Search Results (1,988)

Terahertz technology has demonstrated immense potential across a wide range of applications, particularly in the realm of THz photodetection. However, state-of-the-art detectors typically face fundamental trade-offs among sensitivity, response speed, operating temperature, and spectral bandwidth. While previous studies have shown that graphene field-effect transistors (GFETs) exhibit a broadband, room-temperature photoresponse to THz radiation—often attributed to photothermoelectric (PTE) and plasma-wave rectification effects—the similar functional dependence of these mechanisms on the gate voltage has historically made it challenging to disentangle their individual contributions. In this study, we leverage monolayer graphene as the photoactive material to overcome these limitations within a single device architecture. We present a novel THz photodetector driven predominantly by the PTE effect, facilitated by a precisely designed counterclockwise spiral antenna. The demonstrated device achieves exceptional room-temperature sensitivity, featuring a minimum noise equivalent power (NEP) of 80.7 $\mathrm{p}\mathrm{W}/\sqrt{\mathrm{H}\mathrm{z}}$ alongside a rapid response time of less than 11 μs. Furthermore, by systematically analyzing the temporal response dynamics, we unambiguously identify the PTE effect as the dominant operating mechanism. These results provide a robust strategy for the development of high-performance, room-temperature THz optoelectronics, paving the way for advanced practical applications in high-capacity wireless communications and real-time THz imaging. Full article

The growing need to reduce aviation’s carbon footprint and reliance on fossil fuels has prompted the exploration of alternative propulsion technologies. Fuel cell (FC) systems offer a sustainable solution, generating only water vapor as a by-product. This paper presents a conceptual study, focusing on subsystem integration and safety aspects, for an 80-passenger, hydrogen-powered aircraft developed within the European Union (EU) co-funded NEWBORN (NExt generation high poWer fuel cells for airBORNe applications) Project. The designed configuration incorporates wing-mounted pods housing fuel cells, an electric motor, an inverter, a Thermal Management System (TMS), and Balance of Performance (BoP). This configuration is an effort towards environmentally friendly solutions, addressing climate change and paving the way towards greener aviation. Full article

In this paper, a novel high-shielding-effectiveness energy-selective surface (HSE–ESS) is proposed. In previous solutions regarding energy-selective surfaces (ESSs) presented in the literature, PIN diodes are usually employed as nonlinear transmission components; however, these diodes may be burnt by powerful high-power microwave (HPM) beams, causing ESSs to lose their shielding effectiveness (SE). To date, no studies have focused on maintaining the SE performance of ESSs after PIN diode failure. To address these limitations, we introduce shape memory alloys (SMAs) into ESS design. The consequences of PIN diode failure are offset by the physical deformation of SMA components caused by high-amplitude-current heating. This characteristic, featuring 30 dB SE, can be defined as high shielding effectiveness (HSE). After completing the design and performing accurate numerical simulations, we fabricated a prototype using PCB technology and characterized it in an anechoic environment, verifying the overall method. In particular, the SMA components proved to be an effective medium for guaranteeing electrical continuity under thermal stress conditions, thus paving the way for their extended adoption in ESSs by substituting or acting as a back-up for PIN diodes. Overall, this approach enhances the reliability and SE of ESSs by adding SMA components. Full article

Nanophotonics, an interdisciplinary field merging nanotechnology and photonics, has enabled transformative advancements across diverse sectors, including green energy, biomedicine, and optical computing. This review comprehensively examines recent progress in nanophotonic principles and applications, highlighting key innovations in material design, device engineering, and system integration. In renewable energy, nanophotonics allows the use of light-trapping nanostructures and spectral control in perovskite solar cells, concentrating solar power systems, and thermophotovoltaics. This has significantly enhanced solar conversion efficiencies, approaching theoretical limits. In biosensing, nanophotonic platforms achieve unprecedented sensitivity in detecting biomolecules, pathogens, and pollutants, enabling real-time diagnostics and environmental monitoring. Medical applications leverage tailored light–matter interactions for precision photothermal therapy, image-guided surgery, and early disease detection. Furthermore, nanophotonics underpins next-generation optical neural networks and neuromorphic computing, offering ultrafast, energy-efficient alternatives to von Neumann architectures. Despite rapid growth, challenges in scalability, fabrication costs, and material stability persist. Future advancements will rely on novel materials, AI-driven design optimization, and multidisciplinary approaches to enable scalable, low-cost deployment. This review summarizes recent progress and highlights future trends, including novel material systems, multidisciplinary approaches, and enhanced computational capabilities, paving the way for transformative applications in this rapidly evolving field. Full article

This study investigates the frequency-dependent electrical conductivity of electrically conductive threads (also known as e-threads), particularly focusing on their inherently lower conductivity than traditional conductors like copper. While efforts have been made to electrically characterize conductive threads in the past, most studies have focused on DC or frequencies lower than 1 GHz. Recent works have evaluated attenuation up to 6 GHz, but they do not report bulk conductivity and lack validation in the context of antenna applications. In a major step forward, this study reports a systematic way of characterizing the surface conductivity of conductive yarns, for eight different thread types, from 10 MHz to 6 GHz. Different parameters such as insertion loss, attenuation, and conductivity are reported, determining the suitability of conductive yarns at specific frequencies. The study also reports the first frequency-dependent bulk conductivity of individual conductive threads. By measuring both surface and bulk conductivity, our work provides foundational data crucial for designing textile-based antennas and sensors. The practical relevance of the proposed approach is demonstrated through simulations and measurements of a broadband log-spiral antenna and a single-turn loop antenna. Overall, this research contributes valuable insights into the integration of e-textiles in smart fabric applications, paving the way for further innovations in this evolving field. Full article

Graphene and its derivatives are widely recognized as effective reinforcements due to their unique mechanical, thermal and lubrication performance. Incorporation of these reinforcements into polyamide-imide (PAI) coating matrix has shown significant potential for improving the tribological performance. Here, the mechanisms underlying the tribological improvement enabled by graphene oxide (GO) are investigated via frictional experiments and molecular dynamics simulations. It was found that the coefficient of friction (COF) of PAI coating is reduced upon the addition of GO over the range of 100–400 MPa and 20–100 mm/s, with a maximum reduction of ~25% achieved at 200 MPa and 60 mm/s. Simulations reveal that the friction reduction arises from strong adhesion interactions between the embedded GO sheets and PAI molecular chains, which inhibit the shear-induced mobility of the chains during the friction process. This mechanism enables a further reduction in the COF of the GO/PAI composite coating by increasing the interfacial adhesion through the tailored modulations of surface morphology and chemistry of the GO sheets. These findings pave the way for advancing the rational design and application of graphene-based composite coatings with highly improved tribological performance. Full article

Liquid hydrogen (LH₂) fuel system architectures for aviation remain at low Technology Readiness Levels (TRLs) due to limited experimental data and the challenges of modelling cryogenic hydrogen’s behavior. This paper presents a computationally efficient framework for sensitivity analysis that integrates cryogenic thermodynamics, tank geometry, external heat ingress, engine mass flow demands, and pressurization control strategies. A set of operational scenarios was modeled to demonstrate how tank pressure and temperature evolve under various control and geometric conditions, delivering five key insights: (1) Passive tank self-pressurization leads to continuous pressure rise and subcooled liquid. (2) LH₂ withdrawal alone may not fully stop pressurization with high heat ingress. (3) Gaseous hydrogen (GH₂) injection stabilizes pressure only up to moderate heat ingress during LH₂ extraction. (4) The addition of venting enables full pressure control. (5) Tank geometry and heat flux govern transient behavior. Spherical tanks show slower pressure and temperature rise than cylindrical ones, and both geometries maintain near-constant pressure at low heat flux. These insights offer practical guidance for designing reliable and thermally stable LH₂ storage systems for future aircraft applications, paving the way towards sustainable and zero-emission aviation. Full article

The development of high-performance electrochemical sensors requires precise integration of electrode active materials that provide both superior electrocatalytic activity and long-term structural stability. Herein, we report a systematically optimized, one-pot electrochemical deposition approach for the fabrication of nanographenide-based nanoarchitectures, incorporating either a conducting polymer (PEDOT-NG) or Prussian blue (PB-NG). Derived from optimization-driven structural refinement—including applied potential, electrodeposition time, and precursor concentration—the robust nanoarchitecture exhibits a hierarchical morphology that provides an expanded electroactive surface area, accelerating charge transfer and enhancing electrochemical catalytic activity. The optimized PEDOT-NG exhibits exceptional sensitivity for the simultaneous determination of ascorbic acid (AA), dopamine (DA), and uric acid (UA), achieving wide linear ranges with low detection limits of 4.1, 0.12, and 0.18 μM, respectively. The PB-NG achieves a limit of detection of 4.39 μM, driven by highly reversible and stable redox kinetics. This performance is underpinned by narrowed peak-to-peak separations (ΔE) and reduced redox potentials. These results underscore the pivotal role of precise parametric control in developing high-performance electrochemical sensors. Furthermore, this work establishes a comprehensive strategy for designing resilient electrode active materials, thereby paving the way for next-generation electrochemical platforms tailored for diverse and robust sensing environments. Full article

While the broader context of molecular machinery has already been extensively discussed in the scientific literature, there is a lack of dedicated reviews focusing specifically and exclusively on information ratchets. These ratchets deserve a dedicated analysis as they are common in nature and their implementation in artificial systems can lead to new ways of achieving biomimetic processes and endergonic synthesis. This review summarizes recent advancements in the design of synthetic information ratchets, highlighting breakthroughs in the rationalization and optimization of fueling and structural parameters for the sake of efficiency. Novel methods are described for in situ quantification and the translation of molecular motion into macroscopic work. The latest artificial information ratchets are compared to the previous literature and the natural motors that inspired them. The reported findings are meant to show how research on information ratcheting has progressed in the last five years, with various designs paving the way to bio-inspired nanotechnologies and materials. Full article

The rational design of electrode materials with tailored composition and architecture is crucial for advancing high-capability electrochemical energy storage systems. This study reports that gadolinium-modified NiFe₂O₄ nanosheet electrodes were effectively synthesized on nickel foam via a hydrothermal approach followed by thermal treatment. A series of compositions (NiFe, NiFe–Gd1, NiFe–Gd2, and NiFe–Gd3) were prepared to systematically examine the effect of Gd incorporation on structural features and electrochemical properties. X-ray diffraction (XRD) analysis confirmed the formation of the cubic spinel NiFe₂O₄ phase without detectable secondary phases, indicating that the crystal structure remains intact after Gd introduction. X-ray photoelectron spectroscopy (XPS) further verified the presence of Ni²⁺, Fe³⁺, and Gd³⁺ species within the lattice environment. Morphological analysis using field-emission scanning electron microscopy (FESEM) revealed a nanosheet-based architecture, where the optimized NiFe–Gd2 electrode exhibited a porous and interconnected nanosheet framework with abundant exposed edges. This structural configuration improves electrolyte penetration and facilitates efficient ion transport during charge storage processes. Electrochemical measurements demonstrated that the NiFe–Gd2 electrode delivers an areal capacitance of 5235 mF cm⁻² at 10 mA cm⁻², along with improved reaction kinetics and low internal resistance. An asymmetric supercapacitor assembled using NiFe–Gd2 as the positive electrode and activated carbon as the negative electrode operated stably within a 0–1.5 V potential window, achieving an energy density of 0.136 mWh cm⁻² and a power density of 3.14 mW cm⁻², while retaining 86.55% of its initial capacitance after 7000 cycles. These results highlight the potential of rare-earth engineering as a viable strategy for designing advanced spinel ferrite electrodes and pave the way for the development of high-performance, durable, and scalable supercapacitor systems for practical energy storage applications. Full article

Addressing the prevalent issue of “physical preservation but spiritual silence” in the revitalisation of China’s national industrial heritage, this study proposes and empirically validates a “dual-track narrative” design framework that systematically translates cultural values into spatial experiences. The framework integrates a “figure–history” narrative, which crystallises historical lineage and symbolic spirit through spatial sequences, commemorative landmarks, and authentic remains, with a “scene–activity” narrative, which transforms former production spaces into dynamic, culturally vibrant stages through ecological restoration displays, industrial landscape transformation, and flexible activity implantation. Using Nantong Guangsheng Oil Mill as a single-case study, the research employs qualitative methods including archival analysis, field observation, and semi-structured interviews to examine how the dual-track framework operates in practice. The findings reveal that the “figure–history” narrative manifests in a walkable “time corridor” along the north–south axis, where architectural remnants from different eras are organised to materialise Zhang Jian’s industrial salvation ethos and the collective memory of generations of workers. Meanwhile, the “scene–activity” narrative activates underutilised spaces—such as the repurposing of acid treatment ponds into constructed wetlands and paved grounds into public stages—enabling ongoing cultural production, community interaction, and ecological healing. The study demonstrates that the dual-track framework bridges the historical and contemporary dimensions often treated separately in heritage practice, establishing a systematic “translation mechanism” from cultural decoding to design intervention. Theoretically, it contributes to industrial heritage research by integrating narratology, memory studies, heritage interpretation, and situationism into a coherent design methodology. Practically, it offers decision-makers evaluation criteria beyond the preservation-versus-development binary, provides designers with a mode of creative transformation grounded in material authenticity, and suggests to operators a content-driven, event-based model for sustaining heritage spaces. By spatialising and eventising narratives, the dual-track approach enables industrial heritage to function as a catalyst for cultural identity, social vitality, and economic sustainability, offering a transferable paradigm for the adaptive reuse of industrial heritage in contemporary urban contexts. Full article

Accurate characterization of pavement responses under real traffic loading is essential for improving pavement design reliability. This study presents SmartPave, a full-scale embedded monitoring system for measuring multilayer pavement responses under heavy vehicle loading. The system integrates embedded multi-sensors to capture stress, strain, temperature, and moisture within pavement layers. Field experiments were conducted under static and moving loading conditions. The results show that peak vertical stresses in the granular base were approximately 1.7–2.0 times higher than those at the subgrade, indicating stress attenuation with depth, while tensile strains at the bottom of the asphalt layer ranged between 200 and 350 µε. Lower vehicle speeds increased load duration and amplified viscoelastic strain responses. These findings demonstrate the capability of the system to provide reliable field data for mechanistic analysis and model calibration. Full article

Dragon fruit (Hylocereus spp.) is an emerging crop in the tropics and subtropics, but its production is increasingly threatened by diseases that reduce yield and profitability. Early diagnosis of these diseases is crucial for timely intervention, yet visual symptoms often appear only after significant infection has occurred. The study aims to evaluate how optical spectral reflectance can detect dragon fruit diseases and identify the most responsive spectral regions. In this study, six major dragon fruit stem diseases: Neoscytalidium stem canker, stem sunburn, anthracnose, Botryosphaeria stem canker, Bipolaris stem rot, and bacterial soft rot were characterized by the goal of identifying unique spectral signatures for early detection and differentiation of each disease. Seventy-two potted dragon fruit plants of three distinct species were grown under four organic vermicompost treatments (0, 5, 10, 20 tons/acre) in both open-field and high-tunnel conditions together, in a randomized complete block design. A handheld spectroradiometer (350–2500 nm) was used to collect reflectance from the diseased and healthy cladodes (stem segment). Various spectral vegetative indices were computed to identify disease-specific features. The results revealed distinct spectral features for each disease. Infected cladodes consistently exhibited higher reflectance especially in the visible region (400–700 nm) and the near-infrared region (900–2500 nm) of the spectrum than healthy cladodes. The Normalized Difference Vegetative Index (NDVI), Green Normalized Difference Vegetative Index (GNDVI), and Spectral Ratio (SR) spectral indices were significantly higher in healthy plants than in diseased ones, reflecting higher chlorophyll concentration and plant biomass. Conversely, the 1110/810 ratio was lower in healthy plants than in diseased plants, suggesting a more compact internal plant structure. Statistical analysis revealed highly significant differences (p < 0.00001) between healthy and diseased spectra in the Red, Green and NIR regions. Linear Discriminant Analysis(LDA) achieved the highest classification accuracy (OA = 0.642, κ = 0.488), though performance was limited for minority classes. These findings demonstrate that targeted spectral sensing can identify dragon fruit diseases before obvious symptoms emerge. By pinpointing disease-specific spectral indices, our study paves the way for early-warning tools such as targeted multispectral sensors or drone-based imaging that would enable growers to intervene sooner and limit losses. These results highlight the potential for development of UAV-based or portable spectral sensors for large-scale, near real-time disease monitoring in dragon fruit production. Full article

Vegetation eco-concrete (VEC) is a novel material for slope stabilization, effectively integrating ecological restoration with engineering protection. Its primary supporting skeleton consists of aggregates with specific particle sizes, bonded by cementitious materials, and is characterized by numerous interconnected pores, along with certain mechanical properties. However, VEC still faces challenges in practical application, such as inaccuracies in the optimal mix design and poor vegetative compatibility between the structural material and plants. To determine the optimal mix for porous VEC, this study utilizes Portland cement to design the VEC mix proportions based on orthogonal tests. The study further conducts VEC paving and plant experiments based on the optimal mix obtained. The results indicate the following: (1) The optimal mix consists of a water–cement ratio of 0.27, a cement particle diameter of 10 mm, a cement particle content of 70–75 wt%, a mortar binder content of 0.1 wt%, and a polypropylene fiber content of 0.16 wt%. (2) VEC with nutrient-enriched particles exhibited excellent vegetative compatibility, providing root penetration channels and creating a conducive environment. (3) Plant species with strong adaptability and well-developed root systems that integrate with VEC can enhance both the engineering protection and ecological benefits of VEC. Full article

The application of 3D data in pavement inspection represents an emerging trend. Acquiring and measuring the 3D information of pavement distress enables a more comprehensive assessment of severity, thereby allowing for accurate monitoring and evaluation of the pavement’s technical condition. Existing methods face challenges in high-cost pavement scanning and insufficient research on automated 3D distress segmentation. This study employed a consumer-grade action camera for data acquisition and constructed an engineering-aligned 3D point cloud dataset of pavements. Then a long-tail class imbalance mitigation strategy was introduced, integrating adaptive re-sampling with a weighted fusion loss function, effectively balancing minority class representation. The proposed network, named PointPaveSeg, was a dedicated point cloud processing architecture. A dual-stream feature fusion module was designed for the encoder layer, which decoupled geometric and semantic features to improve distress extraction capability. The network incorporated a hierarchical feature propagation structure enhanced by edge reinforcement, global interaction, and residual connections. Experimental results demonstrated that PointPaveSeg achieved an mIoU of 78.45% and an accuracy of 95.43%. In the field evaluation, post-processing and geometric information extraction were performed on the segmented point clouds. The results showed high consistency with manual measurements. Testing confirmed the method’s practical applicability in real-world projects, offering a new lightweight alternative for intelligent pavement monitoring and maintenance systems. Full article