Enhancing mechanical properties of environmentally friendly and renewable polymers by the introduction of natural fibers not only paves the way for developing sustainable composites but also enables new opportunities in advanced additive manufacturing (AM). In this paper, wood fibers, as a versatile renewable resource of cellulose, are integrated within bio-based polylactic acid (PLA) polymer for the development and 3D printing of sustainable and recycle green composites using fused deposition modeling (FDM) technology. The 3D-printed composites are comprehensively characterized to understand critical materials properties, including density, porosity, microstructures, tensile modulus, and ultimate strength. Non-contact digital image correlation (DIC) technology is employed to understand local stress and strain concentration during mechanical testing. The validated FDB-based AM process is employed to print honeycombs, woven bowls, and frame bins to demonstrate the manufacturing capability. The performance of 3D-printed honeycombs is tested under compressive loads with DIC to fully evaluate the mechanical performance and failure mechanism of ultra-light honeycomb structures. The research outcomes can be used to guide the design and optimization of AM-processed composite structures in a broad range of engineering applications.

Metal additive manufacturing (AM) has grown in recent years to supplement or even replace traditional fabrication methods. Specifically, the laser powder bed fusion (LPBF) process has been used to manufacture components in support of sustainment issues, where obsolete components are hard to procure. While LPBF can be used to solve these issues, much work is still required to fully understand the metal AM technology to determine its usefulness as a reliable manufacturing process. Due to the complex physical mechanisms involved in the multiscale problem of LPBF, repeatability is often difficult to achieve and consequently makes meeting qualification requirements challenging. The purpose of this work is to provide a review of the physics of metal AM at the melt pool and part scales, thermomechanical simulation methods, as well as the available commercial software used for finite element analysis and computational fluid dynamics modeling. In addition, metal AM process qualification frameworks are briefly discussed in the context of the computational basis established in this work.

This paper presents the additive manufacturing and characterization of nanoparticle-reinforced photocurable resin-based nanocomposites with a potential antimicrobial function for improved public health applications. Two types of photocurable resins are reinforced by titanium dioxide (TiO₂) or zinc oxide (ZnO) nanoparticles with average diameters in the 10–30 nm range to provide antimicrobial properties. The developed nanocomposites can be additively manufactured using the digital light processing method with an outstanding surface quality and precise geometrical accuracy. Experimental characterizations are conducted to investigate key mechanical properties of the 3D printed nanocomposites, including Young’s Modulus, tensile strength, and abrasion resistance. Specimens produced were observed to demonstrate the following characteristics during testing. Tensile strength increased by 42.2% at a maximum value of 29.53 MPa. The modulus of elasticity increased by 14.3%, and abrasion resistance increased by 15.8%. The proper dispersion of the nanoparticles within the cured resin is validated by scanning electron images. The wettability and water absorption testing results indicate that the developed nanocomposites have an outstanding water resistance capability. The pairing of digital light processing with these novel nanocomposites allows for the creation of complex composite geometries that are not capable through other manufacturing processes. Therefore, they have the potential for long-term usage to improve general public health with antimicrobial functionality. The pairing of an unmodified photocurable resin with a 1% ZnO concentration demonstrated the most promise for commercial applications.

The development of novel embedded sensors for structural health monitoring (SHM) is crucial to provide real-time assessments of composite structures, ensuring safety, and prolonging their service life. Early damage diagnostics through advanced sensors can lead to timely maintenance, reducing costs and preventing potential catastrophic failures. This paper presents the synthesis, 3D printing, and characterization of novel embedded strain sensors using multi-walled carbon nanotube (MWCNT) -enhanced nanocomposites in fiberglass reinforced composites for potential damage diagnostics and SHM applications. MWCNTs are dispersed within structural epoxy for the additive manufacturing of nanocomposites with piezoresistive sensing capability. The 3D-printed nanocomposite sensors are embedded in fiberglass-reinforced composite laminates. The piezoresistive sensing capabilities of the 3D-printed sensors within composites are characterized by applying different levels of maximum loads and load rates under three-point bending loads. Additionally, the long-term reliability of the developed strain sensors is evaluated up to 1000 cycles. The recorded piezoresistive sensing signals show high sensitivity for the externally applied bending loads with advanced gauge factor up to 100, resulting in potential load sensing capability for in-situ damage diagnostics and real-time SHM for structural composites.

Vat photopolymerization-based additive manufacturing (AM) is critical in improving solutions for wearable sensors. The ability to add nanoparticles to increase the polymer resin’s mechanical, electrical, and chemical properties creates a strong proposition for investigating custom nanocomposites for the medical field. This work uses a low-cost biocompatible polymer resin enhanced with multi-walled carbon nanotubes (MWCNTs), and a digital light processing-based AM system to develop accurate strain sensors. These sensors demonstrate the ability to carry a 244% maximum strain while lasting hundreds of cycles without degradation at lower strain ranges. In addition, the printing process allows for detailed prints to be accomplished at a sub-30 micron spatial resolution while also assisting alignment of the MWCNTs in the printing plane. Moreover, high-magnification imagery demonstrates uniform MWCNT dispersion by utilizing planetary shear mixing and identifying MWCNT pullout at fracture locations. Finally, the proposed nanocomposite is used to print customized and wearable strain sensors for finger motion monitoring and can detect different amounts of flexion and extension. The 3D printed nanocomposite sensors demonstrate characteristics that make it a strong candidate for the applications of human kinematics monitoring and sensing.

Additive manufacturing has enabled the fabrication of complex, bioinspired lattice structures, such as Triply Periodic Minimal Surfaces (TPMSs), for use in lightweight structural applications. To assess their engineering viability, this study benchmarks the compressive properties of isotropic Gyroid and Primitive TPMS lattices against those of the conventional, anisotropic Honeycomb structure, which is widely used in the aerospace industry. We employed a combined computational and experimental approach, using Finite Element Analysis (FEA) for initial evaluation followed by mechanical compression testing of stereolithography (SLA)-printed polymer samples. Full-field strain was measured using Digital Image Correlation (DIC) to validate the simulations. The results show that the Gyroid has a strength-to-density of 5.692, the Primitive has a ratio of 5.182, the Honeycomb in the axial direction has a ratio of 26.144, and the Honeycomb in the transverse direction has a ratio of 1.008, all in units of $\mathrm{N}·{\mathrm{k}\mathrm{g}}^{-1}{\mathrm{m}}^3$. These results clearly indicate that the Honeycomb is best when uniaxially loaded. For other applications where the load paths will vary in multiple directions, the Gyroid is the better option.