Search Results (990)

Two phenanthroline derivatives, 2-(2,6-diisopropylphenoxy)-9-phenyl-1,10-phenanthroline and 2,9-bis(2,6-diisopropylphenoxy)-1,10-phenanthroline, were synthesized. The unsymmetrical derivative was obtained in high yield through a sequence combining Suzuki coupling and nucleophilic substitution. The crystal structures of both compounds were determined by single-crystal X-ray diffraction and examined by Hirshfeld surface analysis, which outlined the main intermolecular interactions responsible for the packing. The optical properties were studied by UV–Vis absorption and fluorescence spectroscopy in different solvents. The unsymmetrical compound showed stronger intramolecular charge transfer and more pronounced solvatochromism, while the symmetrical analog had a higher fluorescence quantum yield and longer excited-state lifetime. These results demonstrate the role of substitution symmetry in controlling molecular organization and photophysical properties of phenanthroline derivatives, with relevance to sensing and optoelectronic applications. Full article

Intelligent gas sensors are indispensable devices widely used in modern society for environmental monitoring, healthcare, the food industry, and public safety. Recent advancements in wireless communication, cloud storage, computing technologies, and artificial intelligence algorithms have significantly enhanced the intelligence level and performance requirements of these sensors. Particularly in the Internet of Things (IoT) environment, flexible and wearable gas sensors are playing an increasingly important role due to their convenience and real-time monitoring capabilities. This review systematically summarizes the latest progress in intelligent gas sensors, covering conceptual frameworks, working principles, and applications across various fields, as well as the construction of IoT networks using sensor arrays. It provides a comprehensive assessment of recent advancements in intelligent gas sensing technologies, highlighting innovations in device architecture, functional mechanisms, and performance in diverse application environments. Special emphasis is placed on transformative developments in flexible and wearable sensor platforms and the enhanced intelligence achieved through the integration of advanced computational algorithms and machine learning techniques. Finally, a summary and future prospects are presented. Despite significant progress, intelligent gas sensors still face challenges related to sensing accuracy, stability, and cost in future applications. Full article

The widespread presence of antibiotic residues, particularly norfloxacin (NFX), in food products and the environment has raised concern, underscoring the need for sensitive and selective detection methods. In this study, a novel broccoli-derived nitrogen-doped carbon quantum dots (N-CQDs) was synthesized via a green hydrothermal approach, 4-dimethylaminopyridine (DMAP) as both a nitrogen dopant and a functionalizing agent. The synthesized N-CQDs exhibit an average diameter of approximately ~4.2 nm and emit bright blue fluorescence, with a maximum emission at 445 nm upon excitation at 360 nm. A “Turn-ON” response toward NFX was achieved with a detection limit of 0.30 nM, attributed to hydrogen bonding and π–π stacking interactions that suppressed non-radiative decay. Moreover, the sensor demonstrates high selectivity for NFX, effectively distinguishing it from common interfering substances, including other antibiotics, organic acids, and biomolecules. The N-CQDs also exhibit excellent stability under diverse conditions, such as varying pH levels, high ionic strength, and prolonged irradiation. Finally, the practical applicability of the developed sensor was validated by detecting NFX in spiked broccoli extract and milk samples, with recovery rates ranging from 98.2% to 100.1% and relative standard deviations of less than 2.0%. This work presents a sustainable and efficient N-CQD-based fluorescent sensing platform, offering significant potential for rapid and reliable detection of NFX in food safety and environmental monitoring. Full article

The electromagnetic density of states (EM-DOS) plays a crucial role in understanding light–matter interactions, especially at metal–dielectric interfaces. This study explores the impact of interface geometry, material properties, and nanostructures on EM-DOS, with a focus on surface plasmon polaritons (SPPs) and evanescent waves. Using a combination of analytical and numerical methods, the behavior of EM-DOS is analyzed as a function of distance from metal–dielectric interfaces, showing exponential decay with penetration depth. The influence of different metals, including copper, gold, and silver, on EM-DOS is examined. Additionally, the effects of dielectric materials, such as Ti${\mathrm{O}}_2$, PMMA, and ${\mathrm{Al}}_2$${\mathrm{O}}_3$, on the enhancement of electromagnetic field confinement are discussed. The study also investigates the effect of nanostructures, like nanohole and nanopillar arrays, on EM-DOS by calculating effective permittivity and analyzing the interaction of quantum emitters with these structures. Results show that nanopillar arrays enhance EM-DOS more effectively than nanohole arrays, especially in the visible spectrum. The findings provide insights into optimizing plasmonic devices for applications in sensing, quantum technologies, and energy conversion. Full article

We investigated the impact of incorporating quantitative reasoning for deeper sense-making in a Quantum Interactive Learning Tutorial (QuILT) on students’ conceptual performance using a framework emphasizing integration of conceptual and quantitative aspects of quantum optics. In this investigation, we compared two versions of the QuILT that were developed and validated to help students learn various aspects of quantum optics using a Mach Zehnder Interferometer with single photons and polarizers. One version of the QuILT is entirely conceptual while the other version integrates quantitative and conceptual reasoning (hybrid version). Performance on conceptual questions of upper-level undergraduate and graduate students who engaged with the hybrid QuILT was compared with that of those who utilized the conceptual QuILT emphasizing the same concepts. Both versions of the QuILT focus on the same concepts, use a scaffolded approach to learning, and take advantage of research on students’ difficulties in learning these challenging concepts as well as a cognitive task analysis from an expert perspective as a guide. The hybrid and conceptual QuILTs were used in courses for upper-level undergraduates or first-year physics graduate students in several consecutive years at the same university. The same conceptual pre-test and post-test were administered after traditional lecture-based instruction in relevant concepts and after student engaged with the QuILT, respectively. We find that the post-test performance of physics graduate students who utilized the hybrid QuILT on conceptual questions, on average, was better than those who utilized the conceptual QuILT. For undergraduates, the results showed differences for different classes. One possible interpretation of these findings that is consistent with our framework is that integrating conceptual and quantitative aspects of physics in research-based tools and pedagogies should be commensurate with students’ prior knowledge of physics and mathematics involved so that students do not experience cognitive overload while engaging with such learning tools and have appropriate opportunities for metacognition, deeper sense-making, and knowledge organization. In the undergraduate course in which many students did not derive added benefit from the integration of conceptual and quantitative aspects, their pre-test performance suggests that the traditional lecture-based instruction may not have sufficiently provided a “first coat” to help students avoid cognitive overload when engaging with the hybrid QuILT. These findings suggest that different groups of students can benefit from a research-based learning tool that integrates conceptual and quantitative aspects if cognitive overload while learning is prevented either due to students’ high mathematical facility or due to their reasonable conceptual facility before engaging with the learning tool. Full article

The exponential increase in environmental pollutants due to industrialization, urbanization, and agricultural intensification has underscored the urgent need for sensitive, selective, and real-time monitoring technologies. Among emerging analytical tools, organic fluorescent sensors have demonstrated exceptional potential for detecting a wide range of pollutants in water, air, and soil, with a limit of detection (LOD) in the pM–µM range. This review critically examines recent advances in organic fluorescent sensors, focusing on their photophysical properties, molecular structures, sensing mechanisms, and environmental applications. Key categories of organic sensors, including small molecules, polymeric materials, and nanoparticle-based systems, are discussed, highlighting their advantages, such as biocompatibility, tunability, and cost-effectiveness. Comparative insights into inorganic fluorescent sensors, including quantum dots, are also provided, emphasizing their superior photostability and wide operating range (in some cases from pg/mL up to mg/mL) but limited biodegradability and higher toxicity. The integration of nanomaterials and microfluidic systems is presented as a promising route for developing portable, on-site sensing platforms. Finally, the review outlines current challenges and future perspectives, suggesting that fluorescent sensors, particularly organic ones, represent a crucial strategy toward sustainable environmental monitoring and pollutant management. Full article

Dual-mode fluorescent materials are vital in bioimaging, sensing, displays, and lighting, owing to their efficient emission of visible or near-infrared light. Traditional optimization methods, including empirical experiments and quantum chemical computations, suffer from high costs, high labor intensities, and difficulties capturing complex relationships among molecular structures, synthesis parameters, and key photophysical properties. In this review, fundamental principles, key methodologies, and representative applications of machine learning (ML) in predicting fluorescent material performance are systematically summarized. The core ML techniques covered include supervised regression, neural networks, and physics-informed hybrid frameworks. The representative fluorescent materials analyzed encompass aggregation-induced emission (AIE) luminogens, thermally activated delayed fluorescence (TADF) emitters, quantum dots, carbon dots, perovskites, and inorganic phosphors. This review details the modeling approaches and typical workflows—such as data preprocessing, descriptor selection, and model validation—and highlights algorithmic optimization strategies such as data augmentation, physical constraints embedding, and transfer learning. Finally, prevailing challenges, including limited high-quality data availability, weak model interpretability, and insufficient model transferability, are discussed. Full article

We report combined scanning probe microscopy and electrical measurements to investigate local electronic transport in reduced graphene oxide (rGO) devices. We demonstrate that quantum transport in these materials can be significantly tuned by the electrostatic potential applied with a conducting atomic force microscope (AFM) tip. Scanning gate microscopy (SGM) reveals a clear p-type response in which local gating modulates the source–drain current, while scanning impedance microscopy (SIM) indicates corresponding shifts of the Fermi level under different gating conditions. The observed transport behavior arises from the combined effects of AFM tip-induced Fermi-level shifts and defect-mediated scattering. These results show that resonant scattering associated with impurities or structural defects plays a central role and highlight the strong influence of local electrostatic potentials on rGO conduction. Consistent with this electrostatic control, the device also exhibits chemical gating and sensing: during exposure to electron-withdrawing molecules (acetone), the source–drain current increases reversibly and returns to baseline upon purging with air. Repeated cycles over 15 min show reproducible amplitudes and recovery. Using a simple transport model, we estimate an increase of about $40\%$ in carrier density during exposure, consistent with p-type doping by electron-accepting analytes. These findings link nanoscale electrostatic control to macroscopic sensing performance, advancing the understanding of charge transport in rGO and underscoring its promise for nanoscale electronics, flexible chemical sensors, and tunable optoelectronic devices. Full article

In special relativity, particle trajectories, whether mass-bearing or not, can be traced on the Minkowski spacetime manifold in (3+1)D. Meantime, in quantum mechanics, trajectories in the phase space are not strictly outlined because coordinate and linear momentum cannot be measured simultaneously with arbitrary precision since they do not commute within the Hilbert space formalism. However, from the density matrix representing a quantum system, the extracted information still produces an imperative description of its properties and, furthermore, by appropriately reordering the matrix entries, additional information can be obtained from the same content. Adhering to this line of work, the paper investigates the definition and the meaning of velocity and speed in a typical quantum phenomenon, the disentanglement for a bipartite system when dynamical evolution is displayed in a (3+1)D pseudo-spacetime whose coordinates are constructed from combinations of entries to the density matrix. The formalism is based on the definition of a Minkowski manifold with compact support, where trajectories are defined following the same reasoning and formalism present in the Minkowski manifold of special relativity. The space-like and time-like regions acquire different significations referred to entangled-like and separable-like, respectively. The definition and the sense of speed and velocities of disentanglement follow naturally from the formalism. Depending on the dynamics of the physical state of the system, trajectories may meander between regions of entanglement and separability in the space of new coordinates defined on the Minkowski manifold. Full article

Aimed at addressing the increasingly serious problem of adulteration in Xihu Longjing, a catechin-targeted nano-enhanced visual and fluorescent dual-mode sensor array was constructed by nano porphyrins and quantum dots (QDs) for the precise analysis of Xihu Longjing from adjacent origins. This sensor array realizes the quantitative analysis of catechin enantiomers in Xihu Longjing through the selective combination of sensing units. It can accurately identify adjacent Xihu Longjing teas with different grades and storage times and can precisely detect samples with a low proportion of adulteration. At the same time, the flavor quality and antioxidant performance of Xihu Longjing tea can also be quantitatively evaluated. The dual-mode sensor array design proposed in this study provides a new idea for detecting minor differences in food authenticity and has significant application value for quality control in the tea industry. Full article

Near-ultraviolet photoluminescence liquid-crystalline molecules (PLLCs) have attracted attention for temperature-responsive photoluminescence (PL) modulation and ON/OFF sensing under external stimuli. We recently developed mesogenic dimers composed of two hexyloxy-substituted, fluorinated tolane-type cores linked by alkylene-1,n-dioxy chains that exhibited near-UV PL in the solid state. However, the formation of LC phases and the temperature range of the LC state were limited. To improve LC phase stability, in this study, we extended the flexible terminal chains and repositioned the fluorinated aromatic rings from the outer to the inner core positions. Accordingly, we synthesized mesogenic dimers with even-numbered alkylene-1,n-dioxy linkers (hexylene, octylene, and decylene) and outer- or inner-ring fluorination. Outer-ring fluorination led to high melting temperatures and stable crystalline phases with limited mesophase formation. In contrast, inner-ring fluorination induced nematic phases upon heating and cooling owing to zig-zag molecular structures that disrupted crystallinity. Photophysical studies confirmed near-UV PL in solution and solid states; however, the quantum yield of the solution PL was low (<0.01). In the solid state, the PL efficiencies and wavelengths were influenced by the fluorinated aromatic ring position and linker length. This study provides important molecular design criteria for developing stable LC materials with tunable near-UV luminescence for temperature-responsive optical devices. Full article

This study presents a theoretical investigation of platinum-modified single-wall carbon nanotubes (SWCNTs) of types (6.0) and (6.6) for their potential application as gas sensor materials. Quantum chemical calculations using density functional theory (DFT) were performed to evaluate the interaction mechanisms with carbon monoxide (CO) and carbon dioxide (CO₂) molecules. The results revealed that pristine SWCNTs exhibit weak and unstable interactions with CO and CO₂, indicating limited sensing capabilities. However, the modification with platinum atoms significantly enhanced their adsorption properties. The most energetically favorable configuration was found when the platinum atom was located at the center of a C–C bond on the SWCNT surface, ensuring the stability of the metal-functionalized system. The Pt-modified SWCNTs exhibited stable sorption interactions with CO and CO₂, characterized by weak van der Waals forces, enabling the reusability of the sensor without contamination. Additionally, the adsorption of these gas molecules induced changes in the band gap of the nanocomposite system, indicating a variation in conductivity upon gas exposure. The distinct band gap changes for the CO and CO₂ adsorption suggest the selectivity of the sensor towards each gas. Overall, the results demonstrate that platinum modification effectively enhances the sensing performance of SWCNTs, paving the way for the development of highly sensitive and selective nanosensors for CO and CO₂ detection based on changes in electronic properties upon gas adsorption. Full article

Quantum interference can strongly enhance thermoelectric response, with higher-order “supernodes” predicted to yield scalable gains in thermopower and efficiency. A central question, however, is whether such features are intrinsically more fragile to dephasing. Using Büttiker voltage–temperature probes, we establish an order-selection rule: the effective near-node order is set by the lowest among coherent and probe-assisted channels. Supernodes are therefore fragile in an absolute sense because their transmission is parametrically suppressed with order. However, once an incoherent floor dominates, the fractional suppression of thermopower, efficiency, and figure of merit becomes universal and order-independent. Illustrating these principles with benzene- and biphenyl-based junction calculations, we show that the geometry of environmental coupling—through a single orbital or across many—dictates whether coherence is lost by order reduction or by floor building. These results yield general scaling rules for the thermoelectric response of interference nodes under dephasing. Full article

Optically levitated particles in high vacuum offer an exceptionally isolated mechanical platform for photonic control. Effective cooling of their center-of-mass motion is essential not only for enabling ultrasensitive precision sensing but also for opening access to the quantum regime where macroscopic superposition and nonclassical states can be realized. In this review, we present a comprehensive overview of recent advances in active feedback cooling, based on real-time photonic modulation, and passive feedback cooling, driven by optomechanical interactions within optical resonators. We highlight key experimental milestones, including ground state cooling in one and two dimensions, and discuss the emerging applications of these systems in force sensing, inertial metrology, and macroscopic quantum state preparation. Particular attention is given to novel proposals for probing quantum gravity, detecting dark matter and dark energy candidates, and exploring high-frequency gravitational waves. These advancements establish levitated optomechanical systems as a powerful platform for both high-precision metrology and the investigation of fundamental quantum phenomena. Finally, we discuss the current challenges and future prospects in cooling multiple degrees of freedom, device integration, and scalability toward future quantum technologies. Full article

This paper makes two distinct contributions to the security and federated learning communities. First, we identify and empirically demonstrate a critical vulnerability in Krum, a widely deployed Byzantine-resilient aggregation algorithm, showing catastrophic failure (44.7% accuracy degradation) when applied to high-dimensional neural networks. We provide comprehensive analysis of five alternative algorithms and validate FLTrust as a more resilient solution, though requiring trusted infrastructure. This finding has immediate implications for production federated learning systems. Second, we present a rigorous feasibility analysis of quantum-enhanced security operations through simulation-based exploration. We document fundamental deployment barriers including (1) environmental electromagnetic interference exceeding sensor capabilities by 6-9 orders of magnitude, (2) infrastructure costs of USD 3–5M with unproven benefits, (3) an absence of validated correlation mechanisms between quantum measurements and cyber threats, and (4) O($n^2$) scalability constraints limiting deployments to 20 nodes. This is purely theoretical research using simulated data without physical quantum sensors. Physical validation through empirical noise characterization and sensor deployment in operational environments represents the critical next step, though faces significant challenges from EMI shielding requirements and calibration procedures. Together, these contributions provide actionable insights for current federated learning deployments while preventing premature investment in quantum sensing for cybersecurity. Full article