Concrete is widely recognized for its excellent compressive strength but limited tensile resistance, which necessitates reinforcement with high-performance materials for effective structural applications. This study investigates the role of Carbon Fiber-Reinforced Polymer (CFRP) as tensile reinforcement in singly reinforced concrete sections, with emphasis on the contribution of tensile concrete to overall flexural resistance. The elastic behaviour of concrete is first examined, demonstrating stability under low stress levels and progressive deterioration caused by matrix cracking at higher stress states. To capture the structural response, a variable-angle strut model is employed for predicting the load–deflection behaviour of CFRP-reinforced beams subjected to combined flexure and shear. Numerical optimization using Box’s Complex Method is incorporated to refine the stress–strain representation and develop an improved stress diagram that realistically reflects CFRP–concrete interaction. The results highlight that tensile concrete, even after cracking, provides significant resistance through tension stiffening, while CFRP reinforcement remains effective under high load conditions. Furthermore, the optimization process reveals that a neutral axis depth of 0.75d substantially greater than conventional design recommendations, mobilizes nearly 200% additional tensile concrete. This enhanced mobilization improves flexural efficiency and overall load-bearing capacity. The findings of this study provide new insights into the synergistic behaviour of CFRP and concrete, emphasizing that tensile concrete should not be disregarded in design. The proposed framework offers a practical and reliable approach for improving the moment resistance of CFRP-reinforced sections, contributing to safer, more economical, and performance-driven structural design practices.

Additive manufacturing (AM) of high-performance alloys has gained increasing attention due to its capability to produce complex geometries with tailored properties. In this study, Inconel 625 powder is processed using the laser powder bed fusion (LPBF) AM technique to fabricate tensile specimens. The printed samples are first characterized through electron backscatter diffraction (EBSD) to investigate their microstructural features, EBSD provides grain orientations, crystallographic textures, Taylor factors, and geometrically necessary dislocation densities, all of which play a critical role in the mechanical response of the alloy. Subsequently, tensile testing is performed to obtain the corresponding stress-strain curve of the samples. Building on these experimental results, a constitutive model is developed to establish correlations between the model’s unknown parameters and the microstructural data obtained from EBSD. The novelty of this work lies in the formulation of the constitutive equation, by analyzing parameters that are traditionally treated as constants, such as hardening coefficients or strain-rate sensitivities, etc. to be expressed as functions of EBSD-derived microstructural descriptors. The aim is to simulate the tensile behavior of the LPBF-manufactured specimens with improved accuracy by directly linking mechanical performance to microstructural characteristics. Furthermore, the study explores the possibility of correlating process parameters with EBSD-derived features. If such a relationship can be identified, it would enable the prediction of mechanical behavior directly from process parameters, reducing the need for extensive experimental testing. Based on the results, the proposed model demonstrates strong predictive capability for capturing the tensile behavior of LPBF-fabricated Inconel 625 directly from microstructural features. By redefining constitutive parameters as functions of EBSD-derived descriptors, the model achieves accurate stress–strain predictions with minimal computational cost. Compared to traditional approaches, the framework reduces error in yield strength and strain hardening predictions by an anticipated margin of 5-10%, while significantly improving correlation between simulated and experimental curves.

Austenitic stainless steel AISI 316L produced by laser powder bed fusion (L-PBF) is one of the most extensively investigated alloys in additive manufacturing due to its good processability and corrosion resistance. However, its mechanical performance is strongly influenced by subsequent post-processing, particularly heat treatment and thermomechanical deformation. This work focuses on the evaluation of the compressive behavior of 316L in three different conditions: as-built, after heat treatment at 1000 °C/1 h followed by water quenching (HT2), and in comparison with conventionally manufactured bulk material. Uniaxial compression tests were carried out to obtain true stress–strain curves, which were further used as input data for numerical simulations. The simulations were performed using DEFORM software to model hot rolling with different thickness reductions (20, 40, 60, and 80 %). Both symmetric and asymmetric rolling configurations were considered to investigate the influence of deformation mode on stress distribution and strain localization. The comparison between experimental data and numerical predictions enables validation of the applied material model and provides insights into the deformation mechanisms of additively manufactured 316L stainless steel. The expected outcomes highlight the role of heat treatment in tailoring the mechanical response and demonstrate the potential of finite element methods for designing efficient rolling strategies for L-PBF materials. This approach may contribute to the development of hybrid processing routes combining additive manufacturing with conventional forming.

Fe-Mn-Ni alloys represent a core subsystem of the widely studied high-entropy Cantor alloy family and offer provide an ideal platform to explore the solidification behaviour, and the impact of elemental partitioning on the microstructural stability and properties. In this work, the microstructure and elemental segregation was systematically investigated in an equimolar FeMnNi medium entropy alloy (MEA). Samples were sectioned from as-cast 400x200x10 mm slabs to examine the microstructure, elemental behaviour and distribution as this alloy upon solidification. Melting took place in vacuumed-furnace ceramic crucible and casting was done in a heat-resistant tool steel rectangular mould. Optical and electron microscopy revealed a predominantly coarse dendritic microstructure with chemical segregation between Fe-rich dendritic cores and Mn-enriched interdendritic regions. EDS chemical mappings and EPMA analysis depicted the elemental segregation: Fe (melting point 1538 ^oC) was mostly concentrated within the coarse grains and arms of the dendrite, while Mn (melting point 1246 ^oC) was segregated towards the interdendritic structure. Ni (melting point 1455 ^oC) Ni was enriched in regions where higher concentrations of Mn were detected, i.e. interdendritic regions. The effects of the elements’ physical properties and thermodynamic parameters including the atomic size, enthalpy of mixing (∆H_mix) and electron state on segregation behaviour during solidification are discussed. The results highlight the potential of as-cast FeMnNi alloys as a model system for understanding metastability-driven deformation in medium entropy alloys, while also pointing to their promise for structural applications requiring robust ductility and toughness, particularly under cryogenic conditions.

The development of cost-effective and scalable nanofabrication techniques is crucial for advancing plasmonic biosensors based on Localized Surface Plasmon Resonance (LSPR). LSPR arises from the resonant oscillation of conduction electrons in metallic nanostructures excited by incident light, and its spectral response is highly sensitive to variations in size, shape, periodicity, and local dielectric environment. These unique optical properties make LSPR a powerful platform for label-free detection of biomolecular interactions with high sensitivity and selectivity.

Conventional nanofabrication methods such as electron-beam or focused ion beam lithography provide excellent control over nanoscale features but are often expensive, time-consuming, and limited in throughput, thereby hindering large-scale deployment. To address these challenges, we investigated colloidal lithography as a scalable and versatile bottom-up strategy to fabricate periodic arrays of plasmonic nanostructures. By exploiting the self-assembly of colloidal particles as deposition masks, we produced large-area patterns of gold nanodisks and nanoholes with tunable geometrical parameters. This approach enables reproducible control over resonance features while maintaining compatibility with low-cost and high-throughput manufacturing.

Our results demonstrate that colloidal lithography can generate plasmonic substrates with well-defined and reproducible LSPR responses, suitable for integration into biosensing platforms. The method provides a promising route toward portable, affordable, and robust sensors for applications in medical diagnostics, food safety, and environmental monitoring.

Bulk metallic glasses (BMGs) are metastable materials that lack the crystalline atomic structure of conventional metals and alloys. Owing to their amorphous structure they combine an exceptional set of properties including high hardness, elastic limit, and corrosion resistance, making them promising candidates for wear-resistant applications. However, their friction and wear behaviour especially under different loading regimes, remains yet not well understood. In this study, the tribological response of a Zr-Cu-Ni-Al BMG was evaluated against a stainless-steel counterpart using a ball-on-disc testing across loads ranging from 1 to 20 N. X-ray diffraction (XRD), confocal microscopy, profilometry, and scanning electron microscopy with energy-dispersive spectroscopy (SEM/EDS) were employed to study the structure and the morphology of the wear tracks. Friction coefficients varied between ~0. 5 and 0.9, depending on applied load. Detailed surface analysis and chemical mapping revealed significant material transfer and distinct load-dependent wear mechanisms. At low loads (1 N), wear was dominated by oxidative film formation and transfer of stainless steel into the BMG wear track. At higher loads (5-20 N), severe shear localisation and mechanical mixing promoted an adhesive wear mechanism predominantly. The findings provide new insights into the interplay between shear banding, counter body transfer, and tribochemical processes in Zr-based BMGs, highlighting both their potential and their limitations as candidate materials for tribological applications.

Current research on high-entropy alloys (HEAs) aims to reduce material costs while enhancing mechanical performance. This is primarily achieved by decreasing the proportion of expensive alloying elements and tailoring the microstructure through the controlled formation of multiple phases, particularly the coexistence of face-centered cubic (FCC) and body-centered cubic (BCC) structures. In this study, the structural and mechanical properties of the Al₀.₂₅Ti₀.₂₅CrFeNi alloy, produced by arc melting, were investigated in both the as-cast condition and after heat treatment. The microstructural evolution was characterized using scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), and X-ray diffraction (XRD), while the melting temperature was determined by differential thermal analysis (DTA). XRD measurements and structural analysis confirmed the presence of three distinct phases: one FCC phase and two BCC phases. In the as-cast state, the alloy exhibited a relatively high microhardness of 566 HV0.1, which is attributed to the significant presence of the BCC phase. To evaluate the mechanical behavior, compression tests and additional microhardness measurements were conducted. The results showed that the applied heat treatment led to a more favorable phase distribution, grain refinement, and an improved balance between strength and plastic strain. These findings highlight the potential of this alloy system for the development of cost-effective HEAs with enhanced mechanical properties, making it a strong candidate for future engineering applications.

Three-dimensional (3D) printing is an additive manufacturing process that enables the precise production of complex structures, layer by layer, with functional properties. The development of new biomaterials that could be used to produce 3D scaffolds for tissue regeneration and/or drug release systems, is nowadays a developing research field. [1,2] Biocompatibility and non-toxic properties are fundamental requirements to select the polymers to use as base matrices. However, using exclusively biopolymers often leads to poor mechanical properties. To overcome this challenge, inorganic reinforcing compounds, as hydroxyapatite, can be applied. This strategy improves both the structural and functional properties of the printed scaffolds.

In this research, an extrusion-based 3D printing was used, with a computer-controlled system, that enabled continuous deposition of the proposed bioblends, along the x-y-z axis. The studied formulations consisted of sodium alginate (5, 7.5 and 10%):hydroxyapatite (0, 2.5 and 5%) mixtures, dopped with 0.1% sulfanilamide. After printing, chemical crosslinking was performed by immersion in an aqueous calcium chloride solution.

The results showed that the addition of hidroxiapatite was fundamental to achieve a printable blend, once increase the viscosity. Mechanical properties were also enhanced and alginate and hydroxyapatite concentrations had influence on the drug release profile.

The feasibility of creating network-like three-dimensional structures using sulfanilamide-doped alginate–hydroxyapatite formulations was confirmed in our investigation. The drug release process performed better with lower alginate concentrations and more successfully with the addition of hydroxyapatite. These results show that these composite systems are promising for developing better biomaterials for use in tissue regeneration and drug delivery systems.

The demand for new processes of production, materials and applications of medication has changed significantly. In particular, there is a growing need for the development of methodologies to delivery active compounds with specific properties for patient-specific drugs with customized dosages, shapes, and release profiles. Three-dimensional bioprinting (3D) emerges as a promising technology, as it enables the creation of structures with high precision, low cost, and the potential to incorporate therapeutic agents.

In this study we developed a hydroxyapatite-based paste suitable for direct-ink-writing (DIW) 3D printing, with a view to producing relatively porous, multi-layered scaffolds that allow the incorporation of antibiotics.

The methodology adopted to obtain these structures consisted of using the 3D syringe extrusion printing technique, based on digital CAD models of varying complexity, which were subsequently rendered and adjusted with optimized printing parameters. This process allowed the creation of hydroxyapatite-based structures with controlled internal and external structure, ensuring a good mechanical stability even when doped with antibiotics. The optimization of the paste was ensured with a specific ratio: 37,5% of hydroxyapatite, 38% of sucrose, 0,5% of sodium alginate and 24% of water w/w. After printing, the scaffolds were impregnated with antibiotics and evaluated in a bacterial culture environment, one containing Escherichia coli and the other in the presence of Staphylococcus aureus, gram-negative and gram-positive microorganisms, respectively.

The results demonstrated that DIW 3D printing of the hydroxyapatite paste was successful, producing stable scaffolds that were suitable for drug solution absorption. Antibiotic impregnation was successful, as the structures exhibited activity against the tested bacteria. This approach has potential to be a promising strategy to develop controlled drug delivery systems that may assist in prevent ant treat localized infections.

Ensuring defect‐free parts in metal additive manufacturing (AM) is vital for safety‐critical components, yet it often relies on costly trial‐and‐error and slow computed‐tomography (CT) inspections. Here, we introduce a two‐stage, machine‐learning‐driven quality‐assurance framework for laser powder‐bed fusion (L‐PBF) that balances predictive modeling with rapid, vibration‐based, non‐destructive evaluation (NDE).

Stage 1: Process‐Parameter Optimization
A full‐factorial design of experiments (DoE) covering laser power, scan speed, and hatch spacing (75 successful builds) feeds a polynomial Ridge‐regression surrogate. Using nested 5‐fold cross‐validation and grid‐search tuning, the final quadratic Ridge model achieved a validation R² of 0.51 (RMSE ≈ 0.59 % density), capturing just over half of the variance in out‐of‐sample relative‐density measurements .

Stage 2: Vibration‐Based Defect Screening
Specimens are subjected to modal excitation and frequency‐response analysis (150–390 kHz), yielding 10,000 interpolated features. After in‐fold LARS feature‐selection and stability‐thresholding, three classifiers (5‐NN, SVC, and MLP) were evaluated via nested CV. The best model (MLP) attained 0.81 ± 0.08 accuracy, with true‐negative rates above 90%, but modest true‐positive recall (25–35%).

Integrated Impact
By combining proactive parameter tuning with vibration‐based NDE, the framework enables the removal of the majority of defective builds before certification and replaces hour‐long CT scans with minute‐scale vibration tests. This dual‐stream approach lays the groundwork for scalable, in‐situ quality assurance in AM, offering a path toward the real‐time monitoring and digital‐twin certification of complex parts.