Search

4D printing has recently emerged as a new manufacturing paradigm by integrating shape memory materials with 3D printing technology. Distinctively, 4D printed structures exhibit dynamic shape changing capability over time in response to certain stimuli. The emerging shape memory property of 4D printed components has attracted increasing research attention due to its potential applications in soft-robotic, origami, and self-construction structures. Ensuring product durability is key to enhancing the technology diffusion of 4D printing as it significantly affects the product service life. In the current literature, durability issues in 4D printing have been largely overlooked and the relationships between external stimulus conditions and the thermo-mechanical cycle life of 4D printed parts remain unknown. To tackle this challenge, in this study, the design of experiments approach is adopted to comprehensively investigate the impacts of external stimulus conditions on the shape memory cycle life of the 4D printed thermo-responsive parts. The results suggest that increasing the operating temperature within the material-allowable temperature range would negatively affect the shape memory cycle times; meanwhile, varying the shape programming hold time also exhibits noticeable impacts on the durability of 4D printed parts. In addition, the extreme stimulus conditions with respect to the high temperature and prolonged shape programming time would worsen the shape memory cycle life.

4D printing has spurred growing interests since its recent emergence, as it enables the fabrication of dynamic structures with reconfigurability over time when exposed to external stimuli, which is not feasible using 3D printing. The current literature on 4D printing is mainly focused on developing new materials and investigating the time-evolving properties of the printed parts, whereas the influences of process parameters on stimuli-response behaviors of 4D printed parts are not adequately explored, especially under cyclic loadings. In this study, experimental analyses are conducted to investigate the effects of infill strategies and stimulus conditions on the shape memory properties of 4D printed thermo-responsive parts. Specifically, cyclic thermo-mechanical tests are performed under different operating temperatures to investigate the shape programmability and recovery characteristic of specimens printed with various infill patterns. The results indicate that specimens printed with the rectilinear pattern exhibit better shape programmability under cyclic thermo-mechanical loadings than polygonal patterns. In addition, the decrease in shape fixity ratios over multiple cycles is also observed for all considered infill patterns. The comparative studies suggest that the increase in operating temperature within the vicinity of the material’s glass transition temperature can improve the cyclic shape memory property.

The integration of additive manufacturing technologies with stimuli-responsive shape memory materials allows the dynamic self-adaptation of fabricated parts upon exposure to external stimulations. The additional dimension of time inspires the concept of four-dimensional printing technology. However, the emerging feedstock materials and the employment of external stimuli in 4D printing are also associated with new workplace hazards and occupational health concerns. Current evaluation studies on additive manufacturing are mainly focused on the safety and health effects that originated from the part production phase and cannot be directly applied in 4D printing processes. In this study, the emissions of volatile organic compounds from stereolithography-based 4D printing process with thermo-responsive materials are targeted as the potential safety concern. Real-time total volatile organic compound monitoring is conducted during various production phases to align the emission sources with critical operating activities, including both operator interventions and machine operations. Comparative experiments are performed to evaluate the effectiveness of proposed emission control strategies. In particular, alterations in operation procedures such as stirring speed in material mixing and post-printing stimulation method can contribute positively to air emission control during manual operations. In addition, the installation of activated carbon fiber filters inside the machine build chamber can lead to a significant reduction of air emissions during part fabrication with an overall total volatile organic compound concentration reduction of 58.91%.

The emergence of smart materials coupled with additive manufacturing technology has provided competitive advantages over traditional manufacturing systems in terms of manufacturing flexibility, product functionality, and the ability to switch between multiple phases under given external stimuli. Although the fabricability of shape memory materials has been widely explored in stereolithography systems, the shape memory performance of printed smart structures has not been extensively studied. More specifically, in current literature, the printing process is mainly considered independent of material characteristics, and a lack of information is reported on how the printing parameters affect the shape fixity and free recovery performance of the printed parts. Therefore, this work is dedicated to experimentally investigating the influences of parameters from both the stereolithography printing process and thermomechanical process (i.e., shape programming and free recovery) on the shape memory properties. Five parameters, including layer thickness, scan speed, maximum programmed angle, hold time, and recovery time, are experimentally analyzed for their impacts on the shape morphing capabilities. According to the results of this study, a variation of 14.33% on the free recovery ratio can be observed when the scan speed is altered. In addition, the printing process parameters exhibit high levels of dominance in affecting the shape memory performance over parameters involved in the thermomechanical process, such as hold time and maximum programmed angle.

The emergence of 4D printing has revolutionized the additive manufacturing industry by enabling dynamic shape memory effects ensured by the use of smart materials. In addition to 3D fabrication, 4D printed products need to undergo shape programming and recovery cycles to achieve desired shape memory effects. Due to the new process and material characteristics, energy consumption models established for 3D printing are no longer applicable for 4D printing. In current literature, the environmental sustainability for 4D printing has not yet been evaluated, leading to unknown environmental impacts that could be caused by 4D printing processes and/or materials. In this research, theoretical models for quantifying the energy consumption in 4D printing thermal-responsive polymers are established by jointly considering the compositional design for materials. Experiments and case studies are performed to validate the proposed models and further investigate some critical factors that can affect energy consumption, e.g., values of process parameters like layer thickness, and thermo-temporal conditions in shape memory cycles. The case study results show that overall energy consumption can be reduced by 1) increasing the concentrations of multi-functional crosslinkers in material composition, and 2) setting the shape programming and recovery temperatures as 10 to 15 ℃ above the material glass transition temperature without compromising the shape fixity and recovery ratios. In addition, by adjusting the influential parameters throughout different stages in 4D printing, the total energy consumption can be reduced by 37.33 % , which corresponds to a reduction of 259.52 pounds of CO2 emissions per kilogram methacrylate resin.

Managing waterborne and water-related diseases is one of the most critical factors in the aftermath of hurricane-induced natural disasters. The goal of the study was to identify water-quality impairments in order to set the priorities for post-hurricane relief and to guide future decisions on disaster preparation and relief administration. Field investigations were carried out on St. Thomas, U.S. Virgin Islands as soon as the disaster area became accessible after the back-to-back hurricane strikes by Irma and Maria in 2017. Water samples were collected from individual household rain cisterns, the coastal ocean, and street-surface runoffs for microbial concentration. The microbial community structure and the occurrence of potential human pathogens were investigated in samples using next generation sequencing. Loop mediated isothermal amplification was employed to detect fecal indicator bacteria, Enterococcus faecalis. The results showed both fecal indicator bacteria and Legionella genetic markers were prevalent but were low in concentration in the water samples. Among the 22 cistern samples, 86% were positive for Legionella and 82% for Escherichia-Shigella. Enterococcus faecalis was detected in over 68% of the rain cisterns and in 60% of the coastal waters (n = 20). Microbial community composition in coastal water samples was significantly different from cistern water and runoff water. Although identification at bacterial genus level is not direct evidence of human pathogens, our results suggest cistern water quality needs more organized attention for protection of human health, and that preparation and prevention measures should be taken before natural disasters strike., Graphical abstract Image 1, Highlights • Rain cistern, coastal ocean and surface runoff waters were sampled post hurricanes. • Microbial community composition was dramatically different in each type of water. • Fecal indicator bacteria and Legionella were prevalent in all water samples. • The concentrations of Legionella and fecal indicator bacteria were generally low.