An integrated three-stage methodology is proposed for the predictive assessment and proactive maintenance of stacker bridges.A three-dimensional finite element analysis (FEA) is performed to characterize the displacement and von Mises stress fields, identifying critical nodes using a kinematic deformation scale factor of 908.2x. A fractal mapping of cracks in the critical planeis developed, estimating the fractal dimension Dfof the crack trajectories using the box-counting method, which allows for the quantification of nonlinear propagation potential beyond linear elastic fracture mechanics (LEFM). Finally, a Graph Neural Network (GNN) is designed and trained that models the structural mesh as a graph G = (V, E, Φ), where the nodes represent the physical connections and the edges represent the structural beams, enabling the iterative prediction of nodal failure probabilities and the projection of remaining useful life (RUL). Results reveal a Structural Health Index (SHI) of 52.9%, identify node 253 as having the highest failure probability (57.7%), and project imminent systemic failure risk within a 3–6 month horizon. A 60-day intervention plan is formulated, including brace replacement, controlled 30-minute post-weld heat treatment (PWHT), and 100% liquid penetrant non-destructive examination (NDE), achieving a fatigue life improvement factor of 4x relative to the as-welded condition.
The devil fish (Loricariidaefamily) is an invasive species that has spread across water bodies in several countries, where, due to its morphological, physiological, and behavioral characteristics, it has caused significant economic, social, and environmental impacts. In response to this problem, it is necessary to prevent its dispersion and to establish management, control, and eradication strategies through alternative uses of this species. In this study, the effectiveness of a bone char synthesized from devil fish bones and chemically modified with NaNO3was evaluated for Cd(II) removal from aqueous solution at pH 7 and 25 °C using batch experiments. The modified bone char exhibited a maximum adsorption capacity of 46.9 mg g-1. These results demonstrate the potential use of devil fish bones as an alternative strategy to mitigate the negative effects associated with this invasive species.
Nanoparticlesbased on Fe, Ni and Pd (Fe_100, Ni_100, Pd_100, PdFe_5050 y PdNi_5050) were synthesized via chemical reduction with NaBH4 and their catalytic activity was evaluated in the hydrodehalogenation (HDH)of diclofenac in aqueous phase in batch experiments. The results demonstrated the higher catalytic activity of Pd-based systems. Monometallic Ni_100 and Fe_100 showed low catalytic activity. In Fe_100 system, the degradation followed an oxidative pathway dependent on dissolved oxygen, in addition to significant metal leaching due to Fe0oxidation.Conversely, although PdFe_5050 proves to be highly active, the high Fe leaching limited its long-term viability. In contrast, both Pd_100 and PdNi_5050 nanoparticlesachieved complete diclofenac (DFC)dechlorination within 60 min, effectively suppressing the accumulation of chlorinated intermediates. The high efficiency of PdNi_5050 was attributed to the surface enrichment of Pd within the bimetallic system. This synergy allowed PdNi_5050 to match the activity of Pd_100, despite the lower content of the precious metal.Finally, PdNi_5050 proved to be a promising alternative, maintaining high catalytic activity and stability over 10 consecutive cycles. This, coupledwith the significant reduction in the associated material costs, positions PdNi_5050 as a promising option for HDH process.
In this study, the synthesis of iron nanoparticles was optimized using an aqueous extract of Eucalyptus grandis foliage, which was used together with iron (II) chloride tetrahydrate salt and iron (III) chloride hexahydrate salt using water as a solvent, inaddition to a basic sodium hydroxide solution. The nanoparticles were precipitated, filtered, and dried, achieving a yield of 98.99%. The synthesized nanoparticles exhibited a specific surface area of 131.90 m²/g. Their functional groups were analyzed using Fourier transform infrared spectroscopy (FTIR), and particle size was determined by transmission electron microscopy (TEM). The behavior of the synthesized nanoparticles during Hg(II) retention was evaluated and assessed. The adsorption isotherm fit the Freundlich model, typical of a heterogeneous adsorption model, with a maximum adsorption capacity for Hg(II) of 274.92 mg Hg/g of nanoparticle. The particle exhibited a good retention percentage for mercury (79.26%), and this synthesized particle reduces the need for reagents in its preparation, generates no polluting waste, and requires low energy input.
Deoxycholic acid (DCA) modified with chitosan in ionic aqueous solution created amphiphilic polymers that self-assembled. FTIR-ATR spectroscopy allowed the study of its spatial and chemical specificity by identifying C-H, O-H, and N-H vibrations in the spectral range from (2700 cm⁻¹ to 3700 cm⁻¹). The OH stretching band of water was resolved by deconvolution and Gaussian curve fitting, classifying the type of strong hydrogen bonds (~3200-3450 cm⁻¹), weak bonds, or free OH (~3550-3650 cm⁻¹). their distribution allowed us to propose 3D aggregate structures with AI-assisted modeling (MAIA), which coexist with each other through hydrophobic and van der Waals forces, governed by predictable thermodynamic principles and the influence of the synthesis method. Theirthermal stability was determined in a range of 20°C-60°C, observing structural rearrangements that formed elastic hydrogels, which changed to a rigid arrangement generating electrostatic cooperativity when the temperature increased. These studies providedinput for their use as host systems for hydrophobic molecules and other medical applications.
