Characterization and parametric optimization of additive manufacturing process for enhancing mechanical properties

Optimization of the removal efficiency of three biodegradable chelating agents for soil cadmium

In recent years, there has been a significant increase in the release of cadmium-containing pollutants into the environment from mining, industrial emissions, wastewater irrigation and the use of chemical fertilizers and pesticides. This leads to the degradation of soil quality and poses a threat to human health. Chemical leaching remediation technology is an effective method for controlling Cd contamination in soil. However, the leaching agent has a low removal efficiency of heavy metals. In order to find more suitable environmentally friendly new leaching agents, this study investigates the effects of three biodegradable chelating agents PMAS, EDTMPS and GLDA on the removal of heavy metal Cd in soil in the single factor soil leaching experiment. The concentration of the chelating agents, the leaching time and the pH of the leaching solution were varied to study their effects. The Box-Behnken (BBD) effect based on RSM was used to design the experimental conditions to optimize the leaching process of three biodegradable chelating agents. The optimum conditions for Cd removal by PMAS, EDTMPS and GLDA were obtained as follows: concentration 7 %, pH = 3.61, reaction time 180 min; concentration 4.94 %, pH = 3.0, reaction time 180 min; and concentration 4.96 %, pH = 3.0, reaction time 180 min. The validation test results showed that the deviation from the experimental value is less than 3 % under the theoretically optimal washing conditions, confirming the reliability and accuracy of the response surface methodology optimization process, which provides a reference for the development of efficient, environmentally friendly and low-cost leaching agents.

3D printed biomedical devices and their applications: A review on state-of-the-art technologies, existing challenges, and future perspectives

3D printing, also known as Additive manufacturing (AM), has emerged as a transformative technology with applications across various industries, including the medical sector. This review paper provides an overview of the current status of AM technology, its challenges, and its application in the medical industry. The paper covers the different types of AM technologies, such as fused deposition modeling, stereolithography, selective laser sintering, digital light processing, binder jetting, and electron beam melting, and their suitability for medical applications. The most commonly used biomedical materials in AM, such as plastic, metal, ceramic, composite, and bio-inks, are also viewed. The challenges of AM technology, such as material selection, accuracy, precision, regulatory compliance, cost and quality control, and standardization, are also discussed. The review also highlights the various applications of AM in the medical sector, including the production of patient-specific surgical guides, prosthetics, orthotics, and implants. Finally, the review highlights the Internet of Medical Things (IoMT) and artificial intelligence (AI) for regulatory frameworks and safety standards for 3D-printed biomedical devices. The review concludes that AM technology can transform the healthcare industry by enabling patients to access more personalized and reasonably priced treatment alternatives. Despite the challenges, integrating AI and IoMT with 3D printing technology is expected to play a vital role in the future of biomedical device applications, leading to further advancements and improvements in patient care. More research is needed to address the challenges and optimize its use for medical applications to utilize AM's potential in the medical industry fully.

Optimizing fused filament fabrication process parameters for quality enhancement of PA12 parts using numerical modeling and taguchi method

Fused Filament Fabrication (FFF) is an Additive Manufacturing (AM) technique implemented in widespread applications and several components. Despite its benefits, the physics behind the FFF process is quite complicated and requires fast heating and cooling rate of the extruded material. Consequently, the component experiences extremely non-uniform internal stresses that might lead to warpage deformation. It is necessary to optimize the printing parameters as they are associated with the warpage deformation of printed components. One method for achieving this target is conducting physical tests that offer precise findings, but it is an expensive strategy. Another approach is to simulate the printing parameters with special software. In this work, Digimat-AM was employed to develop a thermomechanical Finite Element Model of the FFF to simulate parts made of Polyamide12 (PA12). An L27 orthogonal array, a tool of the Taguchi orthogonal array, and an analysis of variance (ANOVA) were used to estimate the impact of five printing parameters and their ultimate levels to improve the dimension's quality by minimizing the warpage deformation. Results showed a significant impact of the bed temperature on the warpage deformation values. The infill density contributed 2.84% in reducing the warpage deformation, and the rest of the parameters' contribution was less than 1% for each.

3D Printable Drug Delivery Systems: Next-generation Healthcare Technology and Regulatory Aspects

A revolutionary shift in healthcare has been sparked by the development of 3D printing, propelling us into an era replete with boundless opportunities for personalized DDS (Drug Delivery Systems). Precise control of the kinetics of drug release can be achieved through 3D printing, improving treatment efficacy and patient compliance. Additionally, 3D printing facilitates the co-administration of multiple drugs, simplifying treatment regimens. The technology offers rapid prototyping and manufacturing capabilities, reducing development timelines and costs. The seamless integration of advanced algorithms and artificial neural networks (ANN) augments the precision and efficacy of 3D printing, propelling us toward the forefront of personalized medicine. This comprehensive review delves into the regulatory frontiers governing 3D printable drug delivery systems, with an emphasis on adhering to rigorous safety protocols to ensure the well-being of patients by leveraging the latest advancements in 3D printing technologies powered by artificial intelligence. The paradigm promises superior therapeutic outcomes and optimized medication experiences and sets the stage for an immersive future within the Metaverse, wherein healthcare seamlessly converges with virtual environments to unlock unparalleled possibilities for personalized treatments.