Search Results (81)

This study investigates the microstructural evolution and mechanical response of an additively manufactured (PBF-LB/M) AlSi10Mg alloy subjected to severe plastic deformation via two passes of twist channel angular pressing (TCAP). Processing was conducted using Route Bc, with the first pass at 150 °C and the second at 250 °C. For the first time, the evolution from the initial hierarchical AM structure to a refined state was characterized in high-fidelity detail using a novel EBSD detector. The two-pass process transformed the initial structure into a heterogeneous, bimodal microstructure existing in a non-equilibrium state, characterized by a high fraction of low-angle grain boundaries (63%) and significant internal lattice distortion. The mechanical properties were dictated by the processing temperature: a single pass at 150 °C induced work hardening, increasing the yield strength from 450 MPa to 482 MPa. Conversely, the second pass at an elevated temperature of 250 °C promoted significant dynamic recovery. This led to a decrease in yield strength to 422 MPa but concurrently resulted in a substantial increase in ultimate compressive strength to 731 MPa. Full article

The continuous advancement of fire protection technologies has necessitated the development of comprehensive safety standards, leading to an increasingly diversified and specialized regulatory landscape. This has made it difficult for fire protection professionals to quickly and accurately locate the required fire safety standard information. In addition, the lack of effective integration and knowledge organization concerning fire safety standard entities has led to the severe fragmentation of fire safety standard information and the absence of a comprehensive “one map”. To address this challenge, we introduce FT-FLAT, an innovative CNN–Transformer fusion architecture designed specifically for fire safety standard entity extraction. Unlike traditional methods that rely on rules or single-modality deep learning, our approach integrates TextCNN for local feature extraction and combines it with the Flat-Lattice Transformer for global dependency modeling. The key innovations include the following. (1) Relative Position Embedding (RPE) dynamically encodes the positional relationships between spans in fire safety texts, addressing the limitations of absolute positional encoding in hierarchical structures. (2) The Multi-Branch Prediction Head (MBPH) aggregates the outputs of TextCNN and the Transformer using Einstein summation, enhancing the feature learning capabilities and improving the robustness for domain-specific terminology. (3) Experiments conducted on the newly annotated Fire Safety Standard Entity Recognition Dataset (FSSERD) demonstrate state-of-the-art performance (94.24% accuracy, 83.20% precision). This work provides a scalable solution for constructing fire safety knowledge graphs and supports intelligent information retrieval in emergency situations. Full article

In the rapidly evolving fields of materials science, catalysis, electronics, drug delivery, and environmental remediation, the development of effective substrates for molecular deposition has become increasingly crucial. Ordered mesoporous silica materials have garnered significant attention due to their unique structural properties and exceptional potential as substrates for molecular immobilization across these diverse applications. This study compares three mesoporous silica powders: MCM-41, SBA-15, and SBA-16. A multi-technique characterization approach was employed, utilizing low- and wide-angle X-ray diffraction (XRD), nitrogen physisorption, and transmission electron microscopy (TEM) to elucidate the structure–property relationships of these materials. XRD analysis confirmed the amorphous nature of silica frameworks and revealed distinct pore symmetries: a two-dimensional hexagonal (P6mm) structure for MCM-41 and SBA-15, and three-dimensional cubic (Im$\overline{3}$m) structure for SBA-16. Nitrogen sorption measurements demonstrated significant variations in textural properties, with MCM-41 exhibiting uniform cylindrical mesopores and the highest surface area, SBA-15 displaying hierarchical meso- and microporosity confirmed by NLDFT analysis, and SBA-16 showing a complex 3D interconnected cage-like structure with broad pore size distribution. TEM imaging provided direct visualization of particle morphology and internal pore architecture, enabling estimation of lattice parameters and identification of structural gradients within individual particles. The integration of these complementary techniques proved essential for comprehensive material characterization, particularly for MCM-41, where its small particle size (45–75 nm) contributed to apparent structural inconsistencies between XRD and sorption data. This integrated analytical approach provides valuable insights into the fundamental structure–property relationships governing ordered mesoporous silica materials and demonstrates the necessity of combined characterization strategies for accurate structural determination. Full article

Lattice structures emerged as a revolutionary class of materials with significant applications in aerospace, biomedical engineering, and mechanical design due to their exceptional strength-to-weight ratio, energy absorption properties, and structural efficiency. This review systematically examines recent advancements in lattice structures, with a focus on their classification, mechanical behavior, and optimization methodologies. Stress distribution, deformation capacity, energy absorption, and computational modeling challenges are critically analyzed, highlighting the impact of manufacturing defects on structural integrity. The review explores the latest progress in hybrid additive manufacturing, hierarchical lattice structures, modeling and simulation, and smart adaptive materials, emphasizing their potential for self-healing and real-time monitoring applications. Furthermore, key research gaps are identified, including the need for improved predictive computational models using artificial intelligence, scalable manufacturing techniques, and multi-functional lattice systems integrating thermal, acoustic, and impact resistance properties. Future directions emphasize cost-effective material development, sustainability considerations, and enhanced experimental validation across multiple length scales. This work provides a comprehensive foundation for future research aimed at optimizing biomimetic lattice structures for enhanced mechanical performance, scalability, and industrial applicability. Full article

Developing high-performance photocatalysts for solar hydrogen production requires the synergistic modulation of chemical composition, nanostructure, and charge carrier transport pathways. Herein, we report a Cs and P co-doped tubular graphitic carbon nitride (Cs/PTCN-x) photocatalyst synthesized via a strategy that integrates elemental doping with morphological engineering. Structural characterizations reveal that phosphorus atoms substitute lattice carbon to form P-N bonds, while Cs⁺ ions intercalate between g-C₃N₄ layers, collectively modulating surface electronic states and enhancing charge transport. Under visible-light irradiation (λ ≥ 400 nm), the optimized Cs/PTCN-3 catalyst achieves an impressive hydrogen evolution rate of 8.085 mmol·g⁻¹·h⁻¹—over 33 times higher than that of pristine g-C₃N₄. This remarkable performance is attributed to the multidimensional synergy between band structure tailoring and hierarchical porous tubular architecture, which together enhance light absorption, charge separation, and surface reaction kinetics. This work offers a versatile approach for the rational design of g-C₃N₄-based photocatalysts toward efficient solar-to-hydrogen energy conversion. Full article

Optimal path planning algorithms offer substantial benefits in high-density storage (HDS) systems in modern smart manufacturing. However, traditional algorithms may encounter significant optimization challenges due to intricate architectural configurations and traffic constraints of the HDS system. This paper addresses these issues by introducing a two-step novel path planning method: (1) the mesh-tree grid map topological representation and the (2) Lattice-Hopping (LH) algorithm. The proposed method first converts the layout of an HDS system into a mesh-tree grid hierarchical structure by capturing and simplifying the spatial and geometrical information as well as the traffic constraints of the HDS system. Then, the LH algorithm is proposed to find optimal shipping path by leveraging the global connectivity of main tracks (main track priority) and the ‘jumping’ mechanism of sub-tracks. The main track priority and the ‘jumping’ mechanism work together to save computational complexity and enhance the feasibility and optimality of the proposed method. Numerical and case studies are performed to demonstrate the superiorities of our method to properly modified benchmark algorithms. Algorithm scalability, robustness, and operational feasibility for industrial production in modern smart manufacturing are also displayed and emphasized. Full article

Traditional β-eucryptite (LiAlSiO₄) is renowned for its unique characteristics of low thermal expansion and high temperature thermal stability, making it an ideal material for precision instruments and aerospace applications. In this study, β-eucryptite was fabricated into an aerogel structure through the sol–gel process and supercritical drying method and using alumina sol as a cost-effective precursor. The synthesized β-eucryptite aerogel demonstrated unique properties including a negative thermal expansion coefficient (−7.85 × 10⁻⁶ K⁻¹), low density (0.60 g/cm³), and high specific surface area (18.1 m²/g). X-ray diffraction (XRD) and transmission electron microscopy (TEM) mutually corroborated the crystalline structure of β-eucryptite, with XRD confirming the phase purity and TEM imaging revealing well-defined crystal lattice characteristics. Combined nitrogen adsorption–desorption analysis and scanning electron microscopy observations supported the hierarchical porous microstructure, with SEM visualizing interconnected nanoporous networks and nitrogen sorption data verifying the porosity. The negative thermal expansion behavior was directly linked to the β-eucryptite crystal structure, as collectively validated by thermal expansion measurements. Additionally, Fourier transform infrared spectroscopy (FTIR) independently confirmed the aluminosilicate framework structure through characteristic vibrational modes. This research shows the innovation in the synthesis of β-eucryptite aerogel, especially its application potential in precision instruments and building materials that need low thermal expansion and high stability, and the use of aluminum sol as an aluminum source has simplified the preparation steps and reduced production costs. Full article

This paper investigates the axial deformation characteristics and crashworthiness of thin-walled metal tubes (TWT) reinforced with Polyetherketoneketone (PEKK) honeycomb lattice structures consisting of bio-inspired hierarchical cellular topological features. Experimentally validated numerical results revealed that the specific energy absorption capacity (SEA) of these composite structures increased with filler volume corresponding to a specific cellular topology. This includes the bio-inspired hierarchical sparse (BHS) topology, which registered a remarkable improvement in SEA over the hollow tube of 202%. In contrast, the central (BHC) topology deformed in an unstable hex-dominated pattern and triggered catastrophic failure of the composite in global bending mode. Furthermore, rigid cells were shown to drastically increase the initial peak force (IPF), while cells with low stiffness were beneficial for maintaining a low level of IPF and moderately improving SEA. Moreover, the rib and wall thickness of the BHS honeycomb cells were suitably tailored to increase the SEA by 2.1%, while simultaneously reducing the IPF by 3.7%. These findings suggest that multi-functional mechanical attributes of PEKK hierarchical honeycomb lattice fillers can mutually benefit thin-walled tubes with superior energy absorption capability and lightweight features over conventional lattice-filled tubes or a hollow tube. Full article

The performance degradation of sodium-ion batteries (SIBs) in extremely low-temperature conditions has faced significant challenges for energy storage applications in extreme environments. This review systematically establishes failure mechanisms that govern the performance of low-temperature SIBs, including significantly increased electrolyte viscosity, lattice distortion and adverse phase transitions in electrodes, and sluggish desolvation kinetics at the solid electrolyte interface. Herein, we specifically summarize a series of multi-scale optimization strategies to address these low-temperature challenges: (1) optimizing low-freezing-point solvent components and regulating solvation structures to increase ionic diffusion conductivity; (2) enhancing the hierarchical structure of electrodes and optimizing electron distribution density to improve structural stability and capacity retention at low temperatures; and (3) constructing an inorganic-rich solid electrolyte interphase to induce uniform ion deposition, reduce the desolvation barrier, and inhibit side reactions. This review provides a comprehensive overview of low-temperature SIB applications coupled with advanced characterization and first-principles simulations. Furthermore, we highlight solvation-shell dynamics, charge transfer kinetics, and metastable-phase evolution at the atomic scale, along with the critical pathways for overcoming low-temperature limitations. This review aims to establish fundamental principles and technological guidelines for deploying advanced SIBs in extreme low-temperature environments. Full article

We investigate the spatial z-correlators of meson operators in $N_f=2+1+1+1$ lattice QCD with optimal domain-wall quarks across eight temperatures ranging from 325 to 3250 MeV. The meson operators include a complete set of Dirac bilinears for ten flavor combinations. Our findings reveal a hierarchical restoration of chiral symmetry in QCD with $(u,d,s,c,b)$ quarks, progressing sequentially from $SU{\left(2\right)}_L\times SU{\left(2\right)}_R\times U{\left(1\right)}_A$ to $SU{\left(3\right)}_L\times SU{\left(3\right)}_R\times U{\left(1\right)}_A$, then to $SU{\left(4\right)}_L\times SU{\left(4\right)}_R\times U{\left(1\right)}_A$, and finally to $SU{\left(5\right)}_L\times SU{\left(5\right)}_R\times U{\left(1\right)}_A$ as the temperature increases. Additionally, we explore the emergence of the $SU{\left(2\right)}_{CS}$ chiral-spin symmetry and compare the temperature windows for all flavor combinations. Our results indicate that the temperature windows for the emergent $SU{\left(2\right)}_{CS}$ symmetry are primarily dominated by the $\overline{u}b$ and $\overline{s}b$ sectors. Full article

In this work, we developed 3D ionic liquid (IL) functionalized graphene assemblies (GAs) decorated by ultrafine RuCu alloy nanoparticles (RuCu-ANPs) via a one-step synthesis process, and integrated it into a microfluidic sensor chip for in situ electrochemical detection of NO released from living cells. Our findings have demonstrated that RuCu-ANPs on 3D IL-GA exhibit high density, uniform distribution, lattice-shaped arrangement of atoms, and extremely ultrafine size, and possess high electrocatalytic activity to NO oxidation on the electrode. Meanwhile, the 3D IL-GA with hierarchical porous structures can facilitate the efficient electron/mass transfer at the electrode/electrolyte interface and the cell culture. Moreover, the graft of IL molecules on GA endows it with high hydrophilicity for facile and well-controllable printing on the electrode. Consequently, the resultant electrochemical microfluidic sensor demonstrated excellent sensing performances including fast response time, high sensitivity, good anti-interference ability, high reproducibility, long-term stability, as well as good biocompatibility, which can be used as an on-chip sensing system for cell culture and real-time in situ electrochemical detection of NO released from living cells with accurate and stable characteristics in physiological conditions. Full article

Although there do exist a few aeroacoustic studies on harmful artificial phenomena related to the usage of non-uniform Cartesian grids in lattice Boltzmann methods (LBM), a thorough quantitative comparison between different categories of grid arrangement is still missing in the literature. In this paper, several established schemes for hierarchical grid refinement in lattice Boltzmann simulations are analyzed with respect to spurious aeroacoustic emissions using a weakly compressible model based on a D3Q19 athermal velocity set. In order to distinguish between various sources of spurious phenomena, we deploy both the classical Bhatnagar–Gross–Krook and other more recent collision models like the hybrid recursive-regularization operator, the latter of which is able to filter out detrimental non-hydrodynamic mode contributions, inherently present in the LBM dynamics. We show by means of various benchmark simulations that a cell-centered approach, either with a linear or uniform explosion procedure, as well as a vertex-centered direct-coupling method, proves to be the most suitable with regards to aeroacoustics, as they produce the least amount of spurious noise. Furthermore, it is demonstrated how simple modifications in the selection of distribution functions to be reconstructed during the communication step between fine and coarse grids affect spurious aeroacoustic artifacts in vertex-centered schemes and can thus be leveraged to positively influence stability and accuracy. Full article

Design optimization through the integration of multiple functions into a single part is a highly effective strategy to reduce costs, simplify assembly, improve performance, and reduce weight. Additive manufacturing facilitates the production of complex structures by allowing parts consolidation, resulting in optimized designs, where multiple functions are integrated into a single component. This study presents a design for additive manufacturing method for integrating multiple lattice structures to achieve thermal management and shock absorption functions. The method follows modeling and simulation phases for dimensioning and optimizing solutions to deliver the design functions at different macro- and mesoscale levels. Hierarchical complexity was leveraged to design the two-levels structure in a single part, each delivering a specific function. Specifically, the external layer addresses energy absorption and thermal insulation, while the internal layer acts as a thermal battery by incorporating a phase change material. The design of a container carried by an unmanned aerial vehicle for the transport of healthcare and biological materials is presented. The container is shock-resistant and can maintain the content at 4 ± 2 °C for at least 1 h. As it operates passively without the need for additional energy-consuming devices, it is easy to operate and contributes to increased flight autonomy. A flight mission experiment for urgent transport of blood bags confirmed the capability of the container to preserve blood integrity. This case study demonstrates that the two-layer lattice structure design represents a highly efficient approach to multifunctional design optimization. Full article

In this study, we successfully synthesized a Pd-doped SnO₂ (Pd-SnO₂) material with a flower-like hierarchical structure using the solvothermal method. The material’s structural proper-ties were characterized employing techniques such as XRD, XPS, FESEM and HRTEM. A gas sensor fabricated from the 2.0 mol% Pd-SnO₂ material demonstrated exceptional sensitivity (R_a/R_g = 106) to 100 ppm ethanolamine at an operating temperature of 150 °C, with rapid response/recovery times of 10 s and 12 s, respectively, along with excellent linearity, selectivity, and stability, and a detection limit down to 1 ppm. The superior gas-sensing performance is attributed to the distinctive flower-like hierarchical architecture of the Pd-SnO₂ and the lattice distortions introduced by Pd doping, which substantially boost the material’s sensing characteristics. Further analysis using density functional theory (DFT) has revealed that within the Pd-SnO₂ system, Sn exhibits strong affinities for O and N, leading to high adsorption energies for ethanolamine, thus enhancing the system’s selectivity and sensitivity to ethanolamine gas. This research introduces a novel approach for the efficient and rapid detection of ethanolamine gas. Full article

We propose several hierarchical graphs that represent the semantic relations between physical theories, their fundamental constants and units of measurement. We begin with an alternative representation of Zel’manov’s cube of fundamental constants as a concept lattice. We then propose the inclusion of a new fundamental constant, Milgrom’s critical acceleration, and discuss the implications of such analysis. We then look for the same fundamental constants in a graph that relates magnitudes and units of measurement in the International System of Units. This exercise shows the potential of visualizing hierarchical networks as a tool to better comprehend the symmetries, interrelations and dependencies of physical magnitudes, units and theories. New regimes of application may be deduced, as well as an interesting reflection on our ontologies and corresponding theoretical objects. Full article