The potential of laser-based powder bed fusion (L-PBF) technology for producing functional components relies on its capability of maintaining or even improving the mechanical properties of the processed material. This improvement is associated with the microstructure resulting from the high thermal gradient and fast cooling rate. However, this microstructural advantage may be counterbalanced by the lack of full density, which could be tolerated to a certain degree for applications such as biomedical implants and medical equipment. In this study, medical-grade 316L stainless steel specimens with porosities ranging from 1.7 to 9.1% were additively manufactured by L-PBF using different combinations of laser power and scanning speeds. Tribological properties were evaluated by pin-on-disc testing in dry conditions against a silicon nitride test body and analyzed in the context of microstructural characterization by optical and electron microscopy. The results reveal that higher porosity allows for a diminishing wear rate, which is explained by the capacity of the pores to retain wear debris related with the three-body abrasion. This research provides practical insights into the design of medical wear-resistant components, thereby enhancing our understanding of the potential of L-PBF in the fields of materials science and biomedical engineering.

Additive manufacturing has evolved from a rapid prototyping technology to a technology with the ability to produce highly complex parts with superior mechanical properties than those obtained conventionally. The processing of metallic powders by means of a laser makes it possible to process any type of alloy and even metal matrix composites. The present work analyzes the tensile and compressive response of 316L stainless steel processed by laser-based powder bed fusion. The resulting microstructure was evaluated by optical microscopy. Regarding the mechanical properties, the yield strength, ultimate tensile strength, percentage of elongation before breakage, compressive strength and microhardness were determined. The results show that the microstructure is constituted by stacked micro molten pools, within which cellular sub-grains are formed due to the high thermal gradient and solidification rate. The compressive strength (1511.88 ± 9.22 MPa) is higher than the tensile strength (634.80 ± 11.62 MPa). This difference is mainly associated with strain hardening and the presence of residual stresses. The initial microhardness was 206.24 ± 11.96 HV; after the compression test, the hardness increased by 23%.

Glass fiber reinforced polymers (GFRPs) have drawn significant attention given their lightweight, mechanical resistance and tunable properties through constituent selection. Due to environmental concerns, research efforts have focused on incorporating sustainable materials, such as bio-epoxy resins, to reduce the ecological impact of GFRPs. This study characterizes a GFRP containing a bio-epoxy resin matrix, various loadings of titanium dioxide (TiO₂) nanoparticles, and a stabilized arrangement of glass fiber. The unreinforced composite exhibited a tensile strength and modulus of 214 MPa, and 13 GPa, respectively, and a flexural strength and modulus of 375 MPa and 14.5 GPa, respectively. The addition of TiO₂ produced an improvement in mechanical response for all the composites. The formulation with 1 wt.% TiO₂ showed the best tensile response with an improvement of 13% and 14% for its tensile strength, and modulus, respectively; meanwhile, the composites with 2 wt.% TiO₂ attained an improvement of 19% and 40% for the flexural strength and modulus, respectively. Scanning electron microscopy (SEM) revealed significant changes in the fracture mechanism of the composites, while energy-dispersive spectroscopy (EDS) confirmed an even nanoparticle distribution. Additionally, machine learning (ML) models were developed to predict the mechanical response as a function of the TiO₂ content.

Polymer matrix composites have become one of the most developed materials due to the possibility of tailored mechanical, physical, or thermal properties. However, important environmental concerns have arisen within conventional thermoset polymers due to the depletion of the non-renewable resources used in their production. For this reason, bio-epoxy resins have been developed by replacing a fraction of the petroleum-based components with renewable materials. In addition, machine learning algorithms have become a powerful tool to estimate material properties in nanocomposites, which might be further corroborated by experimental means. Therefore, this study developed a composite material with a bio-epoxy resin matrix reinforced with graphene oxide (GO). Experimental and theoretical densities revealed a linear relationship between the GO loading and the pore volume fraction of the composites. An estimation of various mechanical properties is listed for a bio-epoxy resin: ultimate tensile strength (UTS) (63.4 MPa), modulus of elasticity (2.74 GPa), flexural strength (95.32 MPa), and flexural modulus of elasticity (2.52 GPa). Composites including 0.1, 0.3, and 0.5 wt. % showed an improvement in the aforementioned properties, while the composites, including 0.8 and 1.2 wt. % exhibit a decrease in the overall mechanical response. Evaluation of tensile and flexural fracture surfaces revealed a noticeable strengthening mechanism in the composites after the addition of the reinforcement. Differential scanning calorimetry results demonstrated increased glass transition temperature as the GO filler loading increased. Machine learning allows the prediction of the UTS as a function of GO content with high accuracy.

Graphene oxide (GO) has garnered significant interest due to its exceptional and tunable properties, which make it a promising candidate for a wide range of engineering applications, including composite material fabrication and water treatment. In this study, GO was synthesized from graphite flakes using a modified Hummers method involving a reduced amount of sulfuric acid. The resulting material was characterized using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS). These techniques enabled a clear differentiation between the morphology of the synthesized GO and that of the original graphite. The GO exhibited a substantially altered structure, with increased thickness likely due to the incorporation of oxygen-containing functional groups on its basal plane. FTIR analysis confirmed the presence of characteristic functional groups such as hydroxyl, carbonyl, and carboxyl. XPS analysis revealed that the elemental composition of the synthesized GO consisted of approximately 69.7% carbon and 29.9% oxygen, with a trace amount of sulfur attributed to the reagents used in the synthesis. The observed changes in morphology and composition suggest the successful synthesis of GO with potential for functionalization and application in diverse engineering contexts.