In the past decades, there has been a significant increase in the use of polymers for biomedical applications. The global medical polymer market size was valued at USD 19.92 billion in 2022 and is expected to grow at a CAGR of 8.0% from 2023 to 2030 despite some limitations, such as cost (financial limitation), strength compared to metal plates for bone fracture, design optimization and incorporation of reinforcement. Recently, this increase has been more pronounced due to important advances in synthesis and modification techniques for the design of novel biomaterials and their behavior in vitro and in vivo. Also, modern medicine allows the use of less invasive surgeries and faster surgical sutures. Besides their use in the human body, polymer biomedical materials must have desired physical, chemical, biological, biomechanical, and degradation properties. This review summarizes the use of polymers for biomedical applications, mainly focusing on hard and soft tissues, prosthetic limbs, dental applications, and bone fracture repair. The main properties, gaps, and trends are discussed.

High‐performance fiber‐reinforced thermoset composites processed by additive manufacturing (3D printing) are attracting substantial attention in both academic and industrial fields in a market currently dominated by thermoplastic matrices. Thermoset polymers have, nevertheless, several advantages over thermoplastic ones. This study aims at recommending suitable fibers and processing conditions that effectively improve the mechanical properties of thermoset composites produced by additive manufacturing. The influence of void content is also highlighted. A systematic review is performed here using the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (P.R.I.S.M.A.) protocol as a guide aiming to identify the main findings recently studied. A total of 147 studies are initially identified within 2014–2020 using three scientific databases. Then, 29 articles are selected and described respecting several inclusion and exclusion criteria. The main findings are presented and discussed, and the gaps are identified to open up further investigations yet to be understood and exploited.

The effects of processing parameters on conventional molding techniques are well-known. However, the fabrication of a carbon fibre (CF)/epoxy composite via additive manufacturing (AM) is in the early development stages relative to fabrications based on resin infusion. Accordingly, we introduce predictions of the flexural strength, modulus, and strain for high-performance 3D printable CF/epoxy composites. The data prediction is analyzed using approaches based on an artificial neural network, analysis of variance, and a response surface methodology. The predicted results present high reliability and low error level, getting closer to experimental results. Different input data can be included in the system with the trained neural network, allowing for the prediction of different output parameters. The following factors that influence the AM composite processing were considered: vacuum pressure, printing speed, curing temperature, printing space, and thickness. We further demonstrate fast and streamlined fabrications of various composite materials with tailor-made properties, as the influence of each processing parameter on the desirable properties.

The environmental and social concerns regarding environmental‐friendly materials lead to alternatives in replacing synthetic fibers for natural ones on polymeric composites. This study focused on modeling dynamic mechanical curves of kenaf/polyester composites using response surface methodology (RSM). Composites with three different reinforcement contents (13.5, 22.33, and 36.27 vol%) were produced and subjected to the dynamic mechanical analysis (DMTA). From the experimental DMTA curves, a 3D surface plot using RSM was done. The results showed that the fiber dynamic mechanical behavior and fiber/matrix interface had a low influence on the glass transition temperature but significantly changed the tan δ peak height. On the other hand, the kenaf fibers presented an enormous difference in the elastomeric region. The constrained region (calculated using the tan delta height) increased ~4 times for the composite reinforced with 36.27 vol% when compared to the composite reinforced with 13.5 vol%. The RSM enabled the viscoelastic modeling using different fiber volumes with high reliability and low error (R² > 0.99). The RSM approach proved to be an intelligent and reliable technique to access a higher range of results, reducing experimental time and cost and keeping statistical significance. Also, the present methodology can be extended to model other properties and/or optimize parameters.