Design framework for mechanically tunable soft biomaterial composites enhanced by modified horseshoe lattice structures

State of the art in Purkinje bioengineering

This review article will cover the recent developments in the new evolving field of Purkinje bioengineering and the development of human Purkinje networks. Recent work has progressed to the point of a methodological and systematic process to bioengineer Purkinje networks. This involves the development of 3D models based on human anatomy, followed by the development of tunable biomaterials, and strategies to reprogram stem cells to Purkinje cells. Subsequently, the reprogrammed cells and the biomaterials are coupled to bioengineer Purkinje networks, which are then tested using a small animal injury model. In this article, we discuss this process as a whole and then each step separately. We then describe potential applications of bioengineered Purkinje networks and challenges in the field that need to be overcome to move this field forward. Although the field of Purkinje bioengineering is new and in a state of infancy, it holds tremendous potential, both for therapeutic applications and to develop tools that can be used for disease modeling.

Tailorable acrylate-endcapped urethane-based polymers for precision in digital light processing: Versatile solutions for biomedical applications

Bioengineering seeks to replicate biological tissues exploiting scaffolds often based on polymeric biomaterials. Digital light processing (DLP) has emerged as a potent technique to fabricate tissue engineering (TE) scaffolds. However, the scarcity of suitable biomaterials with desired physico-chemical properties along with processing capabilities limits DLP's potential. Herein, we introduce acrylate-endcapped urethane-based polymers (AUPs) for precise physico-chemical tuning while ensuring optimal computer-aided design/computer-aided manufacturing (CAD/CAM) mimicry. Varying the polymer backbone (i.e. poly(ethylene glycol) (PEG) versus poly(propylene glycol) (PPG)) and photo-crosslinkable endcap (i.e. di-acrylate versus hexa-acrylate), we synthesized a series of photo-crosslinkable materials labeled as UPEG2, UPEG6, UPPG2 and UPPG6. Comprehensive material characterization including physico-chemical and biological evaluations, was followed by a DLP processing parametric study for each material. The impact of the number of acrylate groups per polymer (2 to 6) on the physico-chemical properties was pronounced, as reflected by a reduced swelling, lower water contact angles, accelerated crosslinking kinetics, and increased Young's moduli upon increasing the acrylate content. Furthermore, the different polymer backbones also exerted a substantial effect on the properties, including the absence of crystallinity, remarkably reduced swelling behaviors, a slight reduction in Young's modulus, and slower crosslinking kinetics for UPPG vs UPEG. The mechanical characteristics of DLP-printed samples showcased the ability to tailor the materials' stiffness (ranging from 0.4 to 5.3 MPa) by varying endcap chemistry and/or backbone. The in vitro cell assays confirmed biocompatibility of the material as such and the DLP-printed discs. Furthermore, the structural integrity of 3D scaffolds was preserved both in dry and swollen state. By adjusting the backbone chemistry or acrylate content, the post-swelling dimensions could be customized towards the targeted application. This study showcases the potential of these materials offering tailorable properties to serve many biomedical applications such as cartilage TE.

Approximation of extracted features enabling 3D design tuning for reproducing the mechanical behaviour of biological soft tissues

This article describes a new method, inspired by machine learning, to mimic the mechanical behaviour of target biological soft tissues with 3D printed materials. The principle is to optimise the structure of a 3D printed composite consisting of a geometrically tunable fibre embedded in a soft matrix. Physiological features are extracted from experimental stress-strain curves of several biological soft tissues. Then, using a cubic Bézier curve as the composite inner fibre, we optimised its geometric parameters, amplitude and height, to generate a specimen that exhibits a stress-strain curve in accordance with the extracted features of tensile tests. From this first phase, we created a database of specimen geometries that can be used to reproduce a wide variety of biological soft tissues. We applied this process to two soft tissues with very different behaviours: the mandibular periosteum and the calvarial periosteum. The results show that our method can successfully reproduce the mechanical behaviour of these tissues. This highlights the versatility of this approach and demonstrates that it can be extended to mimic various biological soft tissues.

Nonlinear Multimaterial Architecture for Greater Soft Material's Toughness and Delaying Damage Propagation

Designing soft robots that have greater toughness and better resistance to damage propagation while at the same time retaining their properties of compliance is fundamentally important for soft robotics applications. This study's main contribution is proposing a framework for nonlinear multimaterial architectural design of soft structures to increase their toughness and delay damage propagation. What are the limits when combining significantly different materials in one structure that will delay crack propagation while significantly maintaining postdamage toughness? Through this study, we observed that there is a very dynamic interplay when combining significantly different materials in one structure; this interplay could weaken or strengthen the multimaterial structure's toughness. In biological evolutionary terms, the Pangolin, Seashell, and Arapaima have found their answer for deflecting the crack and maintaining strength in their bodies. How does nature put these multimaterial structures together? Our research led us to find that the multimaterial toughness limits depend largely on the following parameters: components' relative morphology, architecture, spatial distribution, surface areas, and Young's Modulus. We found that a linear geometry, when it comes to morphology and/or architecture relative to surface area in multimaterial design, significantly reduces total toughness and fails to delay crack propagation. In contrast, incorporating geometric nonlinearities in both morphology and architecture significantly maintains higher total toughness even after damage, and significantly delays crack propagation. We believe that this study can open the door to further research and ultimately to promising and wide applications in soft robotics.

Dual-Phase Inspired Soft Electronic Sensors with Programmable and Tunable Mechanical Properties

Wearable and stretchable sensors are important components to strictly monitor the behavior and health of humans and attract extensive attention. However, traditional sensors are designed with pure horseshoes or chiral metamaterials, which restrict the biological tissue engineer applications due to their narrow regulation ranges of the elastic modulus and the poorly adjustable Poisson's ratio. Inspired by the biological spiral microstructure, a dual-phase metamaterial (chiral-horseshoes) is designed and fabricated in this work, which possesses wide and programmable mechanical properties by tailoring the geometrical parameters. Experimental, numerical, and theoretical studies are conducted, which reveal that the designed microstructures can reproduce mechanical properties of most natural animals such as frogs, snakes, and rabbits skin. Furthermore, a flexible strain sensor with the gauge factor reaching 2 under 35% strain is fabricated, which indicates that the dual-phase metamaterials have a stable monitoring ability and can be potentially applied in the electronic skin. Finally, the flexible strain sensor is attached on the human skin, and it can successfully monitor the physiological behavior signals under various actions. In addition, the dual-phase metamaterial could combine with artificial intelligence algorithms to fabricate a flexible stretchable display. The dual-phase metamaterial with negative Poisson's ratio could decrease the lateral shrinkage and image distortion during the stretching process. This study offers a strategy for designing the flexible strain sensors with programmable, tunable mechanical properties, and the fabricated soft and high-precision wearable strain sensor can accurately monitor the skin signals under different human motions and potentially be applied for flexible display.

3D printing of highly stretchable hydrogel with diverse UV curable polymers

Hydrogel-polymer hybrids have been widely used for various applications such as biomedical devices and flexible electronics. However, the current technologies constrain the geometries of hydrogel-polymer hybrid to laminates consisting of hydrogel with silicone rubbers. This greatly limits functionality and performance of hydrogel-polymer-based devices and machines. Here, we report a simple yet versatile multimaterial 3D printing approach to fabricate complex hybrid 3D structures consisting of highly stretchable and high-water content acrylamide-PEGDA (AP) hydrogels covalently bonded with diverse UV curable polymers. The hybrid structures are printed on a self-built DLP-based multimaterial 3D printer. We realize covalent bonding between AP hydrogel and other polymers through incomplete polymerization of AP hydrogel initiated by the water-soluble photoinitiator TPO nanoparticles. We demonstrate a few applications taking advantage of this approach. The proposed approach paves a new way to realize multifunctional soft devices and machines by bonding hydrogel with other polymers in 3D forms.

Design of 3D Printed Programmable Horseshoe Lattice Structures Based on a Phase-Evolution Model

By 3D printing lattice structure with active materials, the structures can exhibit shape and functional changes under external stimulus. However, the programmable shape changes of the 3D printed lattice structures are limited due to the complex geometries, nonlinear behaviors of the active materials, and the diverse external stimuli. In this work, we propose a design framework combining experiments, theoretical modeling, and finite element simulations for the controllable shape changes of the 3D printed horseshoe under thermal stimulus. The theoretical model is based on a phase evolution model that combines the geometrical nonlinearity and the material nonlinearity. Results show that the shapes with positive or negative Poisson's ratio and bending intermediate shapes can be programmed by tuning the geometrical parameters and the temperature distribution. This work provides a method to aid the design of 3D printed functional lattice structures and have potential applications in soft robotics, biomedicine, and energy absorbing fields.