Sustainable 3D Printing of Recyclable Biocomposite Empowered by Flash Graphene.

Sustainability of 3D printing can be reflected in three main aspects: deployment of renewable inks, recycling of printed products, and applications for energy- and materials- savings. In this work, we demonstrated sustainable vat-photopolymerization (VPP)-based 3D printing in a whole life-cycle process by developing a renewable ink made of soybean oil and natural polyphenols and recycling the ink for reprinting or converting printed biocomposite to flash graphene (FG) as reinforcing nanofillers in the biocomposite. We also realized its applications in fabricating lightweight, materials-saving 3D structures, acoustic metamaterials, and disposable microreactors for time-saving and efficiency-improving synthesis of metal-organic framework nanostructures. In addition to enhancing the tensile strength and Young's modulus of the biopolymers by 42% and 232% with only 0.6 wt % FG nanofillers, respectively, FG improved the printability of the ink in forming 3D tubular structures, which are usually very hard to be achieved in transparent resin. Success of this work will inspire further development for sustainability in 3D printing.

A unified approach for topology optimization with local stress constraints considering various failure criteria: von Mises, Drucker-Prager, Tresca, Mohr-Coulomb, Bresler- Pister and Willam-Warnke.

An interesting, yet challenging problem in topology optimization consists of finding the lightest structure that is able to withstand a given set of applied loads without experiencing local material failure. Most studies consider material failure via the von Mises criterion, which is designed for ductile materials. To extend the range of applications to structures made of a variety of different materials, we introduce a unified yield function that is able to represent several classical failure criteria including von Mises, Drucker-Prager, Tresca, Mohr-Coulomb, Bresler-Pister and Willam-Warnke, and use it to solve topology optimization problems with local stress constraints. The unified yield function not only represents the classical criteria, but also provides a smooth representation of the Tresca and the Mohr-Coulomb criteria-an attribute that is desired when using gradient-based optimization algorithms. The present framework has been built so that it can be extended to failure criteria other than the ones addressed in this investigation. We present numerical examples to illustrate how the unified yield function can be used to obtain different designs, under prescribed loading or design-dependent loading (e.g. self-weight), depending on the chosen failure criterion.