Search Results (130)

Xanthohumol (XN), a prenylated chalcone isolated from Humulus lupulus L., exhibits a wide range of biological activities, including antioxidant, anti-inflammatory, and chemopreventive effects. However, its therapeutic application is limited by poor aqueous solubility, low chemical stability, and rapid clearance from the systemic circulation. The present study aimed to develop and characterize a novel nano-sized drug-delivery system for XN that combines favourable colloidal stability, efficient encapsulation, sustained release, and reduced recognition by macrophages (“stealth-like” properties). To achieve this, XN-loaded cationic liposomes were coated with two marine polysaccharides, iota-carrageenan (CAR) and fucoidan (FUC), followed by Ca²⁺-mediated cross-linking. Liposomes were prepared by the ethanol injection method, and formulation parameters were optimized using a 2³ + 1 full factorial design. Surface modification and cross-linking conditions were further optimized through polyelectrolyte titration and a Taguchi L9 orthogonal array. The resulting nanocarriers were evaluated for particle size, polydispersity, ζ-potential, encapsulation efficiency, release behavior, and cellular uptake. Both coatings significantly prolonged XN release compared with uncoated liposomes, with CAR-coated vesicles providing the most sustained release (≈55% over 48 h). In RAW264.7 macrophages, 50 µg/mL CAR-coated liposomes reduced cellular uptake by approximately 74% following 1-h incubation relative to uncoated controls and maintained this reduction over 2 h whereas FUC-coated vesicles afforded only transient early evasion. The cross-linked iota-carrageenan coating thus represents a promising strategy for conferring stable “stealth-like” characteristics to XN-loaded liposomes intended for prolonged drug delivery. Full article

Electromagnetic wave absorbing materials are important for electromagnetic protection, radar stealth, wireless communication, and advanced electronic systems. However, traditional design methods mainly rely on repeated experiments and full-wave simulations, which are time-consuming and inefficient when dealing with complex compositions, microstructures, and multilayer structures. Machine learning provides a new route to accelerate the design of high-performance absorbers by learning the relationship among material composition, structure, electromagnetic parameters, and absorption performance. This review summarizes recent progress in machine-learning-empowered electromagnetic wave absorbing materials. First, the basic physical principles of electromagnetic wave absorption are introduced, including reflection loss, impedance matching, attenuation, and physical limits such as the Rozanov and Snoek limits. Then, typical machine learning models are discussed, including classical machine learning, deep learning, generative models, physics-informed models, large language models, and artificial-intelligence (AI) Agents. Their applications are further summarized from forward property prediction, high-throughput screening, inverse design, electromagnetic parameter decoupling, physics-informed modeling, explainability, multi-objective optimization, and data augmentation. Finally, the main challenges and future directions are discussed, including data standardization, physics-guided learning, foundation models, autonomous laboratories, and engineering-scale validation. This review shows that machine learning is changing absorber research from experience-driven trial-and-error to data-driven and knowledge-driven design, and provides a useful reference for developing next-generation electromagnetic wave absorbing materials. Full article

MXenes, a rapidly expanding family of two-dimensional transition-metal carbides and nitrides, are increasingly viewed as strong candidates for defense-oriented multifunctional systems because they combine metallic conductivity, surface tunability, mechanical flexibility, and solution processability within a lightweight platform. Unlike conventional metals, ceramics, and semiconductors, which usually optimize one or two parameters at the expense of density, brittleness, or integration compatibility, MXenes offer a rare opportunity to coordinate electromagnetic, mechanical, thermal, and sensing functions within one material family. Different from existing reviews that focus on laboratory-level record performance or single-function optimization, this review presents an innovative deployment-oriented perspective and fills the research gap of systematic military-oriented evaluation for MXenes. In this review, we examine MXenes from a deployment-oriented perspective rather than through isolated record values. We first summarize their formation chemistry and major synthesis routes, including HF and in-situ HF etching, bifluoride and alkaline methods, molten-salt strategies, electrochemical approaches, and precursor-free chemical vapor deposition. We then discuss the principal levers of property regulation, focusing on composition design, surface-termination control, and heterostructure engineering, and show how these strategies shape the performance envelopes relevant to shielding, stealth, impact response, energy storage, and sensing. This review constructs a full-chain analytical framework from synthesis, property regulation to military application and deployment challenges for the first time. Finally, we identify the main barriers to translation, especially manufacturing inconsistency, termination heterogeneity, oxidation and interfacial degradation, and limited application-level validation, and outline the most realistic paths toward deployable defense technologies. Full article

To optimize the electromagnetic and mechanical properties, a resin-based coating with a bionic helical structure made by carbonyl iron fibers (CIF) was prepared by alternating spray and brushing with 0°/45°/90°. The morphologies of CIP and CIF were characterized by a scanning electron microscope (SEM). The electromagnetic parameters of CIP were measured in the frequency range of 2–18 GHz by the coaxial ring method, and microwave absorption properties of the coating were evaluated by reflection loss (RL). The mechanical properties of the coating with the bionic helical structure were investigated by the pull-off method. The effects of the CIP ratio, CIF content, and thickness on the microwave absorption were discussed, respectively. The results show that 6.5:3.5 is the optimal CIP-to-paraffin ratio with superior electromagnetic performance and RL. The coating with the triple helical structure, fiber content of 3 wt% and free of CIP (C4) exhibits optimal electromagnetic wave absorption performance with a minimum RL value of −10.66 dB and wide effective absorbing bandwidth (EAB) of 10.58 GHz at a thickness of 0.6 mm. Moreover, the adhesion strength of C4 reaches 13.52 MPa. The excellent absorption performance and mechanical properties of the resin-based coating with the bionic helical structure indicate that it has potential application value in the field of stealth materials. Full article

As one of the core technologies in modern national defense and security fields, infrared stealth technology aims to realize the controllable regulation of the radiation characteristics of targets in the infrared band. This paper focuses on a novel electrochromic device with a structure of WO₃/nickel mesh/Al³⁺-Zn²⁺gel electrolyte/zinc foil. The structural composition and working mechanism are systematically analyzed, and the infrared stealth regulation performance is emphatically studied. The WO₃ thin film and device structure were characterized by scanning electron microscopy (SEM). The infrared emissivity modulation and optical response properties of the device were measured using an infrared thermal imager and a UV-Vis-NIR spectrophotometer. The prepared WO₃ film exhibits a dense spherical morphology, indicating excellent uniformity and compactness. After 1000 cycles, the areal capacitance of the device remains 83.7% of its initial value, demonstrating good cycling stability. Under the voltage regulation of −0.1 V to 1.1 V, the emissivity ε of the device at the typical mid-wave infrared wavelength of 4.0 μm decreases from 0.89 (−0.1 V) to 0.67 (1.1 V), with an absolute modulation amplitude Δε of 0.22. At the typical long-wave infrared wavelength of 8.7 μm, ε decreases from 0.96 (−0.1 V) to 0.69 (1.1 V), with an absolute modulation amplitude Δε of 0.29. The electrochromic switching times for coloring and bleaching are 10.1 s and 2.44 s, respectively. According to infrared thermal imaging tests, in the temperature range of 30–40 °C, the surface temperature difference ΔT between the colored state and bleached state increases from 4.3 °C to 4.6 °C. The maximum regulation amplitude reaches 4.6 °C at 40 °C. The device achieves efficient regulation of infrared emissivity through the electrochromic effect, providing a new device design strategy for infrared stealth technology. Full article

This study presents experimental evidence of random magnetic behavior in modified barium hexaferrites. We demonstrate a significant shift in the magnetic properties of these materials upon the incorporation of divalent cations (Ni²⁺, Cu²⁺, Mn²⁺), which produces the formation of ceramic nanocomposites. X-ray diffraction, scanning electron microscopy, and laser diffraction reveal that these systems comprise micron-sized clusters formed by sintering polycrystalline nanoparticles. The cation incorporation occurs randomly across each sample, creating conditions conducive to random anisotropy magnetism. We confirm this behavior in our samples by fitting the magnetization data near saturation to a corresponding theoretical model. Additionally, we investigate the microwave absorption capabilities of these systems in the GHz range by calculating the reflection loss coefficient of mm-thick samples using transmission-line theory. The results predict broad (up to 2 GHz) and high (around 60 dB on average) absorption signals. In the case of the thinnest samples (1–2 mm), the Cu-substituted system presents broader absorption bandwidths than the pure hexaferrite and, therefore, proves to be more efficient for stealth applications in lightweight sectors. These findings suggest ceramic nanocomposites are promising candidates for random anisotropy magnets, highlighting their potential as efficient microwave absorbers, consistent with recent theoretical predictions. Full article

Silicon carbide (SiC), owing to its excellent physical and chemical properties, has emerged as a leading third-generation semiconductor material. Conventional diamond wire cutting faces challenges in producing ultra-large, ultra-thin wafers. In contrast, the femtosecond laser has attracted significant attention in recent years due to its low kerf loss and high slicing speed. However, during femtosecond laser stealth slicing, spherical aberration induced by the refractive index mismatch between air and the SiC crystal severely degrades the slicing quality. Based on the analysis and calculation of wavefront aberration at a specific focal depth of 175 μm, we designed and implemented a static aberration correction method to reduce the thickness of the modified layer and improve the slicing quality. This method effectively mitigates focus elongation caused by refractive index mismatch, thereby reducing the modified layer thickness and the tensile stress required for wafer separation, while improving the surface quality of the separated wafers. Furthermore, this method eliminates the need for active optical components in aberration correction, simplifying the system and avoiding errors associated with the limited response speed of active optics. The technique demonstrates potential for practical application in industrial wafer slicing. Full article

We propose Distribution-Preserving Latent Steganography via Conditional Optimal Transport (DPL-COT), a coverless image steganography framework for latent diffusion models. Unlike classical cover-modifying schemes, DPL-COT embeds a bitstream directly into the initialization noise latent ${\mathbf{z}}_T\sim \mathcal{N}(\mathbf{0},\mathbf{I})$ without model retraining. Our primary objective is high recoverability and a low bit error rate (BER) under deterministic inversion, which is inherently imperfect due to numerical discretization and VAE nonlinearity. To maximize decoding stability, we restrict embedding to the natural tails of the latent prior by selecting the largest-magnitude coordinates, thereby increasing the sign decision margin against inversion drift. To preserve distributional stealth, per-bit target values are analytically derived from truncated Gaussians matching the marginal distribution of the selected coordinates. Conditional 1D optimal transport is applied independently for each bit class, mapping every coordinate to its target value while preserving rank order. We generate 5000 stego images using a pretrained diffusion model and demonstrate a favorable capacity–reliability trade-off (e.g., 4916 bits/image with 0.473% mean BER) and strong robustness to JPEG compression (sub-1% mean BER at $Q=60$). Compared with LDStega, a recent LDM-based scheme reporting 99.28% clean-channel accuracy, DPL-COT achieves 99.53% at a comparable operating point and sustains above-99% accuracy under all tested JPEG quality factors. Latent-space tests further confirm negligible cover–stego distribution shift (mean ${\mathrm{KS}}_2<0.003$, mean $W_1<0.003$), a property not formally addressed by prior methods. Full article

Liposomes remain one of the most utilized drug delivery systems due to their numerous advantages. However, they face significant challenges primarily due to their low colloidal stability as well as their rapid clearance by the reticuloendothelial and mononuclear phagocyte systems. Surface modifications have been identified as a highly effective approach to address these challenges. Various molecules can be utilized as surface modifiers. However, polysaccharides are widely employed in this regard, due to their unique characteristics, such as biocompatibility, biodegradability, and non-toxicity, as well as their ability to interact with the liposomal surface through different mechanisms. The aim of the present review is to provide a thorough analysis of polysaccharide-modified liposomes, highlighting recent advancements in their design, synthesis, and therapeutic applications. The utilization of polysaccharides as surface modifiers has been demonstrated to have several notable effects on liposomes. These effects include the enhancement of liposome properties, the provision of “stealth” properties, and the augmentation of colloidal stability. This review provides a comprehensive, polysaccharide-oriented analysis of liposomal surface modification strategies, along with a novel focus on the correlation between polysaccharide structure, modification method, and the resulting physicochemical and biological performance of the designed hybrid liposomes across a wide range of applications. Full article

As key components in efforts to achieve green and sustainable development in machinery, water-lubricated stern bearings are increasingly replacing traditional oil-lubricated bearings. However, water’s inherent properties—such as low viscosity and poor film-forming ability—can induce severe friction-induced vibration and noise under specific operational conditions. These issues not only accelerate wear but also compromise the vessel’s reliability and acoustic stealth, thereby limiting their wider application. This paper provides a comprehensive review of the research progress relating to friction-induced vibration in water-lubricated bearings. It delves into the underlying mechanisms, critiques the primary methodologies used in numerical simulations, summarizes key experimental approaches, and synthesizes the prevailing vibration suppression strategies. Finally, the study clearly outlines existing challenges and proposes directions for future research. Full article

Terahertz (THz) technology is finding increasingly widespread applications in biosensing, high-speed communication, and stealth materials. Meanwhile, graphene, as a quintessential two-dimensional material, has emerged as a core component of THz devices due to its unique optoelectronic properties. However, the precise and non-destructive characterization of the complex conductivity of graphene at the microscopic scale remains a formidable challenge. Conventional measurement methods often suffer from limitations associated with contact resistance or intricate sample preparation processes. In this paper, we propose a non-invasive parameter inversion method based on deep learning. We design a tri-layer graphene-silica-copper metasurface structure featuring a central cavity and establish a high-fidelity scattering model that incorporates physical effects such as edge diffraction and multi-mode resonance. Utilizing the Radar Cross Section (RCS) data generated by this model, we train a Deep Enhanced Conductivity Predictor (DECP) network integrated with a Convolutional Block Attention Module (CBAM). Experimental results demonstrate that the proposed network can accurately reconstruct the complex conductivity of graphene from far-field RCS data. The coefficients of determination (R²) for the prediction of both real and imaginary parts exceed 0.99, with a Root Mean Square Error (RMSE) as low as the order of 10⁻⁵. This study not only validates the effectiveness of data-driven approaches in material characterization but also provides a novel paradigm for the real-time monitoring and intelligent design of terahertz metasurfaces. Full article

A hybrid graphene-VO₂ reconfigurable terahertz metamaterial absorber is proposed for broadband radar cross-section (RCS) reduction and high-performance sensing. The designed structure leverages the phase transition property of VO₂ and the electrostatic tunability of graphene to achieve dynamic switching between ultra-broadband and narrowband absorption states. When VO₂ is in the metallic state and graphene is unbiased, the absorber exhibits over 90% absorption across 0.82~3.50 THz, corresponding to a relative bandwidth of 124%. In the narrowband mode, with VO₂ in the insulating state and graphene biased (E_f = 1 eV), a sharp absorption peak exceeding 60% is achieved at 1.48 THz. The symmetrical design ensures polarization insensitivity and wide-angle stability. Applications in broadband RCS reduction higher than 10 dB and refractive index sensing with a sensitivity of 24.86 GHz/RIU are demonstrated, surpassing conventional terahertz sensors. This work provides a promising platform for adaptive terahertz stealth and sensing systems. Full article

Background/Objectives: Advanced drug delivery systems (DDSs) are essential for targeted delivery, controlled release, and reduced systemic toxicity, but their clinical adoption is limited by biological barriers, manufacturing complexities, and cost. The aim of this systematic review is to critically evaluate the quantitative relationships between platform design, overcoming biological barriers, and clinical translation outcomes for DDS developed between 2016 and 2025. Methods: A comprehensive literature search was conducted in PubMed/MEDLINE, Scopus, and Web of Science (January 2016–April 2025) in accordance with the PRISMA 2020 guidelines. Included studies focused on experimental or clinical data for nanocarrier platforms (liposomes, lipid nanoparticles, polymer systems, biomimetic carriers, extracellular vesicles). Data on platform characteristics, interactions with barriers, pharmacokinetics, manufacturing, and clinical outcomes were extracted and synthesized in narrative form due to the significant methodological heterogeneity. Results: An analysis of 77 included studies confirms that successful clinical translation depends on matching the physicochemical properties of the carrier (size, surface chemistry, material) to specific biological barriers. Liposomes and lipid nanoparticles (LNPs) remain the most clinically validated platforms, exploiting the EPR effect and liver tropism, respectively. Key engineering solutions include stealth coatings, ligand-mediated targeting, and stimulus-responsive materials to overcome barriers such as mononuclear phagocyte system clearance, the blood–brain barrier, and mucosal barriers. Microfluidic and continuous manufacturing processes enable reproducibility, but scalability, cost, and immunogenicity (e.g., anti-PEG responses) remain key translational challenges. Engineered extracellular vesicles, biomimetic carriers, and 3D/4D-printed systems combined with AI-driven design demonstrate the potential for personalized, adaptive delivery. Conclusions: Cutting-edge DDSs have validated their clinical value, but realizing their full potential requires a holistic, patient-centered design approach integrating barrier-specific engineering, scalable manufacturing, and rigorous safety assessment from the earliest stages of development. Further progress will depend on standardizing methods for new platforms (e.g., extracellular vesicles), implementing digital and AI tools, and ensuring translational feasibility as a fundamental principle. Full article

Polyethylene glycol (PEG) has been extensively utilized in drug formulations due to its multifunctional properties, i.e., hydrophilicity and biocompatibility. The roles played by PEG (as a drug delivery carrier and a solubilizer) improve the dissolution profile of several active pharmaceutical ingredients (APIs), leading to an improved absorption, distribution, metabolism, excretion, and toxicity (ADMET) profile. Moreover, PEG aids in upgrading the existing mechanical properties (as a binding agent, a plasticizer, etc.). Furthermore, PEG, due to its unique ability to provide “stealth” properties, is a valuable tool in pharmaceutical nanotechnology. Exploiting physicochemical variables, PEG acts as a coating/conjugation component of nanocarriers for ameliorating permeability and enhancing in vivo circulation without clearance by the body’s immune system. Additionally, PEG’s presence at the target site decreases external interactions and enhances the pharmacological attributes in terms of loading efficiency and controlled release. Nevertheless, cases of hypersensitivity or allergy, as well as anaphylactic shocks and allergic reactions, have been detected. The topic of this article is the exploitation of PEG’s physicochemical properties in the study of drug delivery, focusing on solid dosage forms and nanovesicles, along with the evaluation of its contribution to the fabrication of safe delivery and theragnostic systems. Full article

To reduce the lightness and enhance the thermal resistance of Al-pigmented low-emissivity coatings, CuCr₂O₄ pigment was introduced into the coating system via ball milling. The results revealed that both ball milling time and Al: CuCr₂O₄ mass ratio significantly affect the optical and infrared properties of the coatings. When the milling time reached 9 h, the pigment attained an optimal flake morphology, leading to the best infrared performance of the composite coating. Additionally, the CuCr₂O₄ content effectively suppressed the lightness of Al-pigmented coatings. Compared to Al-pigmented low-emissivity coatings, the composite coating with an Al:CuCr₂O₄ ratio of 10:2 exhibited a reduction in L* value from 90 to 65. Meanwhile, it retained a low average infrared emissivity of 0.42 in the 3–5 μm and 8–14 μm ranges. Moreover, the incorporation of CuCr₂O₄ significantly improved the Al-pigmented coating’s thermal resistance from 500 °C to 600 °C. The composite coating maintained a Grade 1 adhesion rating with heat treatment of 600 °C due to a self-healing effect_. These composite coatings with low emissivity, low lightness, and high-temperature resistance are highly suitable for high-temperature and infrared stealth applications. Full article