Multi-material 3D Research Articles

Hydrogel-driven origami metamaterials for tunable swelling behavior

Origami metamaterial has gradually shown its potential in the fields of science and engineering due to its unique mechanical behaviors. Since hydrogel shows a positive volume change when absorbing water, it provides a new design strategy for actively deformed origami metamaterials composed of normal material framework and active hydrogel layer. In this paper, we proposed three synergistic mechanical designs with positive/negative/zero tunable swelling deformation by adjusting the opening direction of the circular holes. The deformation behaviors of the origami metamaterials manufactured by a multi-material 3D printer were qualitatively and quantitatively characterized and demonstrated, using finite element analysis, experimental test and theoretical method. The results indicate that the origami metamaterials present significant tunable swelling behaviors, which can be customized by adjusting the lattice microstructure geometry parameters. Utilizing the origami metamaterials, cylindrical shell and box structures with tunable swelling behavior were designed. Additionally, the hydrogel-driven actuator based on the origami metamaterials was manufactured to pull/drag an underwater object. Since the tunable swelling behaviors are not related to scale, these hydrogel-driven origami metamaterials can be applied to the design of reconfigurable and programmable devices on the macro and micro scale and possess promising potential for wide applications in bioelectronics and biological tissue engineering.

3D Printing of Electrically Responsive PVC Gel Actuators.

Additive manufacturing of electrically responsive soft actuators is of great importance in designing and constructing novel soft robots and soft machines. However, there are very limited options for 3D-printable and electrically responsive soft materials. Herein, we report a strategy of 3D printing polyvinyl chloride (PVC) gel actuators that are electrically controllable. We print a jellyfish-like actuator from PVC ink, which can achieve 130° bending in less than 5 s. With the multi-material 3D printing technique, we have further printed a soft actuator with a stiffness gradient that can generate undulatory motion. As a proof-of-concept demonstration, we show that a 3D-printed PVC gel-based smart window can change its transparency upon the application of voltage. The 3D printing strategy developed in this article may expand the potential applications of electrically responsive soft materials in diverse engineering fields.

Fabrication of Microfluidic Devices for Emulsion Formation by Microstereolithography.

Droplet microfluidics—the art and science of forming droplets—has been revolutionary for high-throughput screening, directed evolution, single-cell sequencing, and material design. However, traditional fabrication techniques for microfluidic devices suffer from several disadvantages, including multistep processing, expensive facilities, and limited three-dimensional (3D) design flexibility. High-resolution additive manufacturing—and in particular, projection micro-stereolithography (PµSL)—provides a promising path for overcoming these drawbacks. Similar to polydimethylsiloxane-based microfluidics 20 years ago, 3D printing methods, such as PµSL, have provided a path toward a new era of microfluidic device design. PµSL greatly simplifies the device fabrication process, especially the access to truly 3D geometries, is cost-effective, and it enables multimaterial processing. In this review, we discuss both the basics and recent innovations in PµSL; the material basis with emphasis on custom-made photopolymer formulations; multimaterial 3D printing; and, 3D-printed microfluidic devices for emulsion formation as our focus application. Our goal is to support researchers in setting up their own PµSL system to fabricate tailor-made microfluidics.

Physical and immuno-engineering of an advanced bioink based on a cold-adapted biomaterial for multi-material high-resolution 3D bioprinting

Physical and immuno-engineering of an advanced bioink based on a cold-adapted biomaterial for multi-material high-resolution 3D bioprinting

Multi-color and Multi-Material 3D Printing of Knee Joint models

ObjectiveThis study reports on a new method for the development of multi-color and multi-material realistic Knee Joint anatomical models with unique features. In particular, the design of a fibers matrix structure that mimics the soft tissue anatomy.MethodsVarious Computer-Aided Design (CAD) systems and the PolyJet 3D printing were used in the fabrication of three anatomical models wherein fibers matrix structure is mimicked: (i) Anterior cruciate ligament reconstruction (ACL-R) model used in the previous study. (ii) ACL-R model, incorporating orientations, directions, locations, and dimensions of the tunnels, as well as a custom-made surgical guide (SG) for avoiding graft tunnel length mismatch. (iii) Total knee arthroplasty (TKA) model, including custom-made implants. Before models 3D printing, uni-axial tensile tests were conducted to obtain the mechanical behaviors for individual No. 1 (A60-A50), No. 2 (A50-A50), No. 3 (A50-A40), and No. 4 (A70-A60) soft tissue-mimicking polymers. Each material combination represents different shore-hardness values between fiber and matrix respectively.ResultsWe correlated the pattern of stress-strain curves in the elastic region, stiffness, and elastic modulus of proposed combinations with published literature. Accordingly, material combinations No. 1 and No. 4 with elastic modules of 0.76-1.82 MPa were chosen for the soft tissues 3D printing. Finally, 3D printing Knee Joint models were tested manually simulating 50 flexo-extension cycles without presenting ruptures.ConclusionThe proposed anatomical models offer a diverse range of applications. These may be considered as an alternative to replacing cadaver specimens for medical training, pre-operative planning, research and education purposes, and predictive models validation. The soft tissue anatomy-mimicking materials are strong enough to withstand the stretching during the flexo-extension. The methodology reported for the design of the fiber-matrix structure might be considered as a start to develop new patterns and typologies that may mimic soft tissues.

A hybrid additive manufacturing platform based on fused filament fabrication and direct ink writing techniques for multi-material 3D printing

Among the available additive manufacturing (AM) technologies, fused filament fabrication (FFF) technique—broadly used in academia—seems to be a promising alternative to injection molding process in industry regarding physical prototypes. This is partially due to its accessibility, fast responsiveness and the substantial development of low-cost and open-source machines and filament materials. However, beyond the ongoing research efforts related to this material extrusion technique, the inherent layer-by-layer deposition strategy leads to lower mechanical performances compared to traditional formative and subtractive manufacturing processes. Indeed, recurrent anisotropic material properties and fracture strength still remains as the key challenges to be tackled in FFF, so as to get close to mechanical performances obtained by injection molding. In such a context, the main objective of the article is to extend mechanical parts’ performances by improving fracture strength of FFF printed parts. To do so, an innovative hybrid additive manufacturing platform—combining FFF and direct ink writing (DIW) techniques—is proposed. The proposed platform is implemented through a dedicated digital workflow covering process planning algorithms and a new modular concept of hybrid 3D printer. The added value of the proposal is demonstrated with tensile strength tests and opens the door to multi-material 3D printing.

Computational design of multi-stable, reconfigurable surfaces

A planar surface that can be reconfigured into several 3D target shapes is of importance in numerous fields at different length scales, e.g. aeronautical systems, buildings, and in medicine. Transformation into target shapes is typically an inverse problem solved by mapping a discretized representation of the surface to the flat plane and distorting the periodicity or the shape of each element. As this is a geometric problem, the system is not necessarily mechanically stable when reconfigured into the target shape. Here, a method is proposed for the generation of fabrication surfaces that can be reconfigured into several target shapes, each of which are statically stable. First, the target shapes are discretized as Chebyshev nets. The resulting quadrilateral elements are mapped to the fabrication surface, possibly planar for ease of manufacturing, by accounting for their defects in internal angles. These are accommodated by the lengthening or shortening of the diagonal members through the use of bistable actuators. Using a multi-material 3D printer, we fabricate a planar structure that reconfigures into two distinct and stable target shapes. The proposed method serves as a new direction for the design of material-based reconfigurable systems.

Closed-Structure Compliant Gripper With Morphologically Optimized Multi-Material Fingertips for Aerial Grasping

Aerial grasping empowers unmanned aerial vehicles to find applications beyond structured logistics. However, it brings a number of challenges including inaccurate positioning of the end effector and limited energy sources. Moreover, solutions so far have difficulty in handling a variety of objects. A novel closed structure compliant gripper was developed to address the challenges above. The gripper has a large self-centering work envelope and is normally-closed for passive grasping. Introduction of compliance as a form of morphological computation was also considered to enhance grasping capabilities, where multi-material 3D printing would facilitate rapid design changes based on target application. To grasp different objects, the gripper has hot-swappable 3D printed fingertips which are optimized with a multi-objective Bayesian Optimization process using physical bench experiments mimicking drone grasping and ascent on a common object set. The morphology of the fingertip including tip width, curvature and distribution of soft and hard material on contact surface, are optimized with a bench test that mimics quadcopter takeoff and landing. The best design from optimization shows an improvement of more than 10% from the initial design in successful grasp operations, demonstrated by field tests with a quadcopter.

Integrating digital light processing with direct ink writing for hybrid 3D printing of functional structures and devices

As an emerging branch of additive manufacturing, multi-material 3D printing has drawn tremendous attention as it offers more design flexibility that can combine materials with various mechanical, chemical, thermal-mechanical or electrical properties. However, low cost, high-speed, high-resolution, and versatile multi-material 3D printing methods are still lacking. In this paper, we present a new hybrid multi-material 3D printing system that consists of a top-down digital light processing (DLP) printing and a direct ink writing (DIW) printing to fabricate composite structures and unique devices in a single printing job. The vat photopolymerization-based DLP printing allows for high-speed and high-resolution printing of a material matrix with complex geometry. The material extrusion-based DIW printing enables the printing of functional material, including liquid crystal elastomers (LCEs) and conductive silver inks. With this hybrid 3D printing system, a wide choice of inks and resins can be used to print functional composites with tunable mechanical properties, enhanced interfacial bonding, and multifunctionality. We demonstrate that composites prototype, active soft robots, circuit-embedding architectures, and strain sensors can be successfully printed. This work provides a new and robust approach for 3D printing of multi-functional devices for broad applications in soft robotics, electronics, active metamaterials, and biomedical devices.

Optimization of Generatively Encoded Multi-Material Lattice Structures for Desired Deformation Behavior

Natural systems achieve favorable mechanical properties through coupling significantly different elastic moduli within a single tissue. However, when it comes to man-made materials and structures, there are a lack of methods which enable production of artifacts inspired by these phenomena. In this study, a method for design automation based on alternate deposition of soft and stiff struts within a multi-material 3D lattice structure with desired deformation behavior is proposed. These structures, once external forces are applied, conform to the geometry given in advance. For that purpose, a population-based algorithm was proposed and integrated with a multi-material physics simulator. To reduce the amount of data processed during optimization, a generative encoding method based on discrete cosine transform (DCT) was proposed. This enabled a compressed topological description and promoted symmetry in material distribution. The simulation results showed different three-dimensional lattice structures designed with proposed algorithm to meet a set of desired deformation behaviors. The relation between residual deformation error, targeted deformation geometry, and material distribution is discussed.

Shape memory alloy based 3D printed composite actuators with variable stiffness and large reversible deformation

Soft composite actuators can be fabricated by embedding shape memory alloy (SMA) wires into soft polymer matrices. Shape retention and recovery of these actuators are typically achieved by incorporating shape memory polymer segments into the actuator structure. However, this requires complex manufacturing processes. This work uses multimaterial 3D printing to fabricate composite actuators with variable stiffness capable of shape retention and recovery. The hinges of the bending actuators presented here are printed from a soft elastomeric layer as well as a rigid shape memory polymer (SMP) layer. The SMA wires are embedded eccentrically over the entire length of the printed structure to provide the actuation bending force, while the resistive wires are embedded into the SMP layer of the hinges to change the temperature and the bending stiffness of the actuator hinges via Joule heating. The temperature of the embedded SMA wire and the printed SMP segments is changed sequentially to accomplish a large bending deformation, retention of the deformed shape, and recovery of the original shape, without applying any external mechanical force. The SMP layer thickness was varied to investigate its effect on shape retention and recovery. A nonlinear finite element model was used to predict the deformation of the actuators.

Density and Mechanical Properties of Selective Silicon Materials to Produce 3D Printed Paediatric Brain Model

This study presents a step towards exploring the possibility of using silicon materials as a surrogate to produce a multi-material 3D printed soft silicone brain model to be used in the investigation of Traumatic Brain Injury (TBI) in paediatric populations. Silicone represents a popular choice of material due to its viscoelastic properties, 3D printability, and capability to be tuned to possess different properties. Dynamic oscillatory shear tests were carried out for seven types of silicon materials at three different speeds against a different range of frequencies. The mechanical parameters response has been ranked on, which is the most appropriate to try. It also agrees with the range of reported paediatric brain tissue imitating grey and white matter as a surrogate brain material. Utilising of silicone for 3D printing represents a new approach to fabricate surrogate models that closely mimic biofidelic features and advance the medical engineering discipline.

Deep learning models for optically characterizing 3D printers.

Multi-material 3D printers are able to create material arrangements possessing various optical properties. To reproduce these properties, an optical printer model that accurately predicts optical properties from the printer's control values (tonals) is crucial. We present two deep learning-based models and training strategies for optically characterizing 3D printers that achieve both high accuracy with a moderate number of required training samples. The first one is a Pure Deep Learning (PDL) model that is essentially a black-box without any physical ground and the second one is a Deep-Learning-Linearized Cellular Neugebauer (DLLCN) model that uses deep-learning to multidimensionally linearize the tonal-value-space of a cellular Neugebauer model. We test the models on two six-material polyjetting 3D printers to predict both reflectances and translucency. Results show that both models can achieve accuracies sufficient for most applications with much fewer training prints compared to a regular cellular Neugebauer model.

Multi-material multi-photon 3D laser micro- and nanoprinting

Three-dimensional (3D) laser micro- and nanoprinting based upon multi-photon absorption has made its way from early scientific discovery to industrial manufacturing processes, e.g., for advanced microoptical components. However, so far, most realized 3D architectures are composed of only a single polymeric material. Here, we review 3D printing of multi-materials on the nano- and microscale. We start with material properties that have been realized, using multi-photon photoresists. Printed materials include bulk polymers, conductive polymers, metals, nanoporous polymers, silica glass, chalcogenide glasses, inorganic single crystals, natural polymers, stimuli-responsive materials, and polymer composites. Next, we review manual and automated processes achieving dissimilar material properties in a single 3D structure by sequentially photo-exposing multiple photoresists as 3D analogs of 2D multicolor printing. Instructive examples from biology, optics, mechanics, and electronics are discussed. An emerging approach – without counterpart in 2D graphical printing – prints 3D structures combining dissimilar material properties in one 3D structure by using only a single photoresist. A controlled stimulus applied during the 3D printing process defines and determines material properties on the voxel level. Change of laser power and/or wavelength, or application of quasi-static electric fields allow for the seamless manipulation of desired materials properties.

Composition-segmented BiSbTe thermoelectric generator fabricated by multimaterial 3D printing

Abstract Segmented thermoelectric generators (TEGs) comprising multiple TE elements can operate over a large thermal gradient without inherent conversion efficiency (ZT) losses of materials. However, despite excellent theoretical efficiencies, the performance of actual segmented TEGs are critically affected by several challenges related to material incompatibility and limited design flexibility in conventional fabrication processes. Herein, we report the multi-material 3D printing of composition-segmented BiSbTe materials by the sequential deposition of all-inorganic viscoelastic TE inks containing BixSb2-xTe3 particles, tailored with Sb2Te42− chalcogenidometallate binders. The peak ZTs of the 3D-printed materials controllably shifted from room temperature to 250 °C by composition engineering of BixSb2-xTe3 particles. We fabricated the optimally designed TEG comprising the 3D-printed, composition-segmented tri-block Bi0.55Sb1.45Te3/Bi0.5Sb1.5Te3/Bi0.35Sb1.65Te3 TE leg, which extends the peak ZTs and satisfies full compatibility across the entire temperature range, realizing a record-high efficiency of 8.7% under the temperature difference of 236 °C. Our approach offers a promising strategy to optimize segmented TEGs.

3D printed gradient index glass optics.

We demonstrate an additive manufacturing approach to produce gradient refractive index glass optics. Using direct ink writing with an active inline micromixer, we three-dimensionally print multimaterial green bodies with compositional gradients, consisting primarily of silica nanoparticles and varying concentrations of titania as the index-modifying dopant. The green bodies are then consolidated into glass and polished, resulting in optics with tailored spatial profiles of the refractive index. We show that this approach can be used to achieve a variety of conventional and unconventional optical functions in a flat glass component with no surface curvature.

A Novel 3-Dimensional Printing Fabrication Approach for the Production of Pediatric Airway Models.

BACKGROUND:Pediatric airway models currently available for use in education or simulation do not replicate anatomy or tissue responses to procedures. Emphasis on mass production with sturdy but homogeneous materials and low-fidelity casting techniques diminishes these models’ abilities to realistically represent the unique characteristics of the pediatric airway, particularly in the infant and younger age ranges. Newer fabrication technologies, including 3-dimensional (3D) printing and castable tissue-like silicones, open new approaches to the simulation of pediatric airways with greater anatomical fidelity and utility for procedure training.METHODS:After ethics approval, available/archived computerized tomography data sets of patients under the age of 2 years were reviewed to identify those suitable for designing new models. A single 21-month-old subject was selected for 3D reconstruction. Manual thresholding was then performed to produce 3D models of selected regions and tissue types within the dataset, which were either directly 3D-printed or later cast in 3D-printed molds with a variety of tissue-like silicones. A series of testing mannequins derived using this multimodal approach were then further refined following direct clinician feedback to develop a series of pediatric airway model prototypes.RESULTS:The initial prototype consisted of separate skeletal (skull, mandible, vertebrae) and soft-tissue (nasal mucosa, pharynx, larynx, gingivae, tongue, functional temporomandibular joint [TMJ] “sleeve,” skin) modules. The first iterations of these modules were generated using both single-material and multimaterial 3D printing techniques to achieve the haptic properties of real human tissues. After direct clinical feedback, subsequent prototypes relied on a combination of 3D printing for osseous elements and casting of soft-tissue components from 3D-printed molds, which refined the haptic properties of the nasal, oropharyngeal, laryngeal, and airway tissues, and improved the range of movement required for airway management procedures. This approach of modification based on clinical feedback resulted in superior functional performance.CONCLUSIONS:Our hybrid manufacturing approach, merging 3D-printed components and 3D-printed molds for silicone casting, allows a more accurate representation of both the anatomy and functional characteristics of the pediatric airway for model production. Further, it allows for the direct translation of anatomy derived from real patient medical imaging into a functional airway management simulator, and our modular design allows for modification of individual elements to easily vary anatomical configurations, haptic qualities of components or exchange components to replicate pathology.

T 1-mapping and dielectric properties evaluation of a 3D printable rubber-elastomeric polymer as tissue mimicking materials for MRI phantoms

In this study, a new series of 3D printable rubber-elastomeric polymer called PORO-LAY materials have been investigated regarding their suitability to serve as tissue mimicking materials (TMMs) for MRI phantoms. PORO-LAY materials have been previously used in biofuel cell developments, particle filtrations and modeling elastic tissues. We evaluated the electrical permittivity, electrical conductivity, spin-lattice T 1-relaxation time and acquired the MRI contrast for simple and multi-material complex 3D printed shapes made of PORO-LAY materials at 3.0 T. The results showed a T 1 diversity within PORO-LAY materials, which reveals in different MR image contrasts. The outcome favors PORO-LAY as an appropriate candidate that can be used in multi-materials additive manufacturing to produce realistic shapes such as white/grey matter structures for MRI phantoms with visible clear contrast. Finally, this study could serve as a reference and guideline when using these materials as tissue mimicking materials for different types of human body tissues and provide a promising opportunity to design novel phantoms for a wide range of MRI applications.

Multi-material 3D printing of caterpillar-inspired soft crawling robots with the pneumatically bellow-type body and anisotropic friction feet

Due to large shape-changing ability and high adaptability, soft crawling robots become a promising candidate in applications with unpredictable terrain and complex environments. However, designing and fabricating of soft crawling robots with hybrid soft and rigid components are still elusive. Here, we present a novel caterpillar inspired pneumatically-driven soft crawling robot, which can be directly 3D printed with multiple materials and without complex assembling process. To mimic the biological structure and morphological locomotion of caterpillars, we design the soft crawling robot with a pneumatically driven bellow-type body, 12 anisotropic frictional feet, and two end caps, and introduce a passive synergy locomotion model between the crawling robot’s body and feet. By selecting different cross-section shape of the feet, we characterize the moving performance of soft crawling robots. Finally, we integrate a pneumatic closed-loop control system to drive the soft crawling robots with a periodic gait and demonstrate their motion capability in a curve plastic tube.

Scale and size effects on the mechanical properties of bioinspired 3D printed two-phase composites

Multi-material 3D printing offers design flexibility for the manufacture of new architectured composite materials and has been increasingly used to explore the mechanical properties of bioinspired composites. In this study, the influence of scale and size on mechanical properties of periodic two-phase composites with various architectures of a stiff and a soft phase are explored. The studied composites include an interpenetrating phase composite with two continuous phases (inspired by bone), a matrix-inclusion composite with a continuous and a discontinuous phase, and a discontinuous phase composite where both phases are discontinuous. These composites are fabricated by additive manufacturing, and their mechanical properties are evaluated experimentally using a compression test complemented by digital image correlation, and numerically through finite element analysis. Overall trends show that the elastic moduli and yield strengths decrease as the scale is increased. Our results on size effects reveal an increase in elastic modulus and yield strength with increasing size of the sample. Our investigation outcomes help to better understand some of the challenges in studying and applications of additively manufactured composites and shed light on scale and size effects on mechanical properties of 3D printed two-phase composites. This paper illustrates a need for further studies of scale and size effects in additively manufactured materials.