Search Results (599)

Porous materials are characterized by the pore surface area (S) and volume (V) accessible to a confined fluid. For mesoporous materials NMR measurements of diffusion are used to assess the S/V ratio, because at short times, only the diffusivity of molecules in the adsorbed layer is affected by confinement and the fractional population of these molecules is proportional to the S/V ratio. For materials with sub-nanometer pores, this might not be true, as the adsorbed layer can encompass the entire pore volume. Here, using molecular simulations, we explore the role played by S and S/V in determining the dynamical behavior of two carbon-bearing fluids—CO₂ and ethane—confined in sub-nanometer pores of silica. S and V in a silicalite model representing a sub-nanometer porous material are varied by selectively blocking a part of the pore network by immobile methane molecules. Three classes of adsorbents were thus obtained with either all of the straight (labeled ‘S-major’) or zigzag channels (‘Z-major’) remaining open or a mix of a fraction of both types of channel blocked, resulting in half of the total pore volume being blocked (‘Half’). While the adsorption layers from opposite surfaces overlap, encompassing the entire pore volume for all pores except the intersections, the diffusion coefficient is still found to be reduced at high S/V, especially for CO₂, albeit not so strongly as would be expected in the case of wider pores. This is because of the presence of channel intersections that provide a wider pore space with non-overlapping adsorption layers. Full article

In this study, a facile and mask-free femtosecond laser direct writing (FLDW) approach is proposed to fabricate porous graphene (FLIG) patterns directly on polyimide (PI) substrates. By systematically adjusting the laser scanning spacing (10–25 μm), denser and more continuous microstructures are obtained, resulting in significantly enhanced thermal sensitivity. The optimized sensor demonstrated a temperature coefficient of 0.698% °C⁻¹ within the range of 40–120 °C, with response and recovery times of 10.3 s and 20.9 s, respectively. Furthermore, it exhibits remarkable signal stability across multiple thermal cycles, a testament to its reliability in extreme conditions. Moreover, the sensor was successfully integrated into a 3D-printed robotic platform, achieving both contact and non-contact temperature detection. These results underscore the sensor’s practical adaptability for real-time thermal sensing. This work presents a viable and scalable methodology for fabricating high-performance FLIG-based flexible temperature sensors, with extensive application prospects in wearable electronics, electronic skin, and intelligent human–machine interfaces. Full article

Among the various available synthesis approaches, hydrolytic precipitation offers a simple, cost-effective, and scalable route for producing phase-pure NiO with a controlled morphology and crystallite size. However, the influence of calcination temperature on its crystalline phase, particle size, and antimicrobial activity remains an active field of research. This study aims to investigate the structural, morphological, and antibacterial properties of NiO nanoparticles synthesized via hydrolytic methods and thermally treated at different temperatures. XRD data indicate the presence of the hexagonal crystallographic phase of NiO (space group 166: R-3m), a structural variant less commonly reported in the literature, stabilized under mild hydrolytic synthesis conditions. The average crystallite size increases significantly from 4.97 nm at 300 °C to values of ~17.8 nm at 500–700 °C, confirming the development of the crystal lattice. The ATR-FTIR analysis confirms the presence of the characteristic Ni–O band for all samples, positioned between 367 and 383 cm⁻¹, with a reference value of 355 cm⁻¹ for commercial NiO. The displacements and variations in intensity reflect a thermal evolution of the crystalline structure, but also an important influence of the size of the crystallites and the agglomeration state. The results reveal a systematic evolution in particle morphology from porous, flake-like nanostructures at 300 °C to dense, well-faceted polyhedral crystals at 900 °C. With an increasing temperature, particle size increases. EDS spectra confirm the high purity of the NiO phase across all samples. Additionally, the NiO nanoparticles exhibit calcination-temperature-dependent antibacterial activity, with the complete inhibition of Escherichia coli and Enterococcus faecalis observed after 24 h for the sample calcined at 300 °C and over 90% CFU reduction within 4 h. A significant reduction in E. faecalis viability across all samples indicates time- and strain-specific bactericidal effects. Due to its remarkable multifunctionality, NiO has emerged as a strategic nanomaterial in fields ranging from energy storage and catalysis to antimicrobial technologies, where precise control over its structural phase and particle size is essential for optimizing performance. Full article

The remarkable advantages of zinc anodes render aqueous zinc-ion batteries (ZIBs) a highly promising energy storage solution. Nevertheless, the uncontrolled growth of zinc dendrites and side reactions pose significant obstacles to the practical application of ZIBs. To address these issues, a straightforward strategy has been proposed, involving the addition of a minute quantity of AgNO₃ to the electrolyte to stabilize zinc anodes. This additive spontaneously forms a hierarchically porous Ag interphase on the zinc anodes, which is characterized by its zinc-affinitive nature. The interphase offers abundant zinc nucleation sites and accommodation space, leading to uniform zinc plating/stripping and enhanced kinetics of zinc deposition/dissolution. Moreover, the chemically inert Ag interphase effectively curtails side reactions by isolating water molecules. Consequently, the incorporation of AgNO₃ enables zinc anodes to undergo cycling for extended periods, such as over 4000 h at a current density of 0.5 mA/cm² with a capacity of 0.5 mAh/cm², and for 450 h at 2 mA/cm² with a capacity of 2 mAh/cm². Full zinc-ion cells equipped with this additive not only demonstrate increased specific capacities but also exhibit significantly improved cycle stability. This research presents a cost-effective and practical approach for the development of reliable zinc anodes for ZIBs. Full article

The proliferation of electromagnetic wave applications has accentuated electromagnetic pollution concerns, highlighting the critical importance of electromagnetic wave absorbers (EMA). This study proposes innovative I-Wrapped Package Lattice electromagnetic wave absorbers (IWP–EMA) based on the triply periodic minimal surface (TPMS) lattice structure. Through a rational design of porous gradient structures, broadband wave absorption was achieved while maintaining lightweight characteristics and mechanical robustness. The optimized three-dimensional configuration features a 20 mm thick gradient structure with a progressive relative density transition from 10% to 30%. Under normal incidence conditions, this gradient IWP–EMA basically achieves broadband absorption with a reflection loss below −10 dB across the 2–40 GHz frequency band, with absorption peaks below −19 dB, demonstrating good impedance-matching characteristics. Additionally, due to the complex interactions of electromagnetic waves within the structure, the proposed IWP–EMA achieves a wide-angle absorption range of 70° under Transverse Electric (TE) polarization and 70° under Transverse Magnetic (TM) polarization. The synergistic integration of the TPMS design and additive manufacturing technology employed in this study significantly expands the design space and application potential of electromagnetic absorption structures. Full article

Sodium-ion batteries (SIBs) have been considered as a promising alternative to lithium-ion batteries (LIBs) for large-scale energy storage. However, the commercial graphite anode is not suitable for SIBs due to its low Na⁺ ion storage capability. Currently, hard carbon has been considered a promising anode material for SIBs. Herein, the surface porousized hard carbon anode materials have been prepared by using hydrogen peroxide (H₂O₂) with a hydrothermal method (HC-HO) and utilized as the anode material for SIBs. The porous structure of HC-HO provides more storage space for Na⁺ ions and enhances the intercalation/deintercalation reversibility and diffusion rate of Na⁺ ions. Moreover, HC-HO can effectively alleviate the particle volume expansion and generate a thin and stable SEI film during charge/discharge processes. Thus, the HC-HO exhibits a high reversible capacity (314.4 mAh g⁻¹ with an ICE of 92.3% at 0.05 C), excellent rate performance (241.4 mAh g⁻¹ at 3 C), and outstanding cycling stability (a capacity retention of 78.6% after 500 cycles at 1 C). The preparation of porous hard carbon provides new ideas for the future development direction of hard carbon. Full article

The nonlocal macro–meso-scale damage (NMMD) model, implemented in the framework of the finite element method, has been demonstrated to be a promising numerical approach in simulating crack initiation and propagation with reliable efficacy and high accuracy. In this study, the NMMD model was further enhanced by employing an identical degradation mechanism for both the tensile and shear components of shear stiffness, thereby overcoming the limitation of equal degradation in shear and tensile stiffness inherent in the original model. Additionally, a more refined and physically sound seepage evolution function was introduced to characterize the variation in permeability in porous media with geometric damage, leading to the development of an improved NMMD model suitable for simulating coupled seepage–stress problems. The reliability of the enhanced NMMD model was verified by the semi-analytical solutions of the classical KGD problem. Finally, based on the modified NMMD model, the effects of preset fracture spacing and natural voids on hydraulic fracture propagation were investigated. Full article

Sodium dual-ion batteries combine economic and environmental benefits by using carbon materials in both electrodes and sodium compounds in the electrolyte. Among other factors, their successful implementation for energy storage relies on optimization of the properties of the carbon electrode materials. To this end, carbon materials with a wide range of textural and structural properties were prepared by simply heat treating a single porous carbon in the absence or presence of a low-cost highly effective iron-based catalyst. These materials were investigated as anode or cathode in the sodium dual-ion batteries by prolonged galvanostatic cycling. The optimal textural and structural properties for carbon materials to achieve the best performance as electrodes in sodium dual-ion batteries were identified as having a high degree of graphitic structural order combined with minimal microporosity in the cathode and a non-graphitic structure with a layer spacing of around 0.37 nm and moderate microporosity in the anode. Full article

This paper explores the evolving relationship between Digital Twins (DT) and the Metaverse, two foundational yet often conflated digital paradigms in digital architecture. While DTs function as mirrored models of real-world systems—integrating IoT, BIM, and real-time analytics to support decision-making—Metaverses are typically fictional, immersive, multi-user environments shaped by social, cultural, and speculative narratives. Through several research projects, the team investigate the divergence between DTs and Metaverses through the lens of their purpose, data structure, immersion, and interactivity, while highlighting areas of convergence driven by emerging technologies in Artificial Intelligence (AI) and Extended Reality (XR).This study aims to investigate the convergence of DTs and the Metaverse in digital architecture, examining how emerging technologies—such as AI, XR, and Large Language Models (LLMs)—are blurring their traditional boundaries. By analyzing their divergent purposes, data structures, and interactivity modes, as well as hybrid applications (e.g., data-integrated virtual environments and AI-driven collaboration), this study seeks to define the opportunities and challenges of this integration for architectural design, decision-making, and immersive user experiences. Our research spans multiple projects utilizing XR and AI to develop DT and the Metaverse. The team assess the capabilities of AI in DT environments, such as reality capture and smart building management. Concurrently, the team evaluates metaverse platforms for online collaboration and architectural education, focusing on features facilitating multi-user engagement. The paper presents evaluations of various virtual environment development pipelines, comparing traditional BIM+IoT workflows with novel approaches such as Gaussian Splatting and generative AI for content creation. The team further explores the integration of Large Language Models (LLMs) in both domains, such as virtual agents or LLM-powered Non-Player-Controlled Characters (NPC), enabling autonomous interaction and enhancing user engagement within spatial environments. Finally, the paper argues that DTs and Metaverse’s once-distinct boundaries are becoming increasingly porous. Hybrid digital spaces—such as virtual buildings with data-integrated twins and immersive, social metaverses—demonstrate this convergence. As digital environments mature, architects are uniquely positioned to shape these dual-purpose ecosystems, leveraging AI, XR, and spatial computing to fuse data-driven models with immersive and user-centered experiences. Full article

In this research work, two distinct types of three-dimensional (3D) capacitors were successfully fabricated, each with its own unique features and advantages. The first type of capacitor is centered around a 3D nanoporous structure. This structure is formed on a nickel substrate through anodic oxidation. After undergoing high-temperature thermal oxidation, a monolithic Ni-NiO-Pt metal–insulator–metal (MIM) capacitor with a nanoporous dielectric architecture is achieved. Structurally, this innovative design brings about several remarkable benefits. Due to the nanoporous structure, it has a significantly increased surface area, which can effectively store more charges. As a result, it exhibits an equivalent capacitance density of 69.95 nF/cm², which is approximately 18 times higher than that of its planar, non-porous counterpart. This high capacitance density enables it to store more electrical energy in a given volume, making it highly suitable for applications where miniaturization and high energy storage in a small space is crucial. The second type of capacitor makes use of Through-Glass Via (TGV) technology. This technology is employed to create an interdigitated blind-via array within a glass substrate, attaining an impressively high aspect ratio of 22.5:1 (with a via diameter of 20 μm and a depth of 450 μm). By integrating atomic layer deposition (ALD), a conformal interdigital electrode structure is realized. Glass, as a key material in this capacitor, has outstanding insulating properties. This characteristic endows the capacitor with a high breakdown field strength exceeding 8.2 MV/cm, corresponding to a withstand voltage of 5000 V. High breakdown field strength and withstand voltage mean that the capacitor can handle high-voltage applications without breaking down easily, which is essential for power-intensive systems like high-voltage power supplies and some high-power pulse-generating equipment. Moreover, due to the low-loss property of glass, the capacitor can achieve an energy conversion efficiency of up to 95%. Such a high energy conversion efficiency ensures that less energy is wasted during the charge–discharge process, which is highly beneficial for energy-saving applications and systems that require high-efficiency energy utilization. Full article

Heat pipes are highly efficient heat transfer devices relying on phase-change mechanisms, with performance heavily influenced by working fluids and operational dynamics. This review article comprehensively examines hydrodynamics and heat transfer in heat pipes, contrasting conventional working fluids with nanofluid-enhanced systems. In the present work we discuss mathematical models governing fluid flow and heat transfer, emphasizing continuum and porous media approaches for wick structures. Functional dependencies of thermophysical properties (e.g., viscosity, surface tension, thermal conductivity) are reviewed, highlighting temperature-driven correlations and nanofluid modifications. Transport mechanisms within wicks are analyzed, addressing capillary-driven flow, permeability, and challenges posed by nanoparticle integration. Fourth, interfacial phase-change conditions—evaporation and condensation—are modeled, focusing on kinetic theory and empirical correlations. Also, numerical and experimental results are synthesized to quantify performance enhancements from nanofluids, including thermal resistance reduction and capillary limit extension, while addressing inconsistencies in stability and pressure drop trade-offs. Finally, applications spanning electronics cooling, aero-space, and renewable energy systems are evaluated, underscoring nanofluids’ potential to expand heat pipe usability in extreme environments. The review identifies critical gaps, such as long-term nanoparticle stability and scalability of lab-scale models, while advocating for unified frameworks to optimize nanofluid selection and wick design. This work serves as a foundational reference for researchers and engineers aiming to advance heat pipe technology through nanofluid integration, balancing theoretical rigor with practical feasibility. Full article

Severe skin damage poses a significant clinical challenge, as limited availability of skin donors, postoperative skin defects, and scarring often impair skin function. Traditional two-dimensional (2D) nanofibers exhibit small pore sizes that hinder cellular infiltration, unable to simulate the three-dimensional (3D) structure of the skin. To address these issues, we developed 3D porous nanofiber scaffolds composed of polycaprolactone–polylactic acid–mussel adhesive protein (PLGA-PCL-MAP) using low-temperature electrospinning combined with nano-spray technology. Meanwhile, this 3D scaffold features high porosity, enhanced water absorption, and improved air permeability. The incorporation of mussel adhesive protein (MAP) further increased the scaffold’s adhesive properties and biocompatibility. In vitro experiments demonstrated that the 3D nanofiber scaffolds significantly promoted the adhesion, proliferation, and migration of epidermal keratinocytes (HaCaTs) and human fibroblasts (HFBs), while providing ample space for inward cellular growth. Successful co-culture of HaCaT and HFBs within the scaffold revealed key functional outcomes: HaCaTs expressed keratinocyte differentiation markers CK10 and CK14, while HFBs actively secreted extracellular matrix components critical for wound healing, including collagen I, collagen III, and fibronectin. This skin substitute with a composite structure of epidermis and dermis based on three-dimensional nanofiber scaffolds can be used as an ideal skin replacement and is expected to be applied in wound repair in the future. Full article

This study seeks to optimize the shape of a wave absorber with an inclined porous plate using an artificial neural network (ANN) model to improve the operating efficiency and experimental accuracy of a square wave basin. As our numerical tool, we employed the dual boundary element method (DBEM) to avoid the rank deficiency problem occurring at the degenerate plate boundary with zero thickness. A quadratic velocity model incorporating a CFD-based drag coefficient was employed to account for energy dissipation across the porous plate. The developed DBEM tool was validated through comparisons with self-conducted experiments in a two-dimensional wave flume. The input features such as the inclined angle and plate length affect the performance of the wave absorber. These features have been optimized to minimize the averaged reflection coefficient and the installation space (spatial footprint) with the application of a trained ANN model. The dataset used for training the ANN model was created using the DBEM model. The trained model was subsequently utilized to predict the averaged reflection coefficient using a larger dataset, aiding in the determination of the optimal wave absorber design. In the optimization process of minimizing both reflected waves and spatial footprint, the weighting factors are assigned according to their relative importance to each other, using the weighted sum model (WSM) within the multi-criteria decision-making framework. It was found that the optimal design parameters of the non-dimensional plate length ($l/h$) and inclined angle ($\theta$) are $1.46$ and $5.34°$ when performing with a weighting factor ratio (80%: 20%) between reflection and spatial footprint. Full article

Hydroponics is a method of growing plants without soil and serves as an efficient agricultural production system. Compared to traditional farming, hydroponic crops offer significant water savings while also reducing the need for chemical pesticides by eliminating soil-borne diseases and pests. Additionally, hydroponic materials are being studied as a potential food source for space missions and as a substitute for industrially produced animal feed during winter. This paper explores the acoustic absorption properties of green materials derived from hydroponic systems. The roots of wheat grown in a porous layer formed a rigid skeleton structure. After drying, test specimens were prepared for acoustic measurements, undertaken using an impedance tube, to assess the material’s sound absorption performance. The results indicate optimal absorption around 600 Hz and 2000 Hz, reaching α = 0.95–1.0, which is significant. A brief description of the substrate layers is also provided. Full article

The design of orthopedic implants is a complex challenge, requiring the careful balance of mechanical performance and biological integration to ensure long-term success. This study focuses on the development of a porous femoral stem implant aimed at reducing stiffness and mitigating stress shielding effects. To accelerate the design process, neural networks were trained to predict the optimal density distribution of the implant, enabling rapid optimization. Two initial design spaces were evaluated, revealing the necessity of incorporating the femur’s anatomical features into the design process. The trained models achieved a median error near 0 for both conventional and extended design spaces, producing optimized designs in a fraction of the computational time typically required. Finite element analysis (FEA) was employed to assess the mechanical performance of the neural network-generated implants. The results demonstrated that the neural network predictions effectively reduced stress shielding compared to a solid model in 50% of the test cases. While the graded porosity implant design did not show significant differences in stress shielding prevention compared to a uniform porosity design, it was found to be significantly stronger, highlighting its potential for enhanced durability. This work underscores the efficacy of neural network-accelerated design in improving implant development efficiency and performance. Full article