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ABSTRACTFatigue life assessment of metal additive manufacturing (AM) products has remained challenging due to the uncertainty of as–built defects, heterogeneity of the microstructure, and residual stress. In the past few years, many works have been conducted to develop models in order to predict fatigue life of metal AM samples by considering the existence of AM inherent defects. This review paper addresses the main issues regarding fatigue assessment of metal AM parts by considering the effect of defects and post processing strategies. Mechanisms that are contributing to the failure of metal AM samples are categorized and discussed in detail. Several modelling approaches exist in the case of fatigue life prediction. The common fatigue models that are compatible with AM properties are thoroughly explained by discussing the previous works and highlighting their major conclusions. In addition, the use of machine learning is identified as the future of metal AM fatigue life assessment due to their high performance. The main challenge of today's fatigue and fracture community was identified as the fatigue life estimation of complex geometries with the presence of different types of defects, anisotropic microstructure, and complex state of residual stress. This work proposes the available approaches to tackle this challenge.

Although additive manufacturing technologies offer manufacturing highly complex parts, the manufactured parts generally have poor surface quality. Owing to low machinability of hard-to-cut additively manufactured parts, a synergistic approach involving advantages of additive manufacturing and machining processes is needed. This study investigates high-speed machining of additively manufactured nickel alloys using hybrid cryogenic cooling methods. For the first time, a comprehensive study has been presented to compare the synergistic effect of hybrid cooling and lubrication strategies in high-speed milling of additively manufactured parts produced with powder bed fusion and directed energy deposition. The results indicate strong dependency of machinability on additive manufacturing methods and post-treatment strategy used. Hybrid methods make high-speed machining of additively manufactured parts possible, resulting in longer tool life and better surface finish. The cooling plays more significant role on tool life than lubrication. However, it was found that the hybrid cooling methods balanced heat removal and lubrication effects.

Titanium aluminide alloys have gained attention for their lightweight and high-performance properties, particularly in aerospace and automotive applications. Traditional manufacturing methods such as casting and forging have limitations on part size and complexity, but additive manufacturing (AM), specifically electron beam melting (EBM), has overcome these challenges. However, the surface quality of AM parts is not ideal for sensitive applications, so post-processing techniques such as machining are used to improve it. The combination of AM and machining is seen as a promising solution. However, research on optimizing machining parameters and their impact on surface quality characteristics is lacking. Limited studies exist on additively manufactured TiAl alloys, necessitating further investigation into surface roughness during EBM TiAl machining and its relationship to cutting speed. As-built and heat-treated TiAl samples undergo machining at different feed rates and surface speeds. Profilometer analysis reveals worsened surface roughness in both heat-treated and non-heat-treated specimens at certain machining conditions, with higher speeds exacerbating edge cracks and material pull-outs. The hardness of the machined surfaces remains consistent within the range of 32–33.1 HRC at condition 3C (45 SFM and 0.1 mm/tooth). As-built hardness remains unchanged with increasing spindle and cutting head speeds. Conversely, heat-treated condition 3C surfaces demonstrate greater hardness than condition 1A (15 SFM, and 0.04 mm/tooth), indicating increased hardness with varying feed and surface speeds. This suggests crack formation in the as-built condition is considered to be influenced by factors beyond hardness, such as deformation-related grain refinement/strain hardening, while hardness and the existence of the α2 phase play a more significant role in heat-treated surfaces.

This research investigates the accelerated hydrolytic degradation process of both anatomically designed bone scaffolds with a pore size gradient and a rectangular shape (biomimetically designed scaffolds or bone bricks). The effect of material composition is investigated considering poly-ε-caprolactone (PCL) as the main scaffold material, reinforced with ceramics such as hydroxyapatite (HA), β-tricalcium phosphate (TCP) and bioglass at a concentration of 20 wt%. In the case of rectangular scaffolds, the effect of pore size (200 μm, 300 μm and 500 μm) is also investigated. The degradation process (accelerated degradation) was investigated during a period of 5 days in a sodium hydroxide (NaOH) medium. Degraded bone bricks and rectangular scaffolds were measured each day to evaluate the weight loss of the samples, which were also morphologically, thermally, chemically and mechanically assessed. The results show that the PCL/bioglass bone brick scaffolds exhibited faster degradation kinetics in comparison with the PCL, PCL/HA and PCL/TCP bone bricks. Furthermore, the degradation kinetics of rectangular scaffolds increased by increasing the pore size from 500 μm to 200 μm. The results also indicate that, for the same material composition, bone bricks degrade slower compared with rectangular scaffolds. The scanning electron microscopy (SEM) images show that the degradation process was faster on the external regions of the bone brick scaffolds (600 μm pore size) compared with the internal regions (200 μm pore size). The thermal gravimetric analysis (TGA) results show that the ceramic concentration remained constant throughout the degradation process, while differential scanning calorimetry (DSC) results show that all scaffolds exhibited a reduction in crystallinity (Xc), enthalpy (Δm) and melting temperature (Tm) throughout the degradation process, while the glass transition temperature (Tg) slightly increased. Finally, the compression results show that the mechanical properties decreased during the degradation process, with PCL/bioglass bone bricks and rectangular scaffolds presenting higher mechanical properties with the same design in comparison with the other materials.

Melanoma is a serious malignant skin tumor. Effectively eliminating melanoma and healing after-surgical wounds are always challenges in clinical studies. To address these problems, we propose manganese-doped calcium silicate nanowire-incorporated alginate hydrogels (named MCSA hydrogels) for in situ photothermal ablation of melanoma followed by the wound healing process. The proposed MCSA hydrogel had controllable gelation properties, reasonable strength, and excellent bioactivity due to the incorporated calcium silicate nanowires as the in situ cross-linking agents and bioactive components. The doping of manganese into calcium silicate nanowires gave them excellent photothermal effects for eradicating melanoma effectively under near infrared (NIR) irradiation. Moreover, the synergistic effect of manganese and silicon in the MCSA hydrogel effectively promotes migration and proliferation of vascular endothelial cells and promotes angiogenesis. Hence, such bifunctional bioactive hydrogels could achieve combined functions of photothermal therapy and wound healing, showing great promise for melanoma therapy and tissue regeneration.

The design of scaffolds with optimal biomechanical properties for load-bearing applications is an important topic of research. Most studies have addressed this problem by focusing on the material composition and not on the coupled effect between the material composition and the scaffold architecture. Polymer–bioglass scaffolds have been investigated due to the excellent bioactivity properties of bioglass, which release ions that activate osteogenesis. However, material preparation methods usually require the use of organic solvents that induce surface modifications on the bioglass particles, compromising the adhesion with the polymeric material thus compromising mechanical properties. In this paper, we used a simple melt blending approach to produce polycaprolactone/bioglass pellets to construct scaffolds with pore size gradient. The results show that the addition of bioglass particles improved the mechanical properties of the scaffolds and, due to the selected architecture, all scaffolds presented mechanical properties in the cortical bone region. Moreover, the addition of bioglass indicated a positive long-term effect on the biological performance of the scaffolds. The pore size gradient also induced a cell spreading gradient.

In this study, the acidity of urazole (pKa 5–6) was exploited to fabricate a hydrogel in two simple and scalable steps. Commercially available poly(hexamethylene)diisocyanate was used as a precursor to synthesize an urazole containing gel. The formation of urazole was confirmed by FT-IR and 1H-NMR spectroscopy. The hydrogel was characterized by microscopy imaging as well as spectroscopic and thermo-gravimetric analyses. Mechanical analysis and cell viability tests were performed for its initial biocompatibility evaluation. The prepared hydrogel is a highly porous hydrogel with a Young’s modulus of 0.91 MPa, has a swelling ratio of 87%, and is capable of exchanging ions in a medium. Finally, a general strategy was demonstrated to embed urazole groups directly into a crosslinked material.

This paper deals with the development of a realtime structural health monitoring system for airframe structures to localize and estimate the magnitude of the loads causing deflections to the critical components, such as wings. To this end, a framework that is based on artificial neural networks is developed where features that are extracted from a depth camera are utilized. The localization of the load is treated as a multinomial logistic classification problem and the load magnitude estimation as a logistic regression problem. The neural networks trained for classification and regression are preceded with an autoencoder, through which maximum informative data at a much smaller scale are extracted from the depth features. The effectiveness of the proposed method is validated by an experimental study performed on a composite unmanned aerial vehicle (UAV) wing subject to concentrated and distributed loads, and the results obtained by the proposed method are superior when compared with a method based on Castigliano’s theorem.

Melt electrospinning writing has been emerged as a promising technique in the field of tissue engineering, with the capability of fabricating controllable and highly ordered complex three-dimensional geometries from a wide range of polymers. This three-dimensional (3D) printing method can be used to fabricate scaffolds biomimicking extracellular matrix of replaced tissue with the required mechanical properties. However, controlled and homogeneous cell attachment on melt electrospun fibers is a challenge. The combination of melt electrospinning writing with other tissue engineering approaches, called hybrid biomanufacturing, has introduced new perspectives and increased its potential applications in tissue engineering. In this review, principles and key parameters, challenges, and opportunities of melt electrospinning writing, and particularly, recent approaches and materials in this field are introduced. Subsequently, hybrid biomanufacturing strategies are presented for improved biological and mechanical properties of the manufactured porous structures. An overview of the possible hybrid setups and applications, future perspective of hybrid processes, guidelines, and opportunities in different areas of tissue/organ engineering are also highlighted.