Search Results (221)

Environmental pollution is a global issue presenting risks to ecosystems and human health through release of toxic gases, existence of volatile organic compounds (VOCs) in the environment, and heavy metal contamination of waters and soils. To effectively address this issue, reliable and real-time monitoring technology is imperative. Metal–organic frameworks (MOFs) are a disruptive set of materials with high surface area, tunable porosity, and abundant chemistry to design extremely sensitive and selective pollutant detection. This review article gives an account of recent advances towards sensor technology for MOFs with application specificity towards gas and environment monitoring. We critically examine optical, electrochemical, and resistive platforms and their interfacing with embedded electronics and edge artificial intelligence (edge-AI) to realize smart, compact, and energy-efficient monitoring tools. We also detail critical challenges such as scalability, reproducibility, long-term stability, and secure data management and underscore transforming MOF-based sensors from lab prototype to functional instruments to ensure safe coverage of human health and to bring about sustainable environmental management. Full article

We theoretically analyze the spatial Goos-Hänchen (GH) shifts in symmetric Graphene-Integrated Bragg Gratings (GIBGs), where monolayer graphene arrays act as tunable input/output couplers, and a periodically inserted dielectric layer forms a resonant cavity. By optimizing the cavity design, we achieve a GH shift of 1766λ, surpassing the conventional limit of hundreds of wavelengths under single-parameter tuning. The direction and magnitude can be actively controlled by the graphene’s chemical potential, grating geometry, or dielectric thickness. This mechanism may enable high-sensitivity refractive index sensors or adaptive optical devices. Full article

The metal–dielectric hybrid tetramer metasurface has received a lot of attention in the field of optical sensing owing to the excellent refractive index sensing performance. However, achieving simultaneous high-quality Q-factor, polarization insensitivity, multi-band tunability across visible to near-infrared spectra, and ultra-narrow linewidth is an urgent problem to be solved. To overcome this challenge, we proposed a metal–dielectric yurt tetramer metasurface. The finite-difference time-domain method was used to simulate the sensing properties. We explored the physical mechanism of different resonance modes, optimized the structure parameters of the metasurface, and investigated the influence of incident light and environmental parameters on the sensing properties. The results show that the proposed structure not only possesses a high Q-factor but also exhibits excellent wavelength tunability in the visible to near-infrared band and has polarization insensitivity. By skillfully introducing the structural size perturbation, the surface plasmon resonance mode and two Fano resonance modes are successfully excited at the wavelengths of 737.43 nm, 808.99 nm, and 939.50 nm. The light–matter interaction at the Fano resonance frequencies is highly enhanced so that a maximum refractive index sensitivity, figures of merit (FOM), and Q-factor of 500.94 nm/RIU, 491.12 RIU⁻¹, and 793.13 are obtained. The narrowest full width at half maximum (FWHM) is 1.02 nm, respectively. This work provides a theoretical basis for the realization of a high-performance metasurface refractive index sensor. Full article

To design novel imaging devices, we use masks coded with numerical sequences. These masks work in conjunction with varifocal systems that implement zero-throw tunable magnification. Some masks control field depth, even when the size of the pupil aperture remains fixed. Pairs of vortex masks are used to implement tunable phase radial profiles, like axicons and lenses. The autocorrelation properties of the Barker sequences are applied to the generation of narrow passband windows on the OTF. For this application, we apply Barker matrices in rectangular coordinates. A similar procedure, but now in polar coordinates, is useful for sensing in-plane rotations. We implement geometrical transformations by using zero-throw, tunable, anamorphic magnifications. Full article

Metallic nanoclusters (NCs), composed of a few to a hundred atoms, occupy a unique space between molecules and nanoparticles, exhibiting discrete electronic states, strong photoluminescence, and size-dependent catalytic activity. Their ultrasmall cores (<3 nm) and ligand-controlled surfaces confer tunable optical, electronic, and catalytic properties, making them attractive for diverse applications. In recent years, significant progress has been made toward developing faster, more reproducible, and scalable synthesis routes beyond classical wet-chemical reduction. Emerging strategies such as microwave-, photochemical-, sonochemical-, and catalytically assisted syntheses, together with smart, automation-driven platforms, have improved efficiency, structural control, and environmental compatibility. These advances have accelerated the deployment of NCs in imaging, sensing, and catalysis. Near-infrared emitting NCs enable deep-tissue, high-contrast fluorescence imaging, while theranostic platforms combine diagnostic precision with photothermal or photodynamic therapy, gene delivery, and anti-inflammatory treatment. NC-based sensors allow ultrasensitive detection of ions, small molecules, and pathogens, and atomically precise NCs have enabled efficient CO₂ reduction, water splitting, and nitrogen fixation. Therefore, in this review, we highlight studies reported in the past five years on the synthesis and applications of metallic NCs, linking emerging methodologies to their functional potential in nanotechnology. Full article

This study presents a theoretical investigation of a terahertz (THz) surface plasmon resonance (SPR) optical biosensor utilizing a graphene-integrated Otto configuration. Through systematic numerical simulations, we demonstrate that actively modulating graphene’s conductivity via an external magnetic field enables tunable SPR behavior with high phase sensitivity. The proposed sensor achieves a phase sensitivity of up to $3.1043\times {10}^5$ deg RIU⁻¹ in liquid sensing and $2.5854\times {10}^4$ deg RIU⁻¹ in gas sensing. This simulation-based work establishes a foundational framework for the development of highly sensitive, magneto-optically tunable optical sensors, highlighting their potential in chemical detection and medical diagnostics. Full article

Electrospun nanofibers have emerged as a versatile platform for developing advanced materials with diverse applications, owing to their high surface-area-to-volume ratio and tunable properties. The incorporation of metal oxide nanoparticles, such as titanium dioxide (TiO₂), has proven effective in further enhancing the functional performance of these materials, particularly in optoelectrical, antibacterial, and antioxidant domains. This study presents the first report of electrospun multifunctional nanofibers from a ternary blend of polyvinyl alcohol (PVA), polyvinylpyrrolidone (PVP), and polyacrylamide (PAAm) blended with TiO₂ nanoparticles at 0, 1, 3, and 5 wt.%. The objective was to develop nanocomposites with enhanced structural, optical, electrical, antibacterial, and antioxidant properties for applications in environmental, biomedical, and industrial fields. The nanofibers were characterized using X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), Fourier-transform infrared spectroscopy (FTIR), UV–visible spectrophotometry, and DC electrical conductivity tests. Antibacterial efficacy was assessed against Escherichia coli and Staphylococcus aureus via the Kirby–Bauer disk diffusion method, while antioxidant activity was evaluated using the DPPH radical scavenging assay. Results demonstrated that TiO₂ incorporation increased nanofiber diameters (21.5–35.1 nm), enhanced crystallinity, and introduced Ti–O bonding, confirming successful nanoparticle integration. Optically, the nanocomposites exhibited reduced band gaps (from 3.575 eV to 3.320 eV) and increased refractive indices with higher TiO₂ nanoparticle content, highlighting their potential for advanced optoelectronic devices such as UV sensors and transparent electrodes. Electrically, conductivity improved due to increased charge carrier mobility and conductive pathways, making them suitable for flexible electronics and sensing applications. The 5 wt.% TiO₂-doped nanofibers demonstrated superior antibacterial activity, particularly against E. coli (18.2 mm inhibition zone), and antioxidant performance comparable to ascorbic acid (95.32% DPPH inhibition), showcasing their relevance for biomedical applications like wound dressings and food packaging. These findings highlight the potential of PVA-PVP-PAAm/TiO₂ nanofibers as useful materials for moisture sensors, antibacterial agents, and antioxidants, advancing applications in medical devices and environmental technologies. Full article

The nitrogen-vacancy (NV) center magnetic sensor, leveraging nitrogen-vacancy quantum effects, enables high-sensitivity magnetic field detection via optically detected magnetic resonance (ODMR). However, conventional single-point integrated devices suffer from limitations such as inefficient regional magnetic field detection and challenges in discerning the directional variations of dynamic magnetic fields. To address these issues, this study proposes an array- based architecture that innovatively substitutes the conventional 532 nm laser with quantum-dot light-emitting diodes (QLEDs). Capitalizing on the advantages of QLEDs—including compatibility with micro/nano-fabrication processes, wavelength tunability, and high luminance—a 2 × 2 monolithically integrated magnetometer array was developed. Each sensor unit achieves a magnetic sensitivity of below 26 nT·Hz^−1/2 and a measurable range of ±120 μT within the 1–10 Hz effective bandwidth. Experimental validation confirms the array’s ability to simultaneously resolve multi-regional magnetic fields and track dynamic field orientations while maintaining exceptional device uniformity. This advancement establishes a scalable framework for the design of large-scale magnetic sensing arrays, demonstrating significant potential for applications requiring spatially resolved and directionally sensitive magnetometry. Full article

The photonic spin Hall effect (PSHE) has emerged as a powerful metrological approach for precision measurements. Dynamic manipulation of PSHE through external stimuli could substantially expand its applications. In this work, we present a simple and active modulation scheme for PSHE in a surface plasmon resonance (SPR) structure by exploiting electric-field-tunable refractive indices of electro-optic materials. By applying an electric field, the enhancement of PSHE spin shifts is observed, and the dual-field control can further amplify these spin shifts through synergistic effects in this SPR structure. Notably, various operation modes of external electric field enable the real-time switching between two high-performance sensing functionalities (refractive index detection and angle measurement). Therefore, our designed PSHE sensor based on SPR structure with a simple structure of only three layers not only makes up for the complex structure in multi-functional sensors, but more importantly, this platform establishes a new paradigm for dynamic PSHE manipulation while paving the way for advanced multi-functional optical sensing technology. Full article

Due to increasing demand for the exploration of marine resources, underwater optical wireless sensor networks (UOWSNs) have emerged as a promising solution by offering higher bandwidth and lower latency compared to traditional underwater acoustic wireless sensor networks (UAWSNs), with their existing routing protocols facing challenges in energy consumption and packet forwarding. To address these challenges, this paper proposes an energy-partitioned routing protocol based on an advancement function (EPAR) for UOWSNs. By dynamically classifying the nodes into high-energy and low-energy ones, the proposed EPAR algorithm employs an adaptive weighting strategy to prioritize the high-energy nodes in relay selection, thereby balancing network load and extending overall lifetime. In addition, a tunable advancement function is adopted by the proposed EPAR algorithm by comprehensively considering the Euclidean distance and steering angle toward the sink node. By adjusting a tunable parameter α, the function guides forwarding decisions to ensure energy-efficient and directionally optimal routing. Additionally, by employing a hop-by-hop neighbor discovery mechanism, the proposed algorithm enables each node to dynamically update its local neighbor set, thereby improving relay selection and mitigating the impact of void regions on the packet delivery ratio (PDR). Simulation results demonstrate that EPAR can obtain up to about a 10% improvement in PDR and up to about a 30% reduction in energy depletion, with a prolonged network lifetime when compared to the typical algorithms adopted in the simulations. Full article

In this study, composite films based on phosphorylated polyvinyl alcohol (PVA-P), Ti₃C₂T_x MXene, and cholesteryl acetate (ChLC) were designed and characterized to explore their potential in flexible electronic applications. The incorporation of phosphate groups and ChLC enhanced intermolecular interactions, as confirmed with FTIR spectroscopy. Morphological and optical analyses revealed a transition from homogeneous to phase-separated structures with birefringent textures in ChLC-rich films. Thermal studies demonstrated improved stability and increased glass transition and melting temperatures, particularly in samples with higher ChLC content. Mechanical and dielectric evaluations highlighted the tunability of stiffness, flexibility, permittivity, and dielectric losses depending on MXene and ChLC ratios. These multifunctional films exhibit flame-retardant behavior and show promise for use in stimuli-responsive, sustainable electronic devices such as flexible displays and sensors. Full article

We present a comprehensive study of LED-based optical sensing systems for the classification of waste materials, analyzing recent developments in the field. Accurate identification of materials such as plastics, glass, aluminum, and paper is a crucial yet challenging task in waste management for recycling. The first approach uses short-wave infrared reflectance spectroscopy with commercial Germanium photodetectors and selected LEDs to keep data complexity and cost at a minimum while achieving classification accuracies up to 98% with machine learning algorithms. The second system employes a voltage-tunable Germanium-on-Silicon photodetector that operates across a broader spectral range (400–1600 nm), in combination with three LEDs in both the visible and short-wave infrared bands. This configuration enables an adaptive spectral response and simplifies the optical setup, supporting energy-efficient and scalable integration. Accuracies up to 99% were obtained with the aid of machine learning algorithms. Across all systems, the strategic use of low-cost LEDs as light sources and compact optical sensors demonstrates the potential of light-emitting devices in the implementation of compact, intelligent, and sustainable solutions for real-time material recognition. This article explores the design, characterization, and performance of such systems, providing insights into the way light-emitting and optoelectronic components can be leveraged for advanced sensing in waste classification applications. Full article

Bragg gratings are fundamental components in a wide range of sensing applications due to their high sensitivity and tunability. In this work, we present an augmented Bayesian approach for efficiently acquiring limited but highly informative training data for machine learning models in the design and simulation of Bragg grating sensors. Our method integrates a distance-based diversity criterion with Bayesian optimization to identify and prioritize the most informative design points. Specifically, when multiple candidates exhibit similar acquisition values, the algorithm selects the point that is farthest from the existing dataset to enhance diversity and coverage. We apply this strategy to the Bragg grating design space, where various analytical functions are fitted to the optical response. To assess the influence of output complexity on model performance, we compare different fit functions, including polynomial models of varying orders and Gaussian functions. Results demonstrate that emphasizing output diversity during the initial stages of data acquisition significantly improves performance, especially for complex optical responses. This approach offers a scalable and efficient framework for generating high-quality simulation data in data-scarce scenarios, with direct implications for the design and optimization of next-generation Bragg grating-based sensors. Full article

Metal–Organic Frameworks (MOFs) have emerged as advanced porous crystalline materials due to their highly ordered structures, ultra-high surface areas, fine-tunable pore sizes, and massive chemical diversity. These features, arising from the coordination between an almost unlimited number of metal ions/clusters and organic linkers, have resulted in significant interest in MOFs for applications in gas storage, catalysis, sensing, energy, and biomedicine. Beyond their stand-alone properties and applications, recent research has increasingly explored the integration of MOFs with other substrates, particularly electrodes, polymeric thin films, and glass surfaces, to create synergistic effects that enhance material performance and broaden application potential. Coating MOFs onto these substrates can yield significant benefits, including, but not limited to, improved sensitivity and selectivity in electrochemical sensors, enhanced mechanical and separation properties in membranes, and multifunctional coatings for optical and environmental applications. This review provides a comprehensive and up-to-date summary of recent advances (primarily from the past 3–5 years) in MOF coating techniques, including layer-by-layer assembly, in situ growth, and electrochemical deposition. This is followed by a discussion of the representative applications arising from MOF-substrate coating and an outline of key challenges and future directions in this rapidly evolving field. This article aims to serve as a focused reference point for researchers interested in both fundamental strategies and applied developments in MOF surface coatings. Full article

Carbon dots (CDs), a class of carbon-based fluorescent nanomaterials, have garnered significant attention due to their tunable optical properties and functional versatility. In this study, we developed a hybrid material by grafting pH- and temperature-responsive copolymers onto CDs via reversible addition-fragmentation chain-transfer (RAFT) polymerization. Triamino-tetraphenylethylene (ATPE) and N-isopropylacrylamide (NIPAM) were copolymerized at varying ratios and covalently linked to CDs, forming a dual-responsive system. Structural characterization using FTIR, ¹H NMR, and TEM confirmed the successful grafting of the copolymers onto CDs. The hybrid material exhibited pH-dependent fluorescence changes in acidic aqueous solutions, with emission shifting from 450 nm (attributed to CDs) to 500 nm (aggregation-induced emission, AIE, from ATPE) above a critical pH threshold. Solid films of the hybrid material demonstrated reversible fluorescence quenching under HCl vapor and recovery/enhancement under NH₃ vapor, showing excellent fatigue resistance over multiple cycles. Temperature responsiveness was attributed to the thermosensitive poly(NIPAM) segments, with fluorescence intensity increasing above 35 °C due to polymer chain collapse and ATPE aggregation. This work provides a strategy for designing multifunctional hybrid materials with potential applications in recyclable optical pH/temperature sensors. Full article