Machine learning-enabled forward prediction and inverse design of 4D-printed active plates.

Shape transformations of active composites (ACs) depend on the spatial distribution of constituent materials. Voxel-level complex material distributions can be encoded by 3D printing, offering enormous freedom for possible shape-change 4D-printed ACs. However, efficiently designing the material distribution to achieve desired 3D shape changes is significantly challenging yet greatly needed. Here, we present an approach that combines machine learning (ML) with both gradient-descent (GD) and evolutionary algorithm (EA) to design AC plates with 3D shape changes. A residual network ML model is developed for the forward shape prediction. A global-subdomain design strategy with ML-GD and ML-EA is then used for the inverse material-distribution design. For a variety of numerically generated target shapes, both ML-GD and ML-EA demonstrate high efficiency. By further combining ML-EA with a normal distance-based loss function, optimized designs are achieved for multiple irregular target shapes. Our approach thus provides a highly efficient tool for the design of 4D-printed active composites.

Chemical Circularity in 3D Printing with Biobased Δ-Valerolactone.

Digital Light Processing (DLP) is a vat photopolymerization-based 3D printing technology that fabricates parts typically made of chemically crosslinked polymers. The rapidly growing DLP market has an increasing demand for polymer raw materials, along with growing environmental concerns. Therefore, circular DLP printing with a closed-loop recyclable ink is of great importance for sustainability. The low-ceiling temperature alkyl-substituted δ-valerolactone (VL) is an industrially accessible biorenewable feedstock for developing recyclable polymers. In this work, acrylate-functionalized poly(δ-valerolactone) (PVLA), synthesized through the ring-opening transesterification polymerization of VL, is used as a platform photoprecursor to improve the chemical circularity in DLP printing. A small portion of photocurable reactive diluent (RD) turns the unprintable PVLA into DLP printable ink. Various photocurable monomers can serve as RDs to modulate the properties of printed structures for applications like sacrificial molds, soft actuators, sensors, etc. The intrinsic depolymerizability of PVLA is well preserved, regardless of whether the printed polymer is a thermoplastic or thermoset. The recovery yield of virgin quality VL monomer is 93% through direct bulk thermolysis of the printed structures. This work proposes the utilization of depolymerizable photoprecursors and highlights the feasibility of biorenewable VL as a versatile material platform toward circular DLP printing.

Low-temperature 3D printing of transparent silica glass microstructures.

Transparent silica glass is one of the most essential materials used in society and industry, owing to its exceptional optical, thermal, and chemical properties. However, glass is extremely difficult to shape, especially into complex and miniaturized structures. Recent advances in three-dimensional (3D) printing have allowed for the creation of glass structures, but these methods involve time-consuming and high-temperature processes. Here, we report a photochemistry-based strategy for making glass structures of micrometer size under mild conditions. Our technique uses a photocurable polydimethylsiloxane resin that is 3D printed into complex structures and converted to silica glass via deep ultraviolet (DUV) irradiation in an ozone environment. The unique DUV-ozone conversion process for silica microstructures is low temperature (~220°C) and fast (<5 hours). The printed silica glass is highly transparent with smooth surface, comparable to commercial fused silica glass. This work enables the creation of arbitrary structures in silica glass through photochemistry and opens opportunities in unexplored territories for glass processing techniques.

Cold-programmed shape-morphing structures based on grayscale digital light processing 4D printing.

Shape-morphing structures that can reconfigure their shape to adapt to diverse tasks are highly desirable for intelligent machines in many interdisciplinary fields. Shape memory polymers are one of the most widely used stimuli-responsive materials, especially in 3D/4D printing, for fabricating shape-morphing systems. They typically go through a hot-programming step to obtain the shape-morphing capability, which possesses limited freedom of reconfigurability. Cold-programming, which directly deforms the structure into a temporary shape without increasing the temperature, is simple and more versatile but has stringent requirements on material properties. Here, we introduce grayscale digital light processing (g-DLP) based 3D printing as a simple and effective platform for fabricating shape-morphing structures with cold-programming capabilities. With the multimaterial-like printing capability of g-DLP, we develop heterogeneous hinge modules that can be cold-programmed by simply stretching at room temperature. Different configurations can be encoded during 3D printing with the variable distribution and direction of the modular-designed hinges. The hinge module allows controllable independent morphing enabled by cold programming. By leveraging the multimaterial-like printing capability, multi-shape morphing structures are presented. The g-DLP printing with cold-programming morphing strategy demonstrates enormous potential in the design and fabrication of shape-morphing structures.

One-Pot Synthesis of Depolymerizable δ-Lactone Based Vitrimers.

A depolymerizable vitrimer that allows both reprocessability and monomer recovery by a simple and scalable one-pot two-step synthesis of vitrimers from cyclic lactones is reported. Biobased δ-valerolactone with alkyl substituents (δ-lactone) has low ceiling temperature; thus, their ring-opening-polymerized aliphatic polyesters are capable of depolymerizing back to monomers. In this work, the amorphous poly(δ-lactone) is solidified into an elastomer (i.e., δ-lactone vitrimer) by a vinyl ether cross-linker with dynamic acetal linkages, giving the merits of reprocessing and healing. Thermolysis of the bulk δ-lactone vitrimer at 200 °C can recover 85-90 wt% of the material, allowing reuse without losing value and achieving a successful closed-loop life cycle. It further demonstrates that the new vitrimer has excellent properties, with the potential to serve as a biobased and sustainable replacement of conventional soft elastomers for various applications such as lenses, mold materials, soft robots, and microfluidic devices.

Single-vat single-cure grayscale digital light processing 3D printing of materials with large property difference and high stretchability.

Multimaterial additive manufacturing has important applications in various emerging fields. However, it is very challenging due to material and printing technology limitations. Here, we present a resin design strategy that can be used for single-vat single-cure grayscale digital light processing (g-DLP) 3D printing where light intensity can locally control the conversion of monomers to form from a highly stretchable soft organogel to a stiff thermoset within in a single layer of printing. The high modulus contrast and high stretchability can be realized simultaneously in a monolithic structure at a high printing speed (z-direction height 1 mm/min). We further demonstrate that the capability can enable previously unachievable or hard-to-achieve 3D printed structures for biomimetic designs, inflatable soft robots and actuators, and soft stretchable electronics. This resin design strategy thus provides a material solution in multimaterial additive manufacture for a variety of emerging applications.

Stacking nuances modulate the mechanical properties of graphene/SnO2nanocomposites.

Due to its superior mechanical properties, graphene is widely used as reinforcement materials in nanocomposites. In this work, a series of indentation simulations was performed, using finite element method, to investigate the mechanical properties of graphene/TiO2and graphene/SnO2nanocomposite films. The force-displacement curves obtained from simulations were first compared to analytical results, which demonstrates that with increasing the thicknesses of metal oxide layers, the mechanical responses of nanocomposites exhibit a transition from non-linear behaviors to linear behaviors. Furthermore, consistent with literature works, increasing graphene volume fraction can enhance the Young's modulus of the corresponding heterostructure. Interestingly, this enhancement can be modulated by nuances in stacking orders, i.e. layer arrangements, of nanocomposites. Through analyzing stress and strain distributions, the underlying mechanisms were proposed. Our results reported here provide comprehensive characterizations and understandings on the reinforcement effects of graphene on graphene/metal oxide nanocomposites.