraviolet range, with a responsivity up to 0.4 A/W. The UV selectivity originates from the absorption characteristics of PTB7 combined with suppressed long-wavelength charge collection, resulting in a negligible response in the visible–near-infrared region. These results confirm the device’s strong potential for high-sensitivity, solar-blind UV photodetection. By integrating practical material selection with physically consistent SCAPS-1D optoelectronic modeling, this work provides a robust design framework to guide the development of next-generation organic UV photodetectors for environmental sensing, biomedical diagnostics, and wearable optoelectronics. Full article

This study reports the precise synthesis of red-emitting gold–silver bimetallic nanoclusters (Au-AgNCs) via a one-pot hydrothermal method using thiolactic acid as both the ligand and reducing agent. The Au-AgNCs possess an average diameter of 1.85 nm and exhibit strong fluorescence emission at 687 nm. Furthermore, they display notable assembly-induced emission enhancement (AIEE) properties. Upon assembly with bovine serum albumin (BSA), their fluorescence quantum yield significantly increases from 2.50% to 7.78%. Then Au-AgNCs@BSA assembly was employed as a ratiometric fluorescence sensor for the detection of chlortetracycline (CTC). In the presence of CTC, the original red emission of the assembly at 687 nm remained stable, while a new blue emission emerged at 420 nm and intensified progressively with CTC concentration. The ratio of the two emission intensities (I₄₂₀/I₆₈₇) exhibited an excellent linear correlation with CTC concentration over the range of 0.10 to 15 μM, with a limit of detection (LOD) of 20 nM. Notably, the sensor demonstrated exceptional selectivity for CTC, showing negligible response to common interfering substances such as metal ions, anions, amino acids, and crucially, other tetracycline antibiotics (tetracycline, oxytetracycline, and doxycycline). The practical applicability of the sensor was validated through the determination of spiked CTC in real water samples, achieving satisfactory recovery rates. In conclusion, this work accomplishes two key objectives: the development of novel AIEE-active Au-Ag bimetallic nanoclusters and the design of an efficient ratiometric sensing strategy. This approach enables the highly selective and sensitive detection of CTC, offering a promising tool for environmental monitoring. Full article

In today’s fast-changing digital environment, cyber-physical systems face escalating security challenges due to increasingly sophisticated cyberattacks. Artificial Intelligence (AI) has emerged as a powerful enabler of modern cyberattack detection, offering scalable, accurate, and adaptive solutions to counter dynamic threats. This paper provides a comprehensive review of recent advancements in AI-based cyberattack detection, focusing on Machine Learning (ML), Deep Learning (DL), Reinforcement Learning (RL), Federated Learning (FL), and emerging techniques such as generative AI, neuro-symbolic AI, swarm intelligence, lightweight AI, and quantum Computing. We evaluate the strengths and limitations of these approaches, highlighting their performance on benchmark datasets. The review discusses traditional signature-based Intrusion Detection Systems (IDS) and their limitations against novel attack patterns, contrasted with AI-driven anomaly-based and hybrid detection methods that improve detection rates for unknown and zero-day attacks. Key challenges, including computational costs, data quality, privacy concerns, and model interpretability, are analysed alongside the role of Explainable AI (XAI) in enhancing trust and transparency. The impact of computational resources, dataset representativeness, and evaluation metrics on AI model performance is also explored. Furthermore, we investigate the potential of lightweight AI for resource-constrained environments like IoT and edge devices, and quantum computing’s role in advancing detection efficiency and cryptographic security. The paper also draws attention to future research directions, particularly the development of up-to-date datasets, integration of hybrid quantum–classical models, and optimisation of asynchronous FL protocols to address evolving cybersecurity challenges. This study aims to inspire innovation in AI-driven cyberattack detection, fostering robust, interpretable, and efficient solutions for securing complex digital environments. Full article