Search Results (203)

This research seeks to investigate extremely efficient catalysts for the nitrogen reduction process (NRR), utilizing machine learning (ML)-aided density functional theory (DFT) computations. Specifically, we investigate dual transition metal atoms anchored on hexagonal nitrogen-doped graphene (TM₁-TM₂@N₆G) as prospective high-activity catalysts for the NRR. The findings indicate that the synergistic effect of dual transition metal atoms in the TM₁-TM₂@N₆G catalyst overcomes the intrinsic constraints of the linear relationship among intermediates, facilitating the activation and adsorption of N₂, thereby exhibiting significant potential for ammonia synthesis through N₂ reduction. Particularly, four catalysts screened by ML and DFT exhibit good stability and excellent selectivity and activation towards N₂. Among them, the catalysts Ti-Cr@N₆G, Ti-Mo@N₆G, and Ti-Pd@N₆G possess two reaction pathways with minimum reaction energies of 0.55 eV, 0.50 eV, and 0.40 eV, respectively. Remarkably, Ti-Co@N₆G, which features a single reaction pathway, exhibits a reaction energy lower than 0.05 eV, allowing the NRR to proceed spontaneously. It is noteworthy that incorporating ML into DFT calculations facilitates the rapid screening of all transition metal combinations, significantly accelerating the research on catalytic performance and optimizing the selection of catalysts. Full article

The Yellow River Delta is one of China’s most ecologically fragile regions, experiencing prolonged pressures from rapid urbanization and ecological degradation. Existing research, however, has predominantly focused on constructing ecological security patterns under single scenarios, with limited systematic multi-scenario comparisons and insufficient statistical support. To address this gap, this study proposes an integrated framework of “land use simulation—multi-scenario ecological security pattern construction—statistical comparative analysis.” Using the PLUS model, three scenarios were constructed—Business-as-Usual (BAU), Priority Urban Development (PUD), and Priority Ecological Protection (PEP)—to simulate land use changes by 2040. Habitat quality assessment, Multi-Scale Pattern Analysis (MSPA), landscape connectivity, and circuit theory were integrated to identify ecological source areas, corridors, and nodes, incorporating a novel hexagonal grid partitioning method. Statistical significance was evaluated using parametric tests (ANOVA, t-test) and non-parametric tests (permutation test, PERMANOVA). Analysis indicated significant differences in ecological security patterns across scenarios. Under the PEP scenario, ecological source areas reached 3580.42 km² (12.39% of the total Yellow River Delta), corresponding to a 14.85% increase relative to the BAU scenario and a 32.79% increase relative to the PUD scenario. These gains are primarily attributable to stringent wetland and forestland protection policies, which successfully limited the encroachment of construction land into ecological space. Habitat quality and connectivity markedly improved, resulting in the highest ecosystem stability. By contrast, the PUD scenario experienced an 851.46 km² expansion of construction land, resulting in the shrinkage of ecological source areas and intensified fragmentation, consequently increasing ecological security risks. The BAU scenario demonstrated moderate outcomes, with a moderately balanced spatial configuration. In conclusion, this study introduces an ecological restoration strategy of “five zones, one belt, one center, and multiple corridors” based on multi-scenario ecological security patterns. This provides a scientific foundation for ecological restoration and territorial spatial planning in the Yellow River Delta, while the proposed multi-scenario statistical comparison method provides a replicable methodological framework for ecological security pattern research in other delta regions. Full article

Symmetry is a fundamental principle in mathematics, physics, and biology, where it governs structure and invariance. Classical symmetry analysis focuses on exact group-theoretic descriptions, but rarely addresses how robust a symmetric configuration is to perturbations. In this work, we introduce a probabilistic framework for quantifying the stability of finite point-set symmetries under random deletions. Specifically, given a finite set of points with a prescribed nontrivial symmetry group, we define the probability $P_N$ that removing N points reduces the symmetry to the trivial group $C_1$. The complementary quantity $S_N=1-P_N$ serves as a measure of symmetry stability, providing a robustness profile of the configuration. We calculate $S_N$ explicitly for representative families of symmetric point sets, including linear arrays, polygons, polyhedra, directed necklace of points, and crystallographic unit cells. Our results demonstrate unexpected behaviors: the regular hexagon loses symmetry with a probability of 0.6 under the removal of three vertices, while cubes and tetrahedra exhibit the maximal robustness ($S_N=1$) for all admissible N. We further introduce a Shannon entropy of symmetry stability, which quantifies the overall uncertainty of symmetry breaking across all deletion sizes. This framework extends classical symmetry studies by incorporating randomness, linking group theory with probabilistic combinatorics, and suggesting applications ranging from crystallography to defect tolerance in physical systems. Full article

The development of highly selective and sensitive gas sensors is essential for detecting toxic pollutants, such as carbon monoxide (CO), which pose severe health and environmental risks. In this work, the adsorption of CO molecules on Ni_6−xCu_x (x = 0–6) clusters supported on hexagonal boron nitride quantum dots with nitrogen vacancies (h-BN_VQDs) is explored through density functional theory (DFT) calculations. For this purpose, the stability of the metallic clusters supported on the boron nitride sheet was calculated, and the adsorption properties of the CO molecule on the Ni_6−xCu_x (x = 0–6)/h-BN_VQDs composite were determined. The results demonstrated a high binding energy between Ni_6−xCu_x (x = 0–6) clusters and the h-BN_VQDs sheets, suggesting that Ni-Cu clusters are highly stable on h-BN_VQDs sheets. For CO adsorption, adsorption energy and charge transfer calculations indicated that the Ni₆ and Ni_6−xCu_x (x = 2 and 3) clusters exhibit the strongest CO binding and highest charge transfer, suggesting them as good candidates for CO gas sensing. These findings provide theoretical insights into the rational design of bimetallic catalysts for gas-sensing applications. Full article

Wind turbine blades feature complex geometries and operate under harsh conditions, including high curvature gradients, nonlinear deformations, elevated humidity, and particulate contamination. This study presents the design and kinematic analysis of a novel climbing robot based on a 10R folding metamorphic mechanism. The robot employs a hybrid wheel-leg drive and adaptively reconfigures between rectangular and hexagonal topologies to ensure precise adhesion and efficient locomotion along blade leading edges and windward surfaces. A high-order kinematic model, derived from a modified Grubler–Kutzbach criterion augmented by rotor theory, captures the mechanism’s intricate motion characteristics. We analyze the degrees of freedom (DOF) and motion branch transitions for three representative singular configurations, elucidating their evolution and constraint conditions. A scaled-down prototype, integrating servo actuators, vacuum adhesion, and multi-modal sensing on an MDOF control platform, was fabricated and tested. Experimental results demonstrate a configuration switching time of 6.3 s, a single joint response time of 0.4 s, and a maximum crawling speed of 125 mm/s, thereby validating stable adhesion and surface tracking performance. This work provides both theoretical insights and practical validation for the intelligent maintenance of wind turbine blades. Full article

As the most unstable crystalline form of calcium carbonate, vaterite is rarely found in nature due to being highly prone to phase transitions. However, its high specific surface area, excellent biocompatibility, and high solubility properties have led to a research boom and the following breakthroughs in the last two decades: (1) From primitive calculations and spectroscopic analyses to modern multidimensional research methods combining calculations and experiments, the crystal structure of vaterite has turned from early identifications in orthorhombic and hexagonal crystal systems to a complex polymorphic structure within the monoclinic crystal system. (2) The formation process of vaterite not only conforms to the classical crystal growth theory but also encompasses the nanoparticle aggregation theory, which incorporates the concepts of oriented nanoparticle assembly and mesoscale transformation. (3) Regardless of the conditions, the formation of vaterite depends on an excess of CO₃²⁻ relative to Ca²⁺, and its stability duration relates to preservation conditions. (4) Vaterite demonstrates significant value in biomedical applications—including bone repair scaffolds, targeted drug carriers, and antibacterial coating materials—leveraging its porous structure, high specific surface area, and exceptional biocompatibility. While it also shows utility in environmental pollutant adsorption and general coating technologies, the current research remains predominantly concentrated on its medical applications. Currently, the rapid transformation of vaterite presents the primary limitation for its industrial application. Future research should prioritize investigating its formation kinetics and stability. Full article

Aluminum–hydrogen compounds have drawn considerable interest for applications in solid-state hydrogen storage. The structural, hydrogen storage, electronic, mechanical, phonon, and thermodynamic properties of XAl₂H₂ (X = Ca, Sr, Sc, Y) hydrides are investigated using density functional theory. These hydrides exhibit negative formation energies in the hexagonal phase, indicating their thermodynamic stability. The gravimetric hydrogen storage capacities of CaAl₂H₂, SrAl₂H₂, ScAl₂H₂, and YAl₂H₂ are calculated to be 1.41 wt%, 0.94 wt%, 1.34 wt%, and 0.93 wt%, respectively. Analysis of the electronic density of states reveals metallic characteristics. Furthermore, the calculated elastic constants satisfy the Born stability criteria, confirming their mechanical stability. Additionally, through phonon spectra analysis, dynamical stability is verified for CaAl₂H₂ and SrAl₂H₂ but not for ScAl₂H₂ and YAl₂H₂. Finally, we present temperature-dependent thermodynamic properties. This research reveals that XAl₂H₂ (X = Ca, Sr, Sc, Y) materials represent promising candidates for solid-state hydrogen storage, providing a theoretical foundation for further studies on XAl₂H₂ systems. Full article

The transport properties of one-dimensional van der Waals nanodevices composed of carbon nanotubes (CNTs), hexagonal boron nitride (hBN) nanotubes, and molybdenum dichalcogenide (MoX₂) nanotubes were investigated within the framework of density functional theory (DFT). It was found that in nanodevices based on MoS₂(24,24) and MoTe₂(24,24), the effect of resonant tunneling is suppressed due to electron–phonon scattering. This suppression arises from the fact that these materials are semiconductors with an indirect band gap, where phonon participation is required to conserve momentum during transitions between the valence and conduction bands. In contrast, nanodevices incorporating MoSe₂(24,24), which possesses a direct band gap, exhibit resonant tunneling, as quasiparticles can tunnel between the valence and conduction bands without a change in momentum. It was demonstrated that the presence of vacancy defects in the CNT segment significantly degrades quasiparticle transport compared to Stone–Wales (SW) defects. Furthermore, it was revealed that resonant interactions between SW defects in MoTe₂(24,24)–hBN(27,27)–CNT(24,24) nanodevices can enhance the differential conductance under certain voltages. These findings may be beneficial for the design and development of nanoscale diodes, back nanodiodes, and tunneling nanodiodes. Full article

This study investigates the coupling mechanism between a parabolic notch and dislocations in one-dimensional (1D) hexagonal piezoelectric quasicrystals (PQCs) based on the theory of complex variable functions. By applying perturbation techniques and the Cauchy integral, analytical solutions for complex potentials are derived, yielding closed-form expressions for the phonon–phason stress field and electric displacement field. Numerical examples reveal several key findings: significant stress concentration occurs at the notch root, accompanied by suppression of electric displacement; interference patterns between dislocation cores and notch-induced stress singularities are identified; the J-integral quantifies distance-dependent forces, size effects, and angular force distributions reflecting notch symmetry; and the energy-driven dislocation slip toward free surfaces leads to the formation of dislocation-free zones. These results provide new insights into electromechanical fracture mechanisms in quasicrystals. Full article

Polynitrogen compounds have broad applications in the field of high-energy materials, making the exploration of two-dimensional polynitride materials with both novel properties and practical utility a highly attractive research challenge. Through global structure search methods and first-principles theoretical calculations at the Perdew–Burke–Ernzerhof (PBE) level of density functional theory (DFT), the globally minimum-energy configuration of a novel planar BeN₃ monolayer (tetr-2D-BeN₃) is predicted. This material exhibits a planar quasi-isotropic structure containing pentagonal, hexagonal, and dodecagonal rings, as well as “S”-shaped N6 polymeric units, exhibiting a high energy density of 3.34 kJ·g⁻¹, excellent lattice dynamic stability and thermal stability, an indirect bandgap of 2.66 eV (HSE06), high carrier mobility, and ultraviolet light absorption capacity. In terms of mechanical properties, it shows a low in-plane Young’s stiffness of 52.3–52.9 N·m⁻¹ and a high in-plane Poisson’s ratio of 0.55–0.56, indicating superior flexibility. Furthermore, its porous structure endows it with remarkable selectivity for hydrogen (H₂) and argon (Ar) gas separation, achieving a maximum selectivity of up to 10²³ (He/Ar). Therefore, the tetr-2D-BeN₃ monolayer represents a multifunctional two-dimensional polynitrogen-based energetic material with potential applications in energetic materials, flexible semiconductor devices, ductile materials, ultraviolet photodetectors, and other fields, thereby expanding the design possibilities for polynitride materials. Full article

Despite the promising electronic properties of graphene, its lack of an intrinsic bandgap limits its applicability in semiconductor technologies. This has catalyzed the investigation of newly developed two-dimensional carbon materials, including tetragraphene (TG), a quasi-2D semiconducting material featuring a combination of hexagonal and tetragonal rings. This study aims to investigate the mechanical and fracture behaviors of TG using density functional theory (DFT) and molecular dynamics (MD) simulations, studying two distinct atomic configurations of tetragraphene. DFT simulations assess the mechanical properties, while MD simulations explore the fracture dynamics subjected to mixed mode I (opening mode) and mode II (in-plane shear mode) loading. Our analysis focuses on the influence of loading phase angle, crack edge chirality, crack tip configuration, and temperature on crack propagation paths and critical stress intensity factors (SIFs) in TG structures. Our results show that the critical SIF varies by 12.5–21% depending on the crack chirality. Across all loading conditions, increasing the temperature ranging from 300 K to 2000 K reduces the critical SIF by 10–45%, with the largest reductions observed under pure mode I loading. These outcomes offer important insights into the structural integrity of TG and inform its potential integration into flexible nanoelectronic devices, where mechanical reliability is essential. Full article

The structural parameters and electronic structures of Sc- and Y-based nitride semiconductors that adopted hexagonal BN-like atomic sheets were investigated with calculations based on density functional theory (DFT). A hybrid exchange-correlation functional and spin–orbit coupling were employed for studies on the band structures. A strong variation in the band gap type, as well as the width, was revealed not only between the monolayer and bulk materials but also between the multilayer systems. An exceptionally wide range of band gaps from 1.39 (bulk) up to 3.59 eV (three layers) was obtained for two-dimensional materials based on ScN. This finding is related to two phenomena: significant contributions of subsurface ions into bands that formed a valence band maximum and pronounced shifts in conduction band positions with respect to the Fermi energy between the multilayer systems. The relatively low values of the work function (below 2.36 eV) predicted for the few-layer YN materials might be considered for applications in electron emission. In spite of the fact that the band gaps of two-dimensional materials predicted with hybrid DFT calculations may be overestimated to some extent, the electronic structure of homo- and heterostructures formed by rare earth nitride semiconductors seems to be an interesting subject for further experimental research. Full article

To address the deployment accuracy issues of multi-frequency band reflector antennas, this study takes a hexagonal prism modular deployable antenna as an example and proposes an accuracy design method. This paper proposes a screw-theory-based sub-chain precision analysis method. This method constructs a virtual screw model of rod length errors and hinge gap errors. Based on geometric relationships, a multi-loop point position error model is established, and accuracy surfaces considering rod length errors and hinge gap are output using MATLAB R2024b. By outputting the relationship curves of single-rod errors relative to point errors, the linearized influence law of individual rods on precision is further elucidated. Simulation results demonstrate the reliability of the error modeling theory. Based on the established cost-effective precision model and the minimum point error, which is obtained by using the numerical iterative method, the optimal solution for error parameters is obtained. Full article

Permanent magnetic materials are essential for technological applications, with the majority of available magnets being either ferrites or materials composed of critical rare-earth elements, such as well-known Nd₂Fe₁₄B. The binary Fe₂P material emerges as a promising candidate to address the performance gap, despite its relatively low Curie temperature $T_C$ of 214 K. In this study, density functional theory was employed to investigate the effect of Si and Co substitution on the magnetic moments, magnetocrystalline anisotropy energy (MAE) and Curie temperature in ${\mathrm{Fe}}_{2-y}$Co_yP_1−xSi_x compounds. Our findings indicate that Si substitution enhances magnetic moments due to the increase in 3f-3f and 3f-3g interaction energies, which also contribute to higher $T_C$ values. Conversely, Co substitution leads to a reduction in magnetic moments, attributable to the inherently lower magnetic moments of Co. In all examined cases of different Si concentrations, such as hexagonally structured ${\mathrm{Fe}}_{2-y}$Co_yP, ${\mathrm{Fe}}_{2-y}$Co_yP_0.92Si_0.08 and ${\mathrm{Fe}}_{2-y}$Co_yP_0.84Si_0.16, Co substitution increases the Curie temperatures by augmenting 3g-3g exchange interaction energies. Both Si and Co substitutions decrease the magnetocrystalline anisotropy energy, resulting in the loss of the easy magnetization direction at higher Co contents. However, higher Si concentrations appear to confer resilience against the loss. In summary, Si and Co substitutions effectively modify the investigated magnetic properties. Nonetheless, to preserve a high MAE, the extent of substitution should be optimized. Full article

The global energy shortage and the gradual depletion of lithium resources have become increasingly prominent. Improving the energy density of lithium-based secondary batteries and developing other high-performance alkali-metal secondary batteries have become the research focus. In this study, two-dimensional (2D) hexagonal metal borides (h-MBenes) are investigated as ordered alkali metal adsorption substrates for alkali-metal-based battery anode materials using density functional theory (DFT). Twelve thermodynamically stable h-MBenes are screened out from thirty-three structures, and their excellent stability and metallic electronic characteristics are confirmed. The ordered multilayered growth in alkali metal adsorption is found to depend on two factors: low lattice mismatching and dynamic matching of the work function. In particular, Mg/Al/V-based h-MBenes exhibit excellent lithium lattice matching (<3.35% mismatch), enabling layer-by-layer hexagonal (001) Li growth for ≥5 layers. They have ultrahigh lithium capacities (2170–3818 mAh·g⁻¹), low migration barriers (0.01–0.05 eV), and low voltages (0.003–0.714 V). Mg/Y-based h-MBenes enable three Na layers’ adsorption with a capacity of 1717/605 mAh·g⁻¹, and Al₂B₂ achieves a 472 mAh·g⁻¹ potassium storage capacity, respectively. Due to the orderly multilayered growth mechanism, Mg/Al/V-based h-MBenes show great potential as high-safety and ultrahigh-capacity alkali-metal battery anode materials. Full article