The creation of reversibly-actuating components that alter their shapes in a controllable manner in response to environmental stimuli is a grand challenge in active materials, structures, and ...robotics. Here we demonstrate a new reversible shape-changing component design concept enabled by 3D printing two stimuli responsive polymers-shape memory polymers and hydrogels-in prescribed 3D architectures. This approach uses the swelling of a hydrogel as the driving force for the shape change, and the temperature-dependent modulus of a shape memory polymer to regulate the time of such shape change. Controlling the temperature and aqueous environment allows switching between two stable configurations - the structures are relatively stiff and can carry load in each - without any mechanical loading and unloading. Specific shape changing scenarios, e.g., based on bending, or twisting in prescribed directions, are enabled via the controlled interplay between the active materials and the 3D printed architectures. The physical phenomena are complex and nonintuitive, and so to help understand the interplay of geometric, material, and environmental stimuli parameters we develop 3D nonlinear finite element models. Finally, we create several 2D and 3D shape changing components that demonstrate the role of key parameters and illustrate the broad application potential of the proposed approach.
Active composites consisting of materials that respond differently to environmental stimuli can transform their shapes. Integrating active composites and 4D printing allows the printed structure to ...have a pre‐designed complex material or property distribution on numerous small voxels, offering enormous design flexibility. However, this tremendous design space also poses a challenge in efficiently finding appropriate designs to achieve a target shape change. Here, a novel machine learning (ML) and evolutionary algorithm (EA) based approach is presented to guide the design process. Inspired by the beam deformation characteristics, a recurrent neural network (RNN) based ML model whose training dataset is acquired by finite element simulations is developed for the forward shape‐change prediction. EA empowered with ML is then used to solve the inverse problem of finding the optimal design. For multiple target shapes with different complexities, the ML‐EA approach demonstrates high efficiency. Combining the ML‐EA with computer vision algorithms, a new paradigm is presented that streamlines design and 4D printing process where active straight beams can be designed based on hand‐drawn lines and be 4D printed that transform into the drawn profiles under the stimulus. The approach thus provides a highly efficient tool for the design of 4D‐printed active composites.
The machine learning empowered evolutionary algorithm approach enables an efficient design method for complicated shape changes in 4D printing, which further permits a new paradigm that streamlines conceptual design and fabrication of 4D‐printed active beams with shape changes based on hand‐drawn lines.
Abstract
4D printing of liquid crystal elastomers (LCEs) via direct ink writing has opened up great opportunities to create stimuli‐responsive actuations for applications such as soft robotics. ...However, most 4D‐printed LCEs are limited to thermal actuation and fixed shape morphing, posing a challenge for achieving multiple programmable functionalities and reprogrammability. Here, a 4D‐printable photochromic titanium‐based nanocrystal (TiNC)/LCE composite ink is developed, which enables the reprogrammable photochromism and photoactuation of a single 4D‐printed architecture. The printed TiNC/LCE composite exhibits reversible color‐switching between white and black in response to ultraviolet (UV) irradiation and oxygen exposure. Upon near‐infrared (NIR) irradiation, the UV‐irradiated region can undergo photothermal actuation, allowing for robust grasping and weightlifting. By precisely controlling the structural design and the light irradiation, the single 4D‐printed TiNC/LCE object can be globally or locally programmed, erased, and reprogrammed to achieve desirable photocontrollable color patterns and 3D structure constructions, such as barcode patterns and origami‐ and kirigami‐inspired structures. This work provides a novel concept for designing and engineering adaptive structures with unique and tunable multifunctionalities, which have potential applications in biomimetic soft robotics, smart construction engineering, camouflage, multilevel information storage, etc.
► A multibranch finite deformation thermomechanical model was developed for SMP. ► The number of material parameters was significantly reduced. ► Model simulation comparison with thermomechanical ...experiments showed good agreement. ► The model was utilized to study the intrinsic recovery behavior of an SMP. ► Size effect on recovery rate of SMP composite with magneto-particles was studied.
Shape memory polymers (SMPs) are materials that can recover a large pre-deformed shape in response to environmental stimuli. For a thermally activated amorphous SMP, the pre-deformation and recovery of the shape require the SMP to traverse its glass transition temperature (
T
g
) to complete the shape memory (SM) cycle. As a result, the recovery behavior of SMPs shows strong dependency on both the pre-deforming temperature and recovery temperature. Generally, to capture the multitude of relaxation processes, multi-branch models (similar to the 1D generalized viscoelastic model or Prony series) are used to model the time-dependent behaviors of polymers. This approach often requires an arbitrary (usually numerous) number of branches to capture the material behavior, which results in a substantial number of material parameters. In this paper, a multi-branch model is developed to capture the SM effect by considering the complex thermomechanical properties of amorphous SMPs as the temperature crosses
T
g
. The model utilizes two sets of nonequilibrium branches for fundamentally different modes of relaxation: the glassy mode and Rouse modes. This leads to a significant reduction in the number of material parameters. Model simulation comparisons with a range of thermomechanical experiments conducted on a
tert-butyl acrylate-based SMP show very good agreement. The model is further utilized to explore the intrinsic recovery behavior of an SMP and the size effects on the free recovery characteristics of a magneto-sensitive SMP composite.
Shape‐morphing magnetic soft materials, composed of magnetic particles in a soft polymer matrix, can transform shape reversibly, remotely, and rapidly, finding diverse applications in actuators, soft ...robotics, and biomedical devices. To achieve on‐demand and sophisticated shape morphing, the manufacture of structures with complex geometry and magnetization distribution is highly desired. Here, a magnetic dynamic polymer (MDP) composite composed of hard‐magnetic microparticles in a dynamic polymer network with thermally responsive reversible linkages, which permits functionalities including targeted welding for magnetic‐assisted assembly, magnetization reprogramming, and permanent structural reconfiguration, is reported. These functions not only provide highly desirable structural and material programmability and reprogrammability but also enable the manufacturing of functional soft architected materials such as 3D kirigami with complex magnetization distribution. The welding of magnetic‐assisted modular assembly can be further combined with magnetization reprogramming and permanent reshaping capabilities for programmable and reconfigurable architectures and morphing structures. The reported MDP are anticipated to provide a new paradigm for the design and manufacture of future multifunctional assemblies and reconfigurable morphing architectures and devices.
Magnetic dynamic polymer composites composed of hard‐magnetic microparticles in thermally reversible dynamic polymer networks for multifunctional assemblies and reconfigurable architectures are reported. These composites integrate the functionalities of targeted welding of modular assembling with complex actuation, magnetization reprogramming with altered shape‐morphing mode, and remote‐controlled permanent structural reconfiguration, opening a new avenue for manufacturing multifunctional and reconfigurable morphing architectures and devices.
Mechanical metamaterials are architected manmade materials that allow for unique behaviors not observed in nature, making them promising candidates for a wide range of applications. Existing ...metamaterials lack tunability as their properties can only be changed to a limited extent after the fabrication. Herein, a new magneto‐mechanical metamaterial is presented that allows great tunability through a novel concept of deformation mode branching. The architecture of this new metamaterial employs an asymmetric joint design using hard‐magnetic soft active materials that permits two distinct actuation modes (bending and folding) under opposite‐direction magnetic fields. The subsequent application of mechanical compression leads to the deformation mode branching where the metamaterial architecture transforms into two distinctly different shapes, which exhibit very different deformations and enable great tunability in properties such as mechanical stiffness and acoustic bandgaps. Furthermore, this metamaterial design can be incorporated with magnetic shape memory polymers with global stiffness tunability, which also allows for the global shift of the acoustic behaviors. The combination of magnetic and mechanical actuations, as well as shape memory effects, impart wide tunable properties to a new paradigm of metamaterials.
A new magneto‐mechanical metamaterial permits great shape and multi‐physical property tunability through a novel concept of deformation mode branching. This is achieved through an asymmetric joint design using hard‐magnetic soft active materials with coupled magneto‐mechanical actuation. The metamaterial design can be further incorporated with magnetic shape memory polymers for global tunability of physical properties.
Photopolymerization is a widely used polymerization method in many engineering applications such as coating, dental restoration, and 3D printing. It is a complex chemical and physical process, ...through which a liquid monomer solution is rapidly converted to a solid polymer. In the most common free-radical photopolymerization process, the photoinitiator in the solution is exposed to light and decomposes into active radicals, which attach to monomers to start the polymerization reaction. The activated monomers then attack CC double bonds of unsaturated monomers, which leads to the growth of polymer chains. With increases in the polymer chain length and the average molecular weight, polymer chains start to connect and form a network structure, and the liquid polymer solution becomes a dense solid. During this process, the material properties of the cured polymer change dramatically. In this paper, experiments and theoretical modeling are used to investigate the free-radical photopolymerization reaction kinetics, material property evolution and mechanics during the photopolymerization process. The model employs the first order chemical reaction rate equations to calculate the variation of the species concentrations. The degree of monomer conversion is used as an internal variable that dictates the mechanical properties of the cured polymer at different curing states, including volume shrinkage, glass transition temperature, and nonlinear viscoelastic properties. To capture the nonlinear behavior of the cured polymer under low temperature and finite deformation, a multibranch nonlinear viscoelastic model is developed. A phase evolution model is used to describe the mechanics of the coupling between the crosslink network evolution and mechanical loading during the curing process. The comparison of the model and the experimental results indicates that the model can capture property changes during curing. The model is further applied to investigate the internal stress of a thick sample caused by volume shrinkage during photopolymerization. Changes in the conversion degree gradient and the internal stress during photopolymerization are determined using FEM simulation. The model can be extended to many photocuring processes, such as photopolymerization 3D printing, surface coating and automotive part curing processes.
Shape memory polymers (SMPs) have been intensively studied for a wide range of potential applications, including biomedical devices, morphing structures, and 4D printing. For amorphous polymers, the ...glass transition temperature measured by dynamic mechanical analysis (DMA) is an important consideration in designing SMPs. However, typical DMA curves are cooling- and heating-rate dependent and the cooling and heating traces for storage modulus form a (sometimes large) hysteresis loop. This paper first experimentally studies temperature-rate effects on DMA results. A constitutive relation is then developed based on the assumption that the stress relaxation behavior depends on both temperature and structural relaxation state. Good agreement is obtained between the experimental and the modeling results. This model is then applied to study the shape memory behaviors, showing that structural relaxation plays an important role in the free recovery; the model without considering structural relaxation tends to predict a fast recovery.
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•Stress relaxation time depends on temperature structural state of a polymer.•Structural relaxation is the main reason for the hysteresis loops in DMA tests.•The TTSP shift factor is modified to depend on temperature and time.•Temperature-rate dependent thermomechanical and shape memory behaviors are modeled.
Laser net shape manufacturing (LNSM) is a laser cladding/deposition based technology, which can fabricate and repair near-net-shape high-performance components directly from metal powders. ...Characterizing mechanical properties of the laser net shape manufactured components is prerequisite to the applications of LNSM in aircraft engine industrial productions. Nickel-based superalloys such as INCONEL 718 are the most commonly used metal materials in aircraft engine high-performance components. In this study, the laser deposition process is optimized through a set of designed experiments to reduce the porosity to less than 0.03 pct. It is found that the use of plasma rotating electrode processed (PREP) powder and a high energy input level greater than 80 J/mm are necessary conditions to minimize the porosity. Material microstructure and tensile properties of laser-deposited INCONEL 718 are studied and compared under heat treatment conditions of as deposited, direct aged, solution treatment and aging (STA), and full homogenization followed by STA. Tensile test results showed that the direct age heat treatment produces the highest tensile strength equivalent to the wrought material, which is followed by the STA-treated and the homogenization-treated tensile strengths, while the ductility exhibits the reverse trend. Finally, failure modes of the tensile specimens were analyzed with fractography.
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