Three-dimensional (3D) printing has enabled the fabrication of magnesium (Mg) bone scaffold lattices with precisely controlled porosity, strut geometry, and pore architecture, offering unprecedented opportunities to mimic the mechanical behavior of trabecular bone. However, the high specific surface area of these lattice structures exacerbates the rapid corrosion of Mg in physiological fluids, leading to premature loss of mechanical integrity, a critical drawback for load-bearing orthopedic applications. Surface coating strategies are essential to decouple degradation kinetics from mechanical function. This review systematically evaluates how various coating systems, including micro-arc oxidation (MAO), calcium phosphates, biodegradable polymers, and composite multilayers, influence the mechanical performance of 3D-printed Mg lattice scaffolds. We focus on key mechanical metrics, with primary emphasis on compressive strength, elastic modulus, and yield strength under monotonic loading, while also critically assessing the limited available data on fatigue resistance and coating-substrate adhesion under cyclic conditions. A central theme is the interplay between lattice topology (e.g., gyroid, diamond, or rectilinear designs) and coating uniformity, where complex surfaces often exhibit non-uniform thickness, creating stress concentration sites. Recent advances in coatings that actively self-adapt or heal after mechanical damage are discussed, alongside a critical evaluation of their translation challenges from flat substrates to complex lattice architectures. We also identify critical gaps, including the near-absence of standardized fatigue testing for coated porous lattices and limited in vivo data correlating coating performance with long-term load-bearing outcomes. Finally, we propose future research directions, such as topology-optimized coatings and hybrid additive-surface engineering workflows, to achieve clinically viable, mechanically robust, and corrosion-controlled 3D-printed Mg lattice scaffolds for bone regeneration.
Freshwater scarcity has become a pressing global challenge, and pervaporation (PV) has emerged as a promising technology for seawater desalination. In nanoporous membranes, desalination performance is largely determined by membrane nanostructure and interfacial transport behavior, making molecular-level understanding of water and ion transport crucial for membrane design. Herein the performance of novel three-dimensional boron nitride honeycomb (BNHC) membrane for seawater desalination via PV process was investigated by molecular dynamics simulations. The results revealed that water molecules permeated through the BNHC membrane and evaporated at the membrane exit surface. A non-monotonic relationship was observed between membrane thickness and water flux: both permeation and evaporation fluxes initially increased before declining, though the permeation flux peaked at a lower thickness threshold. Mechanistically, the optimal thickness balances enthalpic and entropic effects to maintain continuous water supply. Fundamentally, the structural stability and dynamic agility of hydrogen bonds underlie the intrinsic connection between fast permeation and rapid interfacial evaporation. Furthermore, elevated solution temperatures further enhance water flux by accelerating interfacial hydrogen bonds relaxation and promoting thermal desorption. Notably, the BNHC membrane exhibited exceptional rejection rates across four different ionic solutions (i.e., NaCl, KCl, MgCl2 and NaBr), achieving complete cation rejection and high anion exclusion. These findings provided valuable theoretical insights into the PV behavior in ionic solutions, highlighting the potential of BNHC as an advanced material for seawater desalination.
This paper presents a wavelet-based finite element formulation for the mechanical analysis of fractional viscoelastic problems. The viscoelastic behavior is modeled using the fractional-order Kelvin–Voigt constitutive law, which captures the memory-dependent response of polymers and composites more accurately than classical integer-order models. To address the computational challenges of fractional derivatives, the proposed method transforms the resulting improper integral into a system of algebraic equations using Cardinal Chebyshev wavelets (CCW). This approach significantly enhances both the accuracy and efficiency of the numerical solution. The framework is validated through a benchmark problem, demonstrating its reliability and precision. Additionally, a parametric study investigates the rheological behavior of the materials. The results indicate that the proposed approach offers high fidelity and robustness, establishing it as a promising tool for analyzing complex fractional viscoelastic systems.
Dynamic analysis of structures is one of the most essential techniques for designing earthquake-resistant structures in high-seismicity areas such as the Tehran metropolis. The selection of the acceleration time history of previous earthquakes for utilization in the dynamic analysis is challenging while the chosen ground motions must be not only proportionate to the seismic capacity of the region but also matched a target response/design spectrum. The uniform hazard spectrum (UHS), derived from probabilistic seismic hazard analysis (PSHA), comprises large spectral values at all periods and is too conservative when used as a target for scaling ground motions. An alternative approach is to use the conditional mean spectrum (CMS), which provides a response spectrum conditioned on a spectral acceleration value associated with a unique target period. This alternative procedure is introduced as an appropriate method for selecting and scaling proper ground motions to be used as input for structural dynamic analysis. This study develops the conditional mean spectrum for selected sites in the Tehran region. To this end, a comprehensive PSHA was conducted for the metropolis of Tehran. Subsequently, employing the UHS obtained from the PSHA and the results of the subsequent deaggregation process, the CMS was generated for different sites in the region. The distinction between the CMS and the UHS significantly influences the dynamic behavior of various structural systems in the region. For short-period structures, such as low-rise buildings, the CMS effectively mitigates the unrealistically high spectral accelerations predicted by the UHS at longer periods, resulting in a more rational distribution of seismic demands. In contrast, for long-period structures, including high-rise buildings, the CMS alleviates the overly conservative short-period spectral accelerations associated with the UHS. This results in more realistic force–deformation demands and an improved representation of expected structural responses. Consequently, the application of the CMS directly impacts seismic design decisions and material requirements. The results indicate that CMS-based design can reduce unnecessary conservatism and associated construction costs, particularly for structures sensitive to long-period demands. Furthermore, the findings suggest that the design spectra of the Iranian Seismic Code should be re-evaluated, especially for near-fault sites, to better reflect period-dependent seismic hazard characteristics.
This study introduces a Caputo fractional-order epidemic model to analyze the transmission dynamics of waterborne diseases, such as cholera, with vaccination as a control measure. The population is divided into five compartments alongside the pathogen concentration in water. Using the mass-action incidence rate β S(t)B(t) , a fractional-order system is formulated to capture memory-dependent transmission dynamics. We first establish the existence, uniqueness, positivity, and boundedness of solutions within a positively invariant region. The basic reproduction number ℛ_0 is derived, and two equilibrium points–disease-free and endemic–are identified. Through fractional Routh–Hurwitz criteria and a direct Lyapunov method adapted to the Caputo derivative, we prove that the DFE is globally asymptotically stable when ℛ_0 < 1 , while the EE becomes stable when ℛ_0 > 1 . Numerical simulations, implemented via generalized hat functions, illustrate the influence of the fractional-order α on convergence rates. Results indicate that fractional models lead to slower, more prolonged outbreaks compared to classical integer-order models, emphasizing the role of memory effects in epidemic persistence. The findings highlight the combined importance of vaccination and water sanitation in disease control and demonstrate the utility of fractional calculus in modeling complex biological systems with hereditary dynamics.
