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Active composites are a class of materials that have environmentally responsive components within them. One key advantage of active composites is that through mechanics design, a variety of actuation can be achieved. The development of active composites has been significantly enhanced in recent years by multimaterial 3D printing where different materials can be precisely placed in 3D space, enabling the achievement of shape-shifting of 3D printed parts, or 4D printing. In practical applications, it is highly desirable that the part shape can change in a pre-described manner, which requires the careful design of where to place different materials. However, designing an active composite structure to achieve a target shape change is challenging because it requires solving an inverse problem with spatially heterogenous, highly nonlinear (active) material behavior within a potentially complex boundary value problem. In this paper we present a machine learning approach to the design of active composite structures that can achieve target shape shifting responses. Our strategy is to combine the finite element method with an evolutionary algorithm. In order to achieve a target shape, we compose the structures of equally sized voxel units that are made of either a passive or an active material and optimize the distribution of these two material phases. The optimization method is tested against several illustrative examples in active composite design to show the agreement between the target shape and the best machine learning solution obtained.

Shape memory polymers (SMPs) have the capacity to recover large strains when pre-deformed at an elevated temperature, cooled to a lower temperature and reheated. The thermomechanical recovery behavior of an SMP is examined in three-point flexure for various pre-deformation and recovery conditions. Results indicate that when pre-deformed well above the glass transition temperature, Tg, the stress–strain response at the pre-deformation temperature governs the relationship between the recovery stress/strain and the corresponding pre-deformation strain/stress. When pre-deformed at a temperature below Tg, the relationship between recoverable stress and strain level in the SMP is not governed by the stress–strain response of the material at the pre-deformation temperature. Rather, a peak recovery stress, which is less than the applied pre-deformation stress, appears near Tg. Higher cooling rates during constraint lower the temperature necessary for complete shape fixity, but increase the recoverable stress level. Higher heating rates during recovery raise the recovery onset temperature and decrease the peak recoverable stress. Ramifications of the results on future research efforts and emerging applications of SMPs are discussed.

This paper studies a novel method to fabricate three-dimensional (3D) structure from 2D thermo-responsive shape memory polymer (SMP)/elastomer bilayer laminate. In this method, the shape change is actuated by the thermal mismatch strain between the SMP and the elastomer layers upon heating. However, the glass transition behavior of the SMP locks the material into a new 3D shape that is stable even upon cooling. Therefore, the second shape becomes a new permanent shape of the laminate. A theoretical model that accounts for the temperature-dependent thermomechanical behavior of the SMP material and thermal mismatch strain between the two layers is developed to better understand the underlying physics. Model predictions and experiments show good agreement and indicate that the theoretical model can well predict the bending behavior of the bilayer laminate. The model is then used in the optimal design of geometrical configuration and material selection. The latter also illustrates the requirement of thermomechanical behaviors of the SMP to lock the shape. Based on the fundamental understandings, several self-folding structures are demonstrated by the bilayer laminate design.

Recent developments in soft materials and 3D printing are promoting the rapid development of novel technologies and concepts, such as 4D printing and soft machines, that in turn require new methods for fabricating conductive materials. Despite the ubiquity of silver nanoparticles (NPs) in the conducting electrodes of printed electronic devices, their potential use in stretchable conductors has not been fully explored in 4D printing and soft machines. This paper studies the effect of thermal cure conditions on conductivity and electro-mechanical behaviors of silver ink by the direct ink write (DIW) printing approach. We found that the electro-mechanical properties of silver wires can be tailored by controlling cure time and cure temperature to achieve conductivity as well as stretchability. For the silver NP ink we used in the experiments, silver wires cured at 80 °C for 10–30 min have conductivity >1% bulk silver, Young's modulus

Recent advances in three dimensional (3D) printing technology that allow multiple materials to be printed within each layer enable the creation of materials and components with precisely controlled heterogeneous microstructures. In addition, active materials, such as shape memory polymers, can be printed to create an active microstructure within a solid. These active materials can subsequently be activated in a controlled manner to change the shape or configuration of the solid in response to an environmental stimulus. This has been termed 4D printing, with the 4th dimension being the time-dependent shape change after the printing. In this paper, we advance the 4D printing concept to the design and fabrication of active origami, where a flat sheet automatically folds into a complicated 3D component. Here we print active composites with shape memory polymer fibers precisely printed in an elastomeric matrix and use them as intelligent active hinges to enable origami folding patterns. We develop a theoretical model to provide guidance in selecting design parameters such as fiber dimensions, hinge length, and programming strains and temperature. Using the model, we design and fabricate several active origami components that assemble from flat polymer sheets, including a box, a pyramid, and two origami airplanes. In addition, we directly print a 3D box with active composite hinges and program it to assume a temporary flat shape that subsequently recovers to the 3D box shape on demand.

Shape memory polymers (SMPs) are a class of smart materials that can fix a temporary shape and recover to their permanent (original) shape in response to an environmental stimulus such as heat, electricity, or irradiation, among others. Most SMPs developed in the past can only demonstrate the so-called one-way shape memory effect; i.e., one programming step can only yield one shape memory cycle. Recently, one of the authors (Mather) developed a SMP that exhibits both one-way shape memory (1W-SM) and two-way shape memory (2W-SM) effects (with the assistance of an external load). This SMP was further used to develop a free-standing composite actuator with a nonlinear reversible actuation under thermal cycling. In this paper, a theoretical model for the PCO SMP based composite actuator was developed to investigate its thermomechanical behavior and the mechanisms for the observed phenomena during the actuation cycles, and to provide insight into how to improve the design.

Shape memory polymers (SMPs) have attracted significant research efforts due to their ease in manufacturing and highly tailorable thermomechanical properties. SMPs can be temporarily programmed and fixed in a nonequilibrium shape and are capable of recovering the original undeformed shape upon exposure to a stimulus, the most common being temperature. Most SMPs exhibit a one-way shape memory (1W-SM) effect since one programming step can only yield one shape memory cycle; an additional shape memory cycle requires an extra programming step. Recently, a novel SMP that demonstrates both 1W-SM and two-way shape memory (2W-SM) effects was demonstrated by one of the authors (Mather). However, to achieve two-way actuation this SMP relies on a constant externally applied load. In this paper, an SMP composite where a pre-stretched 2W-SMP is embedded in an elastomeric matrix is developed. This composite demonstrates 2W-SM effects in response to changes in temperature without the requirement of a constant external load. A transversal actuation of ~ 10% of actuator length is achieved. Cyclic tests show that the transversal actuation stabilizes after an initial training cycle and shows no significant decreases after four cycles. A simple analytic model considering the programming stress and actuator dimensions is presented and shown to agree well with the transverse displacement of the actuator. The model also predicts that larger actuation can be achieved when larger pre-stretch of 2W-SMP is used. The scheme used for this polymer composite can promote the design of new shape memory composites at micro- and nano-length scales to meet different application requirements.

We demonstrate the feasibility of using classical atomistic simulations, i.e. molecular dynamics and molecular statics, to study the piezoelectric properties of ZnO using core-shell interatomic potentials. We accomplish this by reporting the piezoelectric constants for ZnO as calculated using two different classical interatomic core-shell potentials: that originally proposed by Binks and Grimes (1994 Solid State Commun. 89 921-4), and that proposed by Nyberg et al (1996 J. Phys. Chem. 100 9054-63). We demonstrate that the classical core-shell potentials are able to qualitatively reproduce the piezoelectric constants as compared to benchmark ab initio calculations. We further demonstrate that while the presence of the shell is required to capture the electron polarization effects that control the clamped ion part of the piezoelectric constant, the major shortcoming of the classical potentials is a significant underprediction of the clamped ion term as compared to previous ab initio results. However, the present results suggest that overall, these classical core-shell potentials are sufficiently accurate to be utilized for large scale atomistic simulations of the piezoelectric response of ZnO nanostructures.