Three-Dimensional-Printing of Bio-Inspired Composites

Studies on effect of failure modes on mechanical properties of staggered composites

Biological materials such as bone, nacre, antler, and teeth are gifted with excellent mechanical properties that have inspired the development of synthetic composites. These superior properties are attributed to the geometrical as well as the material properties of the constituents at a small scale. This paper is focused on the influence of failure modes over the mechanical properties including stiffness, strength, and toughness, after the failure of different interfaces in staggered bio-inspired structures such as regular and stairwise staggered arrangements where stiff platelets are embedded in a pliant matrix. In order to find these properties, this article develops a novel analytical model for stress transfer and effective Young's modulus of a stairwise staggered composite based on composite micro-mechanics principles. The results indicate that the failure sequence indeed influences mechanical characteristics such as stiffness, strength, and toughness. Also, the results from the present study is capable of quantifying the major contribution of toughness that is obtained from the vertical interface failure, which is ignored in previous studies for estimating the toughness. The results indicate that a toughness contribution as high as 56% from the inclusion of the first failure can be obtained in a stairwise staggered composite. The influence of significant parameters like Young's moduli ratio between the platelet and matrix (Ep/Em) over the strength at different modes of failure showed that the strength at first and second failures increases as theEp/Emratio increases. The findings of this study hold significant potential for predicting the failure sequences with their quantified contributions towards the mechanical properties of a bio-inspired staggered composite.

Modeling and design of heterogeneous hierarchical bioinspired spider web structures using deep learning and additive manufacturing

Spider webs are incredible biological structures, comprising thin but strong silk filament and arranged into complex hierarchical architectures with striking mechanical properties (e.g., lightweight but high strength, achieving diverse mechanical responses). While simple 2D orb webs can easily be mimicked, the modeling and synthesis of 3D-based web structures remain challenging, partly due to the rich set of design features. Here, we provide a detailed analysis of the heterogeneous graph structures of spider webs and use deep learning as a way to model and then synthesize artificial, bioinspired 3D web structures. The generative models are conditioned based on key geometric parameters (including average edge length, number of nodes, average node degree, and others). To identify graph construction principles, we use inductive representation sampling of large experimentally determined spider web graphs, to yield a dataset that is used to train three conditional generative models: 1) an analog diffusion model inspired by nonequilibrium thermodynamics, with sparse neighbor representation; 2) a discrete diffusion model with full neighbor representation; and 3) an autoregressive transformer architecture with full neighbor representation. All three models are scalable, produce complex, de novo bioinspired spider web mimics, and successfully construct graphs that meet the design objectives. We further propose an algorithm that assembles web samples produced by the generative models into larger-scale structures based on a series of geometric design targets, including helical and parametric shapes, mimicking, and extending natural design principles toward integration with diverging engineering objectives. Several webs are manufactured using 3D printing and tested to assess mechanical properties.

Generating 3D architectured nature-inspired materials and granular media using diffusion models based on language cues

A variety of image generation methods have emerged in recent years, notably DALL-E 2, Imagen and Stable Diffusion. While they have been shown to be capable of producing photorealistic images from text prompts facilitated by generative diffusion models conditioned on language input, their capacity for materials design has not yet been explored. Here, we use a trained Stable Diffusion model and consider it as an experimental system, examining its capacity to generate novel material designs especially in the context of 3D material architectures. We demonstrate that this approach offers a paradigm to generate diverse material patterns and designs, using human-readable language as input, allowing us to explore a vast nature-inspired design portfolio for both novel architectured materials and granular media. We present a series of methods to translate 2D representations into 3D data, including movements through noise spaces via mixtures of text prompts, and image conditioning. We create physical samples using additive manufacturing and assess material properties of materials designed via a coarse-grained particle simulation approach. We present case studies using images as starting point for material generation; exemplified in two applications. First, a design for which we use Haeckel's classic lithographic print of a diatom, which we amalgamate with a spider web. Second, a design that is based on the image of a flame, amalgamating it with a hybrid of a spider web and wood structures. These design approaches result in complex materials forming solids or granular liquid-like media that can ultimately be tuned to meet target demands.

Learning the stress-strain fields in digital composites using Fourier neural operator

Increased demands for high-performance materials have led to advanced composite materials with complex hierarchical designs. However, designing a tailored material microstructure with targeted properties and performance is extremely challenging due to the innumerable design combinations and prohibitive computational costs for physics-based solvers. In this study, we employ a neural operator-based framework, namely Fourier neural operator (FNO), to learn the mechanical response of 2D composites. We show that the FNO exhibits high-fidelity predictions of the complete stress and strain tensor fields for geometrically complex composite microstructures with very few training data and purely based on the microstructure. The model also exhibits zero-shot generalization on unseen arbitrary geometries with high accuracy. Furthermore, the model exhibits zero-shot super-resolution capabilities by predicting high-resolution stress and strain fields directly from low-resolution input configurations. Finally, the model also provides high-accuracy predictions of equivalent measures for stress-strain fields, allowing realistic upscaling of the results.

•

Predict stress and strain tensors directly from the microstructure

•

Demonstrate material and pixel-wise super-resolution of the FNO model

•

Zero-shot generalization to unseen arbitrary geometries

•

Measuring equivalent quantities such as von-mises stress and equivalent strains

Design, manufacture, and testing of customized sterilizable respirator

The respirator as one of the personal protective equipment is essential for industrial activities (e.g., mining, painting, woodcutting, manufacturing) for protection from contaminants in the air and during the Covid-19 pandemic to protect the wearer from infection. The respirators nowadays are commonly made of rigid plastic. They are expensive, cumbersome, and not comfortable to wear. The many components with complex structures prevent it from cleaning and reusing. We develop a practical and scalable strategy to create customized respirators with durability using computational modeling and 3D printing. It is shown that by morphing the shape according to the user's photo, the respirator is designed to fit a user's face without air leaks. Using a printing-mold-casting method, this respirator can be manufactured by silicone rubber with accuracy, which is highly durable, with its mechanics primarily not affected by sterilization. These features provide the current respirator adaptivity and convenience in carrying and storing, as well as more comfort for long-time wearing.

Targeting angiogenesis in myocardial infarction: Novel therapeutics (Review)

Acute myocardial infarction (AMI) remains the main cause of mortality worldwide. Despite surgery and medical treatment, the non-regeneration of dead cardiomyocytes and the limited contractile ability of scar tissue can lead to heart failure. Therefore, restoring blood flow in the infarcted area is important for the repair of myocardial injury. The objective of the present review was to summarize the factors influencing angiogenesis after AMI, and to describe the application of angiogenesis for cardiac repair. Collectively, this review may be helpful for relevant studies and to provide insight into future therapeutic applications in clinical practice.

Biomimetic Approaches for the Design and Fabrication of Bone-to-Soft Tissue Interfaces

Bone-to-soft tissue interfaces are responsible for transferring loads between tissues with significantly dissimilar material properties. The examples of connective soft tissues are ligaments, tendons, and cartilages. Such natural tissue interfaces have unique microstructural properties and characteristics which avoid the abrupt transitions between two tissues and prevent formation of stress concentration at their connections. Here, we review some of the important characteristics of these natural interfaces. The native bone-to-soft tissue interfaces consist of several hierarchical levels which are formed in a highly specialized anisotropic fashion and are composed of different types of heterogeneously distributed cells. The characteristics of a natural interface can rely on two main design principles, namely by changing the local microarchitectural features (e.g., complex cell arrangements, and introducing interlocking mechanisms at the interfaces through various geometrical designs) and changing the local chemical compositions (e.g., a smooth and gradual transition in the level of mineralization). Implementing such design principles appears to be a promising approach that can be used in the design, reconstruction, and regeneration of engineered biomimetic tissue interfaces. Furthermore, prominent fabrication techniques such as additive manufacturing (AM) including 3D printing and electrospinning can be used to ease these implementation processes. Biomimetic interfaces have several biological applications, for example, to create synthetic scaffolds for osteochondral tissue repair.

In situ three-dimensional spider web construction and mechanics

Spiders are nature's engineers that build lightweight and high-performance web architectures often several times their size and with very few supports; however, little is known about web mechanics and geometries throughout construction, especially for three-dimensional (3D) spider webs. In this work, we investigate the structure and mechanics for a Tidarren sisyphoides spider web at varying stages of construction. This is accomplished by imaging, modeling, and simulations throughout the web-building process to capture changes in the natural web geometry and the mechanical properties. We show that the foundation of the web geometry, strength, and functionality is created during the first 2 d of construction, after which the spider reinforces the existing network with limited expansion of the structure within the frame. A better understanding of the biological and mechanical performance of the 3D spider web under construction could inspire sustainable robust and resilient fiber networks, complex materials, structures, scaffolding, and self-assembly strategies for hierarchical structures and inspire additive manufacturing methods such as 3D printing as well as inspire artistic and architectural and engineering applications.

The Challenge of Dental Education After COVID-19 Pandemic - Present and Future Innovation Study Design

The present work suggests research and innovation on the topic of dental education after the COVID-19 pandemic, is highly justified and could lead to a step change in dental practice. The challenge for the future in dentistry education should be revised with the COVID-19 and the possibility for future pandemics, since in most countries dental students stopped attending the dental faculties as there was a general lockdown of the population. The dental teaching has an important curriculum in the clinic where patients attend general dentistry practice. However, with SARS-CoV-2 virus, people may be reluctant having a dental treatment were airborne transmission can occur in some dental procedures. In preclinical dental education, the acquisition of clinical, technical skills, and the transfer of these skills to the clinic are extremely important. Therefore, dental education has to adapt the curriculum to embrace new technology devices, instrumentations systems, haptic systems, simulation based training, 3D printer machines, to permit validation and calibration of the technical skills of dental students.

Long-term stabilized amorphous calcium carbonate-an ink for bio-inspired 3D printing

Biominerals formed by organisms in the course of biomineralization often demonstrate complex morphologies despite their single-crystalline nature. This is achieved owing to the crystallization via a predeposited amorphous calcium carbonate (ACC) phase, a precursor that is particularly widespread in biominerals. Inspired by this natural strategy, we used robocasting, an additive manufacturing three-dimensional (3D) printing technique, for printing 3D objects from novel long-term, Mg-stabilized ACC pastes with high solids loading. We demonstrated, for the first time, that the ACC remains stable for at least a couple of months, even after printing. Crystallization, if desired, occurs only after the 3D object is already formed and at temperatures significantly lower than those of common postprinting sintering. We also examined the effects different organic binders have on the crystallization, the morphology, and the final amount of incorporated Mg. This novel bio-inspired method may pave the way for a new bio-inspired route to low-temperature 3D printing of ceramic materials for a multitude of applications.

Deep learning model to predict complex stress and strain fields in hierarchical composites

Materials-by-design is a paradigm to develop previously unknown high-performance materials. However, finding materials with superior properties is often computationally or experimentally intractable because of the astronomical number of combinations in design space. Here we report an AI-based approach, implemented in a game theory-based conditional generative adversarial neural network (cGAN), to bridge the gap between a material's microstructure-the design space-and physical performance. Our end-to-end deep learning model predicts physical fields like stress or strain directly from the material microstructure geometry, and reaches an astonishing accuracy not only for predicted field data but also for derivative material property predictions. Furthermore, the proposed approach offers extensibility by predicting complex materials behavior regardless of component shapes, boundary conditions, and geometrical hierarchy, providing perspectives of performing physical modeling and simulations. The method vastly improves the efficiency of evaluating physical properties of hierarchical materials directly from the geometry of its structural makeup.

Artificial intelligence and machine learning in design of mechanical materials

Artificial intelligence, especially machine learning (ML) and deep learning (DL) algorithms, is becoming an important tool in the fields of materials and mechanical engineering, attributed to its power to predict materials properties, design de novo materials and discover new mechanisms beyond intuitions. As the structural complexity of novel materials soars, the material design problem to optimize mechanical behaviors can involve massive design spaces that are intractable for conventional methods. Addressing this challenge, ML models trained from large material datasets that relate structure, properties and function at multiple hierarchical levels have offered new avenues for fast exploration of the design spaces. The performance of a ML-based materials design approach relies on the collection or generation of a large dataset that is properly preprocessed using the domain knowledge of materials science underlying chemical and physical concepts, and a suitable selection of the applied ML model. Recent breakthroughs in ML techniques have created vast opportunities for not only overcoming long-standing mechanics problems but also for developing unprecedented materials design strategies. In this review, we first present a brief introduction of state-of-the-art ML models, algorithms and structures. Then, we discuss the importance of data collection, generation and preprocessing. The applications in mechanical property prediction, materials design and computational methods using ML-based approaches are summarized, followed by perspectives on opportunities and open challenges in this emerging and exciting field.

Liquid Crystal Elastomers for Biological Applications

The term liquid crystal elastomer (LCE) describes a class of materials that combine the elastic entropy behaviour associated with conventional elastomers with the stimuli responsive properties of anisotropic liquid crystals. LCEs consequently exhibit attributes of both elastomers and liquid crystals, but additionally have unique properties not found in either. Recent developments in LCE synthesis, as well as the understanding of the behaviour of liquid crystal elastomers—namely their mechanical, optical and responsive properties—is of significant relevance to biology and biomedicine. LCEs are abundant in nature, highlighting the potential use of LCEs in biomimetics. Their exceptional tensile properties and biocompatibility have led to research exploring their applications in artificial tissue, biological sensors and cell scaffolds by exploiting their actuation and shock absorption properties. There has also been significant recent interest in using LCEs as a model for morphogenesis. This review provides an overview of some aspects of LCEs which are of relevance in different branches of biology and biomedicine, as well as discussing how recent LCE advances could impact future applications.

Properties and role of interfaces in multimaterial 3D printed composites

In polyjet printing photopolymer droplets are deposited on a build tray, leveled off by a roller and cured by UV light. This technique is attractive to fabricate heterogeneous architectures combining compliant and stiff constituents. Considering the layer-by-layer nature, interfaces between different photopolymers can be formed either before or after UV curing. We analyzed the properties of interfaces in 3D printed composites combining experiments with computer simulations. To investigate photopolymer blending, we characterized the mechanical properties of the so-called digital materials, obtained by mixing compliant and stiff voxels according to different volume fractions. We then used nanoindentation to measure the spatial variation in mechanical properties across bimaterial interfaces at the micrometer level. Finally, to characterize the impact of finite-size interfaces, we fabricated and tested composites having compliant and stiff layers alternating along different directions. We found that interfaces formed by deposition after curing were sharp whereas those formed before curing showed blending of the two materials over a length scale bigger than individual droplet size. We found structural and functional differences of the layered composites depending on the printing orientation and corresponding interface characteristics, which influenced deformation mechanisms. With the wide dissemination of 3D printing techniques, our results should be considered in the development of architectured materials with tailored interfaces between building blocks.

Bioinspired Compliance Grading Motif of Mortar in Nacreous Materials

The impressive toughness and strength of natural nacre, attributed to its multi-scale and -material hierarchical architecture, has inspired biomimicry and bioinspired materials development, and here we show that material compliance gradients are a motif that can help explain their advantaged mechanical performance. We present experiments enabled via additive manufacturing that allow direct evaluation of a compliance grading motif of the mortar between the relatively stiff bricks of the nacreous material. Spatial grading of the mortar compliance redistributes stresses away from critical regions (at, and around, brick corners), resulting in overall increases of ∼60% in strength, ∼ 70% in toughness, and ∼30% in strain-to-break, while maintaining macroscopic stiffness. Mechanistically, failure initiation threshold is delayed due to enhanced strain-tolerance and strain-localization as revealed in prefailure experimental strain maps, and in agreement with numerical analyses. We further demonstrate that this modulus grading motif, beyond the stiffness mismatch between the brick and mortar periodic architecture, is a significant contributor to the performance of the much-studied nacreous systems and is suggested as a natural but overlooked mechanism in such systems.

Soft Defect-Tolerant Material Inspired by American Lobsters

The joint membrane of the American lobster shows an excellent combination of high strength, toughness, and defect tolerance due to the periodic helicoidal stacking of the fiber layers that are connected by a weak continuous matrix. Inspired by the joint membrane of American lobsters, we simply use nonwoven fabrics and silicon rubber to fabricate a multilayer soft composite with the helicoidal stacking and controllable matrix. The influences of stacking structure, matrix strength, fabrics strength, and notch size on the fracture behavior of the soft composite during the tensile process are systematically analyzed by both experimental tests and finite element analysis (FEA). We find that similar to the joint membrane, the soft composite demonstrates a gradual failure process and a linear relationship between tensile strength/toughness and notch size. Such phenomena demonstrate the strong defect-tolerant ability, thereby imparting the soft composite with both high strength and toughness. The defect-tolerant ability is closely related to the helicoidal stacking and weak matrix between the fabrics layers, which induce crack deflection and inhibit the propagation of cracks across the sample.

Historical Review of Combined Experimental and Computational Approaches for Investigating Annulus Fibrosus Mechanics

Intervertebral disc research has sought to develop a deeper understanding of spine biomechanics, the complex relationship between disc health and back pain, and the mechanisms of spinal injury and repair. To do so, many researchers have focused on characterizing tissue-level properties of the disc, where the roles of tissue subcomponents can be more systematically investigated. Unfortunately, experimental challenges often limit the ability to measure important disc tissue- and subtissue-level behaviors, including fiber–matrix interactions, transient nutrient and electrolyte transport, and damage propagation. Numerous theoretical and numerical modeling frameworks have been introduced to explain, complement, guide, and optimize experimental research efforts. The synergy of experimental and computational work has significantly advanced the field, and these two aspects have continued to develop independently and jointly. Meanwhile, the relationship between experimental and computational work has become increasingly complex and interdependent. This has made it difficult to interpret and compare results between experimental and computational studies, as well as between solely computational studies. This paper seeks to explore issues of model translatability, robustness, and efficient study design, and to propose and motivate potential future directions for experimental, computational, and combined tissue-level investigations of the intervertebral disc.

Algorithmic-driven design of shark denticle bioinspired structures for superior aerodynamic properties

All engineering systems that move through fluids can benefit from a reduction in opposing forces, or drag. As a result, there is a significant focus on finding new ways to improve the lift-to-drag ratios of systems that move through fluids. Nature has proven to be an extremely beneficial source of inspiration to overcome current technical endeavors. Shark skin, with its low-drag riblet structure, is a prime example of an evolutionary design that has inspired new implementations of drag reducing technologies. Previously, it has been shown that denticles have drag reducing properties when applied to airfoils and other surfaces moving through fluids. Researchers have been able to mimic the structure of shark skin, but minimal work has been done in terms of optimizing the design of the denticles due to the large number of parameters involved. In this work, we use a combination of computational fluid dynamics simulations and optimization methods to optimize the size and shape of shark skin denticles in order to decrease drag. Results show that by changing the size, shape, and orientation of the denticles, the boundary layer can be altered, and thereby reduce drag. This research demonstrates that denticles play a similar role as vortex generators in energizing the boundary layer to decrease drag. These mechanisms, along with the fundamental knowledge gained through the study of these drag reducing structures can be applied to a vast number of fields including aeronautical, oceanic, and automotive engineering.

Allogenic tooth transplantation using 3D printing: A case report and review of the literature

BACKGROUND

The history of allogenic tooth transplantation can be traced back to the 16^th century. Although there have been many successful cases, much needs to be better understood and researched prior to the technique being translated to everyday clinical practice.

CASE SUMMARY

In the present report, we describe a case of allogenic tooth transplantation between a mother and her daughter. The first left maxillary molar of the mother was diagnosed with residual root resorption and needed to be extracted. The 3^rd molar of the daughter was used as a donor tooth. Prior to transplantation, a 3D printing system was introduced to fabricate an individualized reamer drill specifically designed utilizing the donor’s tooth as a template. The specific design of our 3D printed bur allowed for the recipient site to better match the donor tooth. With the ability to 3D print in layers, even the protuberance of the root can be matched and 3D printed, thereby minimizing unnecessary bone loss.

CONCLUSION

Our study is a pioneering case combining 3D printing with allogenic tooth transplantation, which could be able to minimize unnecessary bone loss and improve the implant stability. This article aims to enhance our understanding of allogenic tooth transplantation and 3D printing, and may potentially lead to tooth transplantation being utilized more frequently - especially since transplantations are so commonly utilized in many other fields of medicine with high success rates.

Impact resistance of nanocellulose films with bioinspired Bouligand microstructures

The Bouligand structure features a helicoidal (twisted plywood) layup of fibers that are uniaxially arranged in-plane and is a hallmark of biomaterials that exhibit outstanding impact resistance. Despite its performance advantage, the underlying mechanisms for its outstanding impact resistance remain poorly understood, posing challenges for optimizing the design and development of bio-inspired materials with Bouligand microstructures. Interestingly, many bio-sourced nanomaterials, such as cellulose nanocrystals (CNCs), readily self-assemble into helicoidal thin films with inter-layer (pitch) angles tunable via solvent processing. Taking CNC films as a model Bouligand system, we present atomistically-informed coarse-grained molecular dynamics simulations to measure the ballistic performance of thin films with helicoidally assembled nanocrystals by subjecting them to loading similar to laser-induced projectile impact tests. The effect of pitch angle on the impact performance of CNC films was quantified in the context of their specific ballistic limit velocity and energy absorption. Bouligand structures with low pitch angles (18-42°) were found to display the highest ballistic resistance, significantly outperforming other pitch angle and quasi-isotropic baseline structures. Improved energy dissipation through greater interfacial sliding, larger in-plane crack openings, and through-thickness twisting cracks resulted in improved impact performance of optimal pitch angle Bouligand CNC films. Intriguingly, decreasing interfacial interactions enhanced the impact performance by readily admitting dissipative inter-fibril and inter-layer sliding events without severe fibril fragmentation. This work helps reveal structural and chemical factors that govern the optimal mechanical design of Bouligand microstructures made from high aspect ratio nanocrystals, paving the way for sustainable, impact resistant, and multi-functional films.

Bone-inspired enhanced fracture toughness of de novo fiber reinforced composites

Amplification in toughness and balance with stiffness and strength are fundamental characteristics of biological structural composites, and a long sought-after objective for engineering design. Nature achieves these properties through a combination of multiscale key features. Yet, emulating all these features into synthetic de novo materials is rather challenging. Here, we fine-tune manual lamination, to implement a newly designed bone-inspired structure into fiber-reinforced composites. An integrated approach, combining numerical simulations, ad hoc manufacturing techniques, and testing, yields a novel composite with enhanced fracture toughness and balance with stiffness and strength, offering an optimal lightweight material solution with better performance than conventional materials such as metals and alloys. The results also show how the new design significantly boosts the fracture toughness compared to a classic laminated composite, made of the same building blocks, also offering an optimal tradeoff with stiffness and strength. The predominant mechanism, responsible for the enhancement of fracture toughness in the new material, is the continuous deviation of the crack from a straight path, promoting large energy dissipation and preventing a catastrophic failure. The new insights resulting from this study can guide the design of de novo fiber-reinforced composites toward better mechanical performance to reach the level of synergy of their natural counterparts.

Additive Manufacturing as a Method to Design and Optimize Bioinspired Structures

Additive manufacturing (AM) is a current technology undergoing rapid development that is utilized in a wide variety of applications. In the field of biological and bioinspired materials, additive manufacturing is being used to generate intricate prototypes to expand our understanding of the fundamental structure-property relationships that govern nature's spectacular mechanical performance. Herein, recent advances in the use of AM for improving the understanding of the structure-property relationship in biological materials and for the production of bioinspired materials are reviewed. There are four essential components to this work: a) extracting defining characteristics of biological designs, b) designing 3D-printed prototypes, c) performing mechanical testing on 3D-printed prototypes to understand fundamental mechanisms at hand, and d) optimizing design for tailorable performance. It is intended to highlight how the various types of additive manufacturing methods are utilized, to unravel novel discoveries in the field of biological materials. Since AM processing techniques have surpassed antiquated limitations, especially with respect to spatial scales, there has been a surge in their demand as an integral tool for research. In conclusion, current challenges and the technical perspective for further development of bioinspired materials using AM are discussed.

Imaging and analysis of a three-dimensional spider web architecture

Spiders are abundantly found in nature and most ecosystems, making up more than 47 000 species. This ecological success is in part due to the exceptional mechanics of the spider web, with its strength, toughness, elasticity and robustness, which originate from its hierarchical structures all the way from sequence design to web architecture. It is a unique example in nature of high-performance material design. In particular, to survive in different environments, spiders have optimized and adapted their web architecture by providing housing, protection, and an efficient tool for catching prey. The most studied web in literature is the two-dimensional (2D) orb web, which is composed of radial and spiral threads. However, only 10% of spider species are orb-web weavers, and three-dimensional (3D) webs, such as funnel, sheet or cobwebs, are much more abundant in nature. The complex spatial network and microscale size of silk fibres are significant challenges towards determining the topology of 3D webs, and only a limited number of previous studies have attempted to quantify their structure and properties. Here, we focus on developing an innovative experimental method to directly capture the complete digital 3D spider web architecture with micron scale resolution. We built an automatic segmentation and scanning platform to obtain high-resolution 2D images of individual cross-sections of the web that were illuminated by a sheet laser. We then developed image processing algorithms to reconstruct the digital 3D fibrous network by analysing the 2D images. This digital network provides a model that contains all of the structural and topological features of the porous regions of a 3D web with high fidelity, and when combined with a mechanical model of silk materials, will allow us to directly simulate and predict the mechanical response of a realistic 3D web under mechanical loads. Our work provides a practical tool to capture the architecture of sophisticated 3D webs, and could lead to studies of the relation between architecture, material and biological functions for numerous 3D spider web applications.

Design of a Scaffold Parameter Selection System with Additive Manufacturing for a Biomedical Cell Culture

Open-source 3D printers mean objects can be quickly and efficiently produced. However, design and fabrication parameters need to be optimized to set up the correct printing procedure; a procedure in which the characteristics of the printing materials selected for use can also influence the process. This work focuses on optimizing the printing process of the open-source 3D extruder machine RepRap, which is used to manufacture poly(ε-caprolactone) (PCL) scaffolds for cell culture applications. PCL is a biocompatible polymer that is free of toxic dye and has been used to fabricate scaffolds, i.e., solid structures suitable for 3D cancer cell cultures. Scaffold cell culture has been described as enhancing cancer stem cell (CSC) populations related to tumor chemoresistance and/or their recurrence after chemotherapy. A RepRap BCN3D+ printer and 3 mm PCL wire were used to fabricate circular scaffolds. Design and fabrication parameters were first determined with SolidWorks and Slic3r software and subsequently optimized following a novel sequential flowchart. In the flowchart described here, the parameters were gradually optimized step by step, by taking several measurable variables of the resulting scaffolds into consideration to guarantee high-quality printing. Three deposition angles (45°, 60° and 90°) were fabricated and tested. MCF-7 breast carcinoma cells and NIH/3T3 murine fibroblasts were used to assess scaffold adequacy for 3D cell cultures. The 60° scaffolds were found to be suitable for the purpose. Therefore, PCL scaffolds fabricated via the flowchart optimization with a RepRap 3D printer could be used for 3D cell cultures and may boost CSCs to study new therapeutic treatments for this malignant population. Moreover, the flowchart defined here could represent a standard procedure for non-engineers (i.e., mainly physicians) when manufacturing new culture systems is required.

Solution Mask Liquid Lithography (SMaLL) for One-Step, Multimaterial 3D Printing

A novel methodology for printing 3D objects with spatially resolved mechanical and chemical properties is reported. Photochromic molecules are used to control polymerization through coherent bleaching fronts, providing large depths of cure and rapid build rates without the need for moving parts. The coupling of these photoswitches with resin mixtures containing orthogonal photo-crosslinking systems allows simultaneous and selective curing of multiple networks, providing access to 3D objects with chemically and mechanically distinct domains. The power of this approach is showcased through the one-step fabrication of bioinspired soft joints and mechanically reinforced "brick-and-mortar" structures.

Recent Progress in Biomimetic Additive Manufacturing Technology: From Materials to Functional Structures

Nature has developed high-performance materials and structures over millions of years of evolution and provides valuable sources of inspiration for the design of next-generation structural materials, given the variety of excellent mechanical, hydrodynamic, optical, and electrical properties. Biomimicry, by learning from nature's concepts and design principles, is driving a paradigm shift in modern materials science and technology. However, the complicated structural architectures in nature far exceed the capability of traditional design and fabrication technologies, which hinders the progress of biomimetic study and its usage in engineering systems. Additive manufacturing (three-dimensional (3D) printing) has created new opportunities for manipulating and mimicking the intrinsically multiscale, multimaterial, and multifunctional structures in nature. Here, an overview of recent developments in 3D printing of biomimetic reinforced mechanics, shape changing, and hydrodynamic structures, as well as optical and electrical devices is provided. The inspirations are from various creatures such as nacre, lobster claw, pine cone, flowers, octopus, butterfly wing, fly eye, etc., and various 3D-printing technologies are discussed. Future opportunities for the development of biomimetic 3D-printing technology to fabricate next-generation functional materials and structures in mechanical, electrical, optical, and biomedical engineering are also outlined.

Materials-by-Design: Computation, Synthesis, and Characterization from Atoms to Structures

In the 50 years that succeeded Richard Feynman's exposition of the idea that there is "plenty of room at the bottom" for manipulating individual atoms for the synthesis and manufacturing processing of materials, the materials-by-design paradigm is being developed gradually through synergistic integration of experimental material synthesis and characterization with predictive computational modeling and optimization. This paper reviews how this paradigm creates the possibility to develop materials according to specific, rational designs from the molecular to the macroscopic scale. We discuss promising techniques in experimental small-scale material synthesis and large-scale fabrication methods to manipulate atomistic or macroscale structures, which can be designed by computational modeling. These include recombinant protein technology to produce peptides and proteins with tailored sequences encoded by recombinant DNA, self-assembly processes induced by conformational transition of proteins, additive manufacturing for designing complex structures, and qualitative and quantitative characterization of materials at different length scales. We describe important material characterization techniques using numerous methods of spectroscopy and microscopy. We detail numerous multi-scale computational modeling techniques that complements these experimental techniques: DFT at the atomistic scale; fully atomistic and coarse-grain molecular dynamics at the molecular to mesoscale; continuum modeling at the macroscale. Additionally, we present case studies that utilize experimental and computational approaches in an integrated manner to broaden our understanding of the properties of two-dimensional materials and materials based on silk and silk-elastin-like proteins.

Rapid generation of three-dimensional microchannels for vascularization using a subtractive printing technique

The development of tissue-engineered products has been limited by lack of a perfused microvasculature that delivers nutrients and maintains cell viability. Current strategies to promote vascularization such as additive three-dimensional printing techniques have limitations. This study validates the use of an ultra-fast laser subtractive printing technique to generate capillary-sized channels in hydrogels prepopulated with cells by demonstrating cell viability relative to the photodisrupted channels in the gel. The system can move the focal spot laterally in the gel at a rate of 2500 mm/s by using a galvanometric scanner to raster the in plane focal spot. A Galilean telescope allows z-axis movement. Blended hydrogels of polyethylene glycol and collagen with a range of optical clarities, mechanical properties and swelling behavior were tested to demonstrate that the subtractive printing process for writing vascular channels is compatible with all of the blended hydrogels tested. Channel width and patterns were controlled by adjusting the laser energy and focal spot positioning, respectively. After treatment, high cell viability was observed at distances greater than or equal to 18 μm from the fabricated channels. Overall, this study demonstrates a flexible technique that has the potential to rapidly generate channels in tissue-engineered constructs.

Modular Elastomer Photoresins for Digital Light Processing Additive Manufacturing

A series of photoresins suitable for the production of elastomeric objects via digital light processing additive manufacturing are reported. Notably, the printing procedure is readily accessible using only entry-level equipment under ambient conditions using visible light projection. The photoresin formulations were found to be modular in nature, and straightforward adjustments to the resin components enabled access to a range of compositions and mechanical properties. Collectively, the series includes silicones, hydrogels, and hybrids thereof. Printed test specimens displayed maximum elongations of up to 472% under tensile load, a tunable swelling behavior in water, and Shore A hardness values from 13.7 to 33.3. A combination of the resins was used to print a functional multimaterial three-armed pneumatic gripper. These photoresins could be transformative to advanced prototyping applications such as simulated human tissues, stimuli-responsive materials, wearable devices, and soft robotics.

A bioinspired study on the compressive resistance of helicoidal fibre structures

Helicoidal fibre structures are widely observed in natural materials. In this paper, an integrated experimental and analytical approach was used to investigate the compressive resistance of helicoidal fibre structures. First, helicoidal fibre-reinforced composites were created using three-dimensionally printed helicoids and polymeric matrices, including plain, ring-reinforced and helix-reinforced helicoids. Then, load-displacement curves under monotonic compression tests were collected to measure the compressive strengths of helicoidal fibre composites. Fractographic characterization was performed using an X-ray microtomographer and scanning electron microscope, through which crack propagations in helicoidal structures were illustrated. Finally, mathematical modelling was performed to reveal the essential fibre architectures in the compressive resistance of helicoidal fibre structures. This work reveals that fibre-matrix ratios, helix pitch angles and interlayer rotary angles are critical to the compressive resistance of helicoidal structures.

Design for Additive Bio-Manufacturing: From Patient-Specific Medical Devices to Rationally Designed Meta-Biomaterials

Recent advances in additive manufacturing (AM) techniques in terms of accuracy, reliability, the range of processable materials, and commercial availability have made them promising candidates for production of functional parts including those used in the biomedical industry. The complexity-for-free feature offered by AM means that very complex designs become feasible to manufacture, while batch-size-indifference enables fabrication of fully patient-specific medical devices. Design for AM (DfAM) approaches aim to fully utilize those features for development of medical devices with substantially enhanced performance and biomaterials with unprecedented combinations of favorable properties that originate from complex geometrical designs at the micro-scale. This paper reviews the most important approaches in DfAM particularly those applicable to additive bio-manufacturing including image-based design pipelines, parametric and non-parametric designs, metamaterials, rational and computationally enabled design, topology optimization, and bio-inspired design. Areas with limited research have been identified and suggestions have been made for future research. The paper concludes with a brief discussion on the practical aspects of DfAM and the potential of combining AM with subtractive and formative manufacturing processes in so-called hybrid manufacturing processes.

Hierarchically Enhanced Impact Resistance of Bioinspired Composites

An order of magnitude tougher than nacre, conch shells are known for being one of the toughest body armors in nature. However, the complexity of the conch shell architecture creates a barrier to emulating its cross-lamellar structure in synthetic materials. Here, a 3D biomimetic conch shell prototype is presented, which can replicate the crack arresting mechanisms embedded in the natural architecture. Through an integrated approach combining simulation, additive manufacturing, and drop tower testing, the function of hierarchy in conch shell's multiscale microarchitectures is explicated. The results show that adding the second level of cross-lamellar hierarchy can boost impact performance by 70% and 85% compared to a single-level hierarchy and the stiff constituent, respectively. The overarching mechanism responsible for the impact resistance of conch shell is the generation of pathways for crack deviation, which can be generalized to the design of future protective apparatus such as helmets and body armor.

Mechanical properties of crossed-lamellar structures in biological shells: A review

The self-fabrication of materials in nature offers an alternate and powerful solution towards the grand challenge of designing advanced structural materials, where strength and toughness are always mutually exclusive. Crossed-lamellar structures are the most common microstructures in mollusks that are composed of aragonites and a small amount of organic materials. Such a distinctive composite structure has a fracture toughness being much higher than that of pure carbonate mineral. These structures exhibiting complex hierarchical microarchitectures that span several sub-level lamellae from microscale down to nanoscale, can be grouped into two types, i.e., platelet-like and fiber-like crossed-lamellar structures based on the shapes of basic building blocks. It has been demonstrated that these structures have a great potential to strengthen themselves during deformation. The observed underlying toughening mechanisms include microcracking, channel cracking, interlocking, uncracked-ligament bridging, aragonite fiber bridging, crack deflection and zig-zag, etc., which play vital roles in enhancing the fracture resistance of shells with the crossed-lamellar structures. The exploration and utilization of these important toughening mechanisms have attracted keen interests of materials scientists since they pave the way for the development of bio-inspired advanced composite materials for load-bearing structural applications. This article is aimed to review the characteristics of hierarchical structures and the mechanical properties of two kinds of crossed-lamellar structures, and further summarize the latest advances and biomimetic applications based on the unique crossed-lamellar structures.

Nanomechanics of silk: the fundamentals of a strong, tough and versatile material

Spider silk is a remarkable material that provides a template for upscaling molecular properties to the macroscale. In this article we review fundamental aspects of the mechanisms behind these behaviors, discuss the molecular makeup, chemical designs, and how these integrate in a complex arrangement to form webs, cocoons and other material architectures. Moreover, this review paper explores the unique ability of silk to tolerate various kinds of defects, in a way enabling this material platform to serve as one of the most resilient materials in nature. We conclude the discussion with a summary of key scaling laws, an attempt model and define hierarchical length-scales, and the translation to synthetic materials.