Nowadays, additive manufacturing (AM) technologies have been widely used in construction, medical, military, aerospace, fashion, etc. The advantages of AM (e.g., more design freedom, no restriction on the complexity of parts, and rapid prototyping) have attracted a growing number of researchers. Increasing number of papers are published each year. Until now, thousands of review papers have already been published in the field of AM. It is, therefore, perhaps timely to perform a survey on AM review papers so as to provide an overview and guidance for readers to choose their interested reviews on some specific topics. This survey gives detailed analysis on these reviews, divides these reviews into different groups based on the AM techniques and materials used, highlights some important reviews in this area, and provides some discussions and insights.

Sound absorption is one of the important properties of porous materials such as foams and lattices. Many mathematical models in the literature are capable of modeling the acoustic properties of lattices. However, appropriate models need to be chosen for specific lattice structures on a case-by-case basis and require significant experience in acoustic modeling. This work aims to provide simplified insights into different mathematical models for the simple cubic lattice. The strut lengths and radii of the unit cells were varied, and the sound absorption properties were measured using an impedance tube. The sound absorption coefficients of the lattices generally increased and exhibited more resonant-like behavior as the strut radius increased. The Delany-Bazley (DB) model and the multi-layered micropore-cavity (MMC) model were used to simulate the acoustic properties of the lattices. The correction factors in the MMC were calculated based on empirical relations fitted using experimental data of the design geometry parameters. Results show that the DB model was able to model the sound absorption coefficients for lattice samples with porosities as low as 0.7, while the MMC with resonator theory is a more appropriate acoustics approach for lattices with porosities lower than 0.7. This work will be highly useful for materials researchers who are studying the acoustic properties of novel porous materials, as well as manufacturers of acoustic materials interested in the additive manufacturing of lattice structures for sound absorption and insulation applications.

To accelerate the optimization of selective electron-beam melting (SEBM) processing parameters, two machine learning models, Gaussian process regression, and support vector regression were applied in this work to predict the relative density of Inconel 718 from experimental data. The experimental validation indicated that the trained algorithms can precisely predict the relative density of SEBM samples. Moreover, the effects of different parameters on surface integrity, internal defects, and mechanical properties are discussed in this paper. The Inconel 718 samples with high density (>99.5%) prepared by the same SEBM energy density exhibit different mechanical properties, which are related to the existence of the unmelted powder, Laves phase, and grain structure. Finally, Inconel 718 sample with superior strength and plasticity was fabricated using the optimized processing parameters.

Biomedical magnesium (Mg) alloy with unique biodegradability and excellent biocompatibility is one of the most sought after materials in medical field for orthopedics applications. Nevertheless, the high corrosion rate and inadequate mechanical properties hinder its development. Apart from that, to obtain the best surgical result, the size and shape of the fixation implant need to be adapted to the individual case. Thus, additive manufacturing (AM) processes, such as laser powder bed fusion (LPBF), are used to overcome these issues. This work reviews the recent advancements in biodegradable Mg-based alloys prepared by LPBF for biomedical applications. The influence of feedstock features and manufacturing parameters on the formability and quality is delineated in detail. The mechanical performances, degradation behaviors, and biological behavior of the LPBF-processed parts are discussed. Furthermore, we also made some suggestions for the challenges of Mg alloys in LPBF processing and applications in biomedical.

A metal matrix composite with Inconel 718 as the base metal and yttrium oxide (Y₂O₃) as the reinforcement particles was fabricated by the laser powder bed fusion technology. This paper presents a comprehensive study on the influence of the Y₂O₃ reinforcement particles on the microstructures and mechanical properties of the heat-treated printed composite. Complex precipitates formation between the Y₂O₃ nanoparticles and the carbonitride precipitates were shown. The complex precipitates separated into individual Y₂O₃ and titanium nitride (TiN) nanoparticles after heat treatment. Nano-sized Y-Ti-O precipitates were observed after solutionization due to the release of supersaturated Y in the metal matrix. Grain refinement was also observed in the heat-treated composites due to the high number of nano-sized precipitates. After solutionizing and aging, the grain size of the Y₂O₃-reinforced sample is 28.2% and 33.9% smaller, respectively, than that of the monolithic Inconel 718 sample. This effectively reduced the segregation of Nbat the grain boundaries and thus, γ′ and γ′′ precipitates were distributed in the metal matrix more homogeneously. Combined with the increased Orowan strengthening from a significantly higher number of nano-sized precipitates and grain boundary strengthening, the composite achieved higher yield strength, and ultimate tensile strength (1099.3 MPa and 1385.5 MPa, respectively) than those of the monolithic Inconel 718 (1015.5 MPa and 1284.3 MPa, respectively).