Additive Manufacturing Technology E-Book
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- Herausgeber: Wiley-VCH GmbH
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- Sprache: Englisch
Additive Manufacturing Technology
Highly comprehensive resource covering all key aspects of the current developments of additive manufacturing
Additive Manufacturing Technology: Design, Optimization, and Modeling provides comprehensive and in-depth knowledge of the latest advances in various additive manufacturing technologies for polymeric materials, metals, multi-materials, functionally graded materials, and cell-laden bio-inks. It also details the application of numerical modeling in facilitating the design and optimization of materials, processes, and printed parts in additive manufacturing.
The topics covered in this book include:
- Fundamentals and applications of 4D printing, 3D bioprinting of cell-laden bio-inks, and multi-material additive manufacturing
- Alloy design for metal additive manufacturing, mechanisms of metallurgical defect formation, and the mechanical properties of printed alloys
- Modified inherent strain method for the rapid prediction of residual stress and distortion within parts fabricated by additive manufacturing
- Modeling of the different stages in polymer and metal additive manufacturing processes, including powder spreading, melting, and thermal stress evolution
By providing extensive coverage of highly relevant concepts and important topics in the field of additive manufacturing, this book highlights its essential role in Industry 4.0 and serves as a valuable resource for scientists, engineers, and students in materials science, engineering, and biomedicine.
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Veröffentlichungsjahr: 2022
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Table of Contents
Cover
Title Page
Copyright
Preface
1 Introduction to 4D Printing: Concepts and Material Systems
1.1 Background
1.2 Overview of 3D Printing Techniques
1.3 Shape‐Programmable Materials for 4D Printing
1.4 Modeling‐Guided Design for 4D Printing
1.5 Summary and Outlook
Acknowledgments
References
2 Strategies in 3D Bioprinting of Cell‐Laden Bioinks
2.1 Introduction
2.2 Drop‐on‐Demand (DOD)‐Based Inkjet Printing
2.3 Laser Printing
2.4 Support Bath‐Enabled Printing‐then‐Solidification Extrusion
2.5 Continuous Precuring Digital Light Processing (DLP) Printing
2.6 Summary
References
3 Alloy Design for Metal Additive Manufacturing
3.1 Additive Manufacturing
3.2 Melting and Cooling Processes and Associated Defects
3.3 Alloy Design Methodology
3.4 Summary
Abbreviations
References
4 Laser and Arc‐Based Methods for Additive Manufacturing of Multiple Material Components – From Design to Manufacture
4.1 Background
4.2 MMAM components design
4.3 Multi‐material L‐DED
4.4 Multi‐material L‐PBF
4.5 Multi‐Material WAAM
4.6 Comparison of Multi‐Material AM Technologies
4.7 Potential Applications of Multi‐Material AM
4.8 Challenges of Multi‐Material AM Technologies
4.9 Summary and Outlook
References
5 Modified Inherent Strain Method for Predicting Residual Deformation and Stress in Metal Additive Manufacturing
5.1 Background
5.2 Modified Inherent Strain (MIS) Method
5.3 Extraction of ISs for L‐PBF Process
5.4 Governing Equations for MIS‐Based Sequential Analysis
5.5 Experimental Validation: Double Cantilever Beam
5.6 Simulation‐Driven Design for L‐PBF Process
5.7 Summary and Outlook
Acknowledgment
References
6 High‐Fidelity Modeling of Metal Additive Manufacturing
6.1 Background
6.2 Powder Spreading
6.3 Powder Melting
6.4 Thermal Stress
6.5 Modeling of Other Unique Phenomena
6.6 Conclusions
Appendix 6.A Material Properties for Thermal-Fluid Simulation
References
7 Modeling of Polymer Powder‐Based Additive Manufacturing
7.1 Background
7.2 Discrete Element Modeling of the Powder Recoating Process
7.3 Finite Element Modeling of the SLS Process
7.4 Summary and Outlook
References
Index
End User License Agreement
List of Tables
Chapter 3
Table 3.1 Minimum tensile requirements for alloys manufactured by LPBF at r...
Table 3.2 Compositions of Hastelloy X manufactured by LPBF with correspondi...
Table 3.3 Surface tension measurements on parabolic flights by the Thermola...
Chapter 4
Table 4.1 Classification of PBF and DED technologies involving either a las...
Table 4.2 Materials processed by AM technologies.
Table 4.3 Summary of multi‐material L‐DED investigations.
Table 4.4 Summary of multi‐material WAAM investigations.
Table 4.5 Comparison of multiple metallic material AM technologies.
Table 4.6 Potential applications for metal‐based multi‐material AM.
Table 4.7 Summary of defects reported in multi‐material L‐DED investigation...
Table 4.8 Summary of defects reported in multi‐material L‐PBF investigation...
Table 4.9 Typical defects in WAAM.
Chapter 5
Table 5.1 Maximum deformation (mm) in the build direction of the single‐wal...
Table 5.2 Comparison of the bending deformation of the double cantilever be...
Table 5.3 Default DMLS process parameters of the core‐skin mode for Ti64.
Table 5.4 Total deformations at the two ends of the double cantilever beam ...
Table 5.5 Computational time for simulation cases involving different numbe...
Table 5.6 Comparison of the compliance between the initial and optimized sc...
Chapter 6
Table 6.1 Physical parameters of 316L stainless steel powder particle in th...
Table 6.2 Results from Ge et al. [52], showing that the molten pool dimensi...
Table 6.3 Results from Yan et al. [41], showing the molten pool width obtai...
Table 6.4 Material parameters for different material states in the FEM mode...
Table 6.A.1 Material parameters of 316L stainless steel (SS316L)...
Chapter 7
Table 7.1 Predicted deformation ratio and experimental deformation ratios o...
List of Illustrations
Chapter 1
Figure 1.1 (a) Schematic illustration of 1D to 4D. (b) Flowchart showing the...
Figure 1.2 Schematic summary of the primary 3D printing techniques, various ...
Figure 1.3 Schematics of three major 3D printing techniques for polymers: ex...
Figure 1.4 Typical examples of multi‐material printing techniques. (a) Hybri...
Figure 1.5 Design examples of SMP for 4D printing of SMP. (a) The chemical s...
Figure 1.6 SMP composites with hybrid polymer network design. (a) Semi‐inter...
Figure 1.7 4D printing of SMP nanocomposites. (a) Schematics of extrusion of...
Figure 1.8 4D printing by printed active fiber‐reinforced composites. (a) Sc...
Figure 1.9 4D printing of SMP‐based bilayer composites. (a) Schematics of di...
Figure 1.10 4D printing by multi‐material SMPs. (a) Pictures showing the fol...
Figure 1.11 A typical example of 4D printing of single hydrogel and composit...
Figure 1.12 4D printing of multi‐material hydrogels. (a) Schematics of 3D‐pr...
Figure 1.13 Liquid crystal elastomer (LCE)‐based multi‐material 4D printing....
Figure 1.14 4D printing by MSMs‐based multi‐material. Schematic of the magne...
Figure 1.15 Simulation‐based design for 4D printing. (a) An FE‐based m...
Chapter 2
Figure 2.1 Scaffold‐based (a) and cell embedded (b) tissue engineering.
Figure 2.2 Four bioprinting technologies. (a) Inkjet printing; (b) laser pri...
Figure 2.3 Biofabrication window for the rational design of bioinks requirin...
Figure 2.4 Schematic diagram of inkjet‐based bioprinting system.
Figure 2.5 Recent progress of inkjet‐based bioprinting. (a) Inkjet‐printed m...
Figure 2.6 (a) Morphological features of a forming droplet. Jet/droplet morp...
Figure 2.7 Alginate microspheres embedded with living cells.
Figure 2.8 Representative images of microspheres and cell distribution in th...
Figure 2.9 Effect of cell concentration on the mean cell number within one m...
Figure 2.10 (a) Effect of polymer concentration on cell distribution. The ot...
Figure 2.11 Effect of excitation voltage on the mean cell number within one ...
Figure 2.12 Schematics of laser printing experimental setup.
Figure 2.13 (a) Laser printing printed human umbilical vein endothelial cell...
Figure 2.14 Time‐resolved representative images during laser printing of cel...
Figure 2.15 (a) Jet velocity and (b) printed droplet diameter of cell‐laden ...
Figure 2.16 Schematics illustrating the formation of different types of jets...
Figure 2.17 Schematic of (a) typical laser printing setup and (b) printing p...
Figure 2.18 Schematics of bifurcated construct printing (inset: a typical Y‐...
Figure 2.19 (a) Representative images of Y‐shaped alginate tubes printed usi...
Figure 2.20 Schematic of support bath‐enabled printing‐then‐solidification e...
Figure 2.21 Representative applications in cell printing. (a) Printed vessel...
Figure 2.22 Schematic of two‐step gelation approach based on reversible ther...
Figure 2.23 Y‐shaped alginate structure printing. (a) Illustration of the pr...
Figure 2.24 (a) Printed Y‐shaped cellular construct (scale bars: 1.0mm). (b...
Figure 2.25 Schematic of extrusion printing in a nanoclay bath of colloidal ...
Figure 2.26 Gelatin structure printing. (a) Gelatin structure printed and th...
Figure 2.27 Schematic of the DLP printer.
Figure 2.28 Research progress of DLP technology. (a) Continuous liquid inter...
Figure 2.29 (a) Schematic diagram of working curve and meaning of each param...
Figure 2.30 (a) Schematic of the beginning of curing with an infinitesimal t...
Figure 2.31 Schematic of the UV light energy distribution and accumulation i...
Figure 2.32 The basic steps of each printing circle of the conventional and ...
Figure 2.33 The total printing of the conventional and tunable pre‐curing DL...
Figure 2.34 (a) The CAD model of the pyramid model. (b, c, and d) The micros...
Figure 2.35 Representative live/dead fluorescence images of PC12 cells encap...
Chapter 3
Figure 3.1 (a) Number of yearly unit sales for metal printers (solid) and ma...
Figure 3.2 Typical fusion‐based AM processes: (a) powder bed fusion (PBF), (...
Figure 3.3 Process of alloy development for metal additive manufacturing.
Figure 3.4 Elongation and tensile strength of alloys manufactured by convent...
Figure 3.5 Martensitic transformation in Ti–6Al–4V under rapid cooling: (a) ...
Figure 3.6 Microstructure of as‐fabricated Ti–6Al–4V via LPBF (a) with multi...
Figure 3.7 Mechanical properties of Ti–6Al–4V reported in the literature. (a...
Figure 3.8 Compositional variations in Ti–6Al–4V: (a) Aluminum content in LP...
Figure 3.9 (a) Fraction of research on Ni‐based superalloys in powder bed fu...
Figure 3.10 Mechanical properties of Hastelloy‐X reported in the literature....
Figure 3.11 Mechanical properties of IN718 reported in the literature. (a) Y...
Figure 3.12 Mechanical properties corresponding to different sample orientat...
Figure 3.13 Mechanical properties corresponding to different sample orientat...
Figure 3.14 Time sequence of melt pool formation in 316L at laser powder of ...
Figure 3.15 (a) Schematic of defects formation locations in powder bed fusio...
Figure 3.16 Classification of defects in LPBF and factors that influence the...
Figure 3.17 (a) Absorptivity of incident photons onto a metallic surface as ...
Figure 3.18 Absorptivity of metal plates and powders under incident laser ra...
Figure 3.19 Interdependence between room‐temperature heat capacity (a), late...
Figure 3.20 Specific heat capacity of wrought 316L, IN718, and Ti–6Al–4V all...
Figure 3.21 (a) Thermal conductivity of LPBF processed and wrought 316L, Ti–...
Figure 3.22 Effect of surface tension – temperature dependence on the flow c...
Figure 3.23 (a) Vapor pressure of metallic elements at various temperatures....
Figure 3.24 Interdependence between room temperature thermal expansion coeff...
Figure 3.25 Linear thermal expansion of wrought 316L, IN718, and Ti–6Al–4V a...
Figure 3.26 (a) Correlation between the keyhole aspect ratio and keyhole num...
Figure 3.27 Relation between experimentally measured thermal strain in vario...
Figure 3.28 Schematic diagram of the modifying conventional powder for LPBF ...
Figure 3.29 (a) Scheil solidification curves for different Cu contents in Al...
Figure 3.30 (a) Influence of
and
on the phase stability of Ti alloys; (b...
Figure 3.31 (a, b) Computational alloy design spaces evaluated by Tang et al...
Figure 3.32 (a, b) Microstructure of as‐printed (AP) SB‐CoNi‐10 alloy develo...
Chapter 4
Figure 4.1 MMAM components design procedure.
Figure 4.2 (a) Typical DED system setup., deposition head configurations...
Figure 4.3 (a) Schematic diagram of the powder feeding system in an L‐DED se...
Figure 4.4 L‐DED‐processed (a) 304L–Inconel 625 FGM sample.
Figure 4.5 (a) The H13‐Cu FGM structure with the composition varying in 10% ...
Figure 4.6 A schematic diagram of a standard L‐PBF system.
Figure 4.7 (a1) Flow chart of ultrasonic‐assisted L‐PBF.
Figure 4.8 Processing routes for joining bimetallic materials.
Figure 4.9 (a) A schematic diagram of the cross‐finger structure at the mate...
Figure 4.10 (a) Top view and (b) cross section of a horizontal 316L/Cu10Sn F...
Figure 4.11 Morphological characteristics of a solidified Invar36/Cu10Sn pow...
Figure 4.12 Schematic diagrams of (a1) metal/ceramic building in layers, (a2...
Figure 4.13 (a1) A 316 L‐glass pendant, (a2) a Cu10Sn‐glass pendant.
Figure 4.14 (a1) and (a2) Cu‐PET‐SS components processed by inline integrate...
Figure 4.15 Printed Cu
10
Sn/PA11 (a) vertical FGM and (b) horizontal FGM. Pri...
Figure 4.16 An integrated DEM‐CFD modeling framework for multi‐track, multi‐...
Figure 4.17 (a) A schematic diagram of a typical WAAM system.
Figure 4.18 (a) The microstructure of the cross section of a Ti–Al alloy and...
Figure 4.19 (a) L‐DED‐manufactured aerospace shaft sleeve parts composed of ...
Chapter 5
Figure 5.1 Mechanical strain induced at a concerned material point during a ...
Figure 5.2 (a) Two‐layer representative volume with the bottom‐fixed substra...
Figure 5.3 Normal IS component distribution for Inconel 718 builds by the L‐...
Figure 5.4 Applying the ISs to a part‐scale model in a layer‐by‐layer fashio...
Figure 5.5 Double cantilever beam of Ti64 before and after cutting off the s...
Figure 5.6 Total deformation of Points #1 and #2 (see Figure 5.5) obtained b...
Figure 5.7 Workflow of the evaluation for cracking at solid/support interfac...
Figure 5.8 (a) Geometry of the fracture block sample, and (b) samples w/ and...
Figure 5.9 (a) Geometry of Sample A, (b) geometry of Sample B, (c) equivalen...
Figure 5.10 (a) Geometry of the fracture sample with a curved interface, (b)...
Figure 5.11 (a) Geometry of the bearing bracket, (b) evaluation of
J
‐integra...
Figure 5.12 Two designs for cracking prevention: (a) Design A where the latt...
Figure 5.13 Workflow of the support structure design for a practical compone...
Figure 5.14 (a) Geometry of the double cantilever beam and (b) voxel‐based m...
Figure 5.15 Optimization results of the double cantilever beam: (a) optimal ...
Figure 5.16 Four different support structure designs for double cantilever b...
Figure 5.17 Build for samples of the double cantilever beam printed out by E...
Figure 5.18 Experimental measurement for the distortion of the beams after c...
Figure 5.19 Full‐scale simulation results of the beams before cutting: (a) d...
Figure 5.20 (a) Geometry of the hip implant, (b) printed sample after cuttin...
Figure 5.21 (a, b) Initial setup of the L‐bracket optimization (Compliance 1...
Figure 5.22 Layer‐wise von Mises stress comparison before and after optimiza...
Figure 5.23 Layer‐wise scanning path of the L‐bracket for thermal stress min...
Figure 5.24 Layer‐wise stress comparison before and after optimization: (a) ...
Figure 5.25 (a) Optimized structure, (b) bottom layer stress distribution, a...
Chapter 6
Figure 6.1 An overview of the overall framework for high‐fidelity modeling o...
Figure 6.2 (a) Schematic of the two types of powder spreading mechanisms. Th...
Figure 6.3 Experimental validation of the DEM model in the rake‐type (a)–(d)...
Figure 6.4 (a) The stress defined as the total contact forces per unit volum...
Figure 6.5 Static and dynamic wall effects reduce the packing layer density....
Figure 6.6 The plot of
and
against particle size, showing the optimal si...
Figure 6.7 Percolation effect where ...
Figure 6.8 (a) Numerical simulation showing the powder dynamics during the s...
Figure 6.9 Variations of (a) mass flow rate
and (b) ratio of
with the sp...
Figure 6.10 (a) The tendency for the particles to adhere to the roller leads...
Figure 6.11 The contact force network of the powder pile at
.
Figure 6.12 The schematic of the ray‐tracing model. (a) The laser beam is di...
Figure 6.13 (a) Schematic of the electron–atom interaction model, with atoms...
Figure 6.14 Schematic of the evaporation model, and schematic of the Knudsen...
Figure 6.15 (a) The verification simulation for the ray‐tracing model where ...
Figure 6.16 Comparison of the recoil pressure ratio at different molten pool...
Figure 6.17 Comparison of molten pool and keyhole formation at different tim...
Figure 6.18 Shape of the molten pool at the same time frame (600
s). (a) an...
Figure 6.19 Comparison of the keyhole geometry feature of the current model ...
Figure 6.20 Experimental and simulation comparisons of the surface elevation...
Figure 6.21 An integrated modeling framework to perform a simulation of a si...
Figure 6.22 Comparison of melt pool geometry between (a) simulations and (b)...
Figure 6.23 Transition from continuous melt track to balling effect. As scan...
Figure 6.24 The time evolution of the flow pattern near a semi‐spherically m...
Figure 6.25 The fused zones with various scan paths of (a) single track, (b)...
Figure 6.26 Marangoni effect in molten pool flow causes the melt pool front ...
Figure 6.27 Schematic of the layer‐wise scan strategy of (a) rotated by
, a...
Figure 6.28 (a) Unidirectional case: A pore is observed between the centerli...
Figure 6.29 Schematic of the temperature interpolation between the CFD contr...
Figure 6.30 (a) Schematic of the quiet element model, within the defined dom...
Figure 6.31 (a) Comparison of the geometrical features and the temperature f...
Figure 6.32 (a) Thermal‐fluid simulation results. (b) The geometrical shape ...
Figure 6.33 The comparison of (a) the temperature and (b) stress distributio...
Figure 6.34 Comparison with crack observed in the SLM of Fe‐based metallic g...
Figure 6.35 Comparison with microcracks in AM tungsten by Vrancken et al. [6...
Figure 6.36 (a) The Bright‐Field Scanning Transmission Electron Microscopy i...
Figure 6.37 Thermal‐fluid flow simulation of liquid‐state sintering. (a) ini...
Figure 6.38 Phase‐field simulation of the solid‐state sintering of equal‐siz...
Figure 6.39 Phase‐field simulation of the solid‐state sintering of unequal‐s...
Figure 6.40 Denudation zones in simulations and experiments. Simulation: (a1...
Figure 6.41 Spattering phenomenon: (a1) side view and (a2) top view of the v...
Figure 6.42 (a) Temperature field of the ...
Figure 6.43 Simulation results of a “melt pool” with a moving hot spot with ...
Figure 6.44 Simulation results of the spattering and denudation phenomena at...
Chapter 7
Figure 7.1 Contact force model of two particles
i
and
j
[38, 39].
Figure 7.2 Morphology of polymer powder particles: (a) polyetherketone....
Figure 7.3 (a) Microscopic image of PA12 powder, (b) the particle size distr...
Figure 7.4 Different types of PEEK powder particles approximated from STL mo...
Figure 7.5 Multi‐sphere reconstruction of polymer powder particles: (a) PA11...
Figure 7.6 (a) SEM image of PA12 and glass fiber‐reinforced PA12 composite p...
Figure 7.7 AOR of the powder particles with different fiber loading
w
: (a) 0...
Figure 7.8 Effects of the aspect ratio of particles (
A
r
), spreader type (rol...
Figure 7.9 Powder beds of different powder layer thicknesses...
Figure 7.10 (a) Packing density and surface roughness versus the powder laye...
Figure 7.11 (a) Side and top views of the powder bed at different recoating ...
Figure 7.12 Powder beds with different recoating velocities
v
: (a) 0.05 m s
−
...
Figure 7.13 (a) Packing density and surface roughness versus the recoating v...
Figure 7.14 Powder beds with different fiber loading
w
: (a) 0, (b) 10%, (c) ...
Figure 7.15 (a) Packing density and surface roughness versus the fiber loadi...
Figure 7.16 (a) Surface roughness and (b) packing density of the powder beds...
Figure 7.17 Flowchart of the thermo‐mechanical finite element modeling for t...
Figure 7.18 Simulation model with three scanning tracks on the powder layer....
Figure 7.19 Microstructures of the sintered specimen on the
x–z
plane ...
Figure 7.20 3D finite element model of the SLS process for PEKK powder.
Figure 7.21 Temperature evolution on the powder bed under different laser po...
Figure 7.22 Diagram of the maximum temperature under different sets of laser...
Figure 7.23 Relationship between (a) the maximum temperature, and (b) the wi...
Figure 7.24 Diagram of (a) the available regions determined by two constrain...
Figure 7.25 Temperature evolution of the PA12 polymer during the cooling pro...
Figure 7.26 Evolution of the recrystallization degree at the center of the t...
Figure 7.27 Evolution of the recrystallization‐induced strain (
ɛ
re
) and...
Figure 7.28 Distribution of Mises stress and other two stress components....
Figure 7.29 Evolution of Mises stress during the cooling process.
Guide
Cover Page
Table of Contents
Title Page
Copyright
Preface
Begin Reading
Index
Wiley End User License Agreement
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Additive Manufacturing Technology
Design, Optimization, and Modeling
Edited byKun Zhou
Editor
Prof. Kun Zhou
Nanyang Technological University
Mechanical & Aerospace Engineering
50 Nanyang Avenue
639798 Singapore
Singapore
Cover Image: © Nordroden/Shutterstock
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Preface
Additive manufacturing (AM) covers a wide range of techniques capable of transforming digital models into solid objects through layer‐by‐layer accumulation of feedstock. The AM approach offers great flexibility in part design and enables the fabrication of complex parts without additional machining or tooling. Since the invention of the first AM technique in the 1980s, AM has undergone extensive development and become a disruptive technology capable of manufacturing products from a wide spectrum of materials, including polymers, metals, ceramics, composites, and biological materials. With the design freedom, high efficiency, ease of customization, and industrial‐grade part quality that it offers, the AM technology has gained the attention of numerous industries and has been increasingly employed to replace conventional manufacturing methods in commercial applications.
AM technology, with its tremendous untapped potential, is one of the fastest growing fields today. Extensive research has been dedicated to pursuing new discoveries and attaining new insights into various AM techniques to supplement our existing knowledge and further the advancement of the technology. In particular, the scientific community has placed significant emphasis on researching design, optimization, and modeling for AM. The development of novel material systems expands the selection of AM materials, which is advantageous for uncovering new scientific and industrial applications. Meanwhile, process optimization and modeling are also crucial research domains that provide a deeper understanding of the process mechanisms involved in AM techniques. This book reviews and discusses the latest developments in AM technology with a focus on material design, process optimization, and modeling.
Chapter 1 provides a brief introduction to four‐dimensional (4D) printing that utilizes programmable polymeric materials and advanced structural methodologies. The four major types of programmable polymers for 4D printing, namely, shape memory polymers, hydrogel composites, liquid crystal elastomers, and magnetoactive materials, are presented. The design methods and principles of controlling shape change in 4D printing are summarized, and the trends, prospects, and potential applications of 4D printing are discussed.
Chapter 2 covers the recent progress in four common 3D cell‐laden bioprinting technologies, namely, inkjet printing, laser printing, support bath‐enabled extrusion printing, and digital light processing printing. Various strategies implemented in these printing technologies that control and optimize the precision of cell deposition while ensuring cell viability and functionality are also discussed.
Chapter 3 grants an in‐depth understanding of the mechanisms for metallurgical defect formation of alloys and their mechanical properties in fusion‐based AM with an emphasis on powder‐bed fusion techniques. The development of methodologies to evaluate the suitability of designed alloys for fusion‐based AM is delineated.
Chapter 4 introduces multi‐material AM (MMAM) technologies and elucidates the design of MMAM‐processed components. The working principles of direct energy deposition (laser‐ and arc‐based) and laser powder‐bed fusion MMAM are explained, and the multi‐material feeding mechanisms and material properties of metal–metal, metal–ceramic, and metal–polymer interfaces are described. Specific challenges in materials science and engineering pertaining to different MMAM technologies are stated, followed by a summary and evaluation of the potential research directions in this area.
Chapter 5 presents a modified inherent strain method for the fast prediction of residual stress and distortion in metal parts fabricated by AM. Inherent strains are applied to a layerwise quasi‐static finite element analysis model to simulate residual stress and deformation evolution during the fabrication of the part by a heat source. Applications such as crack prevention, support structure optimization, and laser scanning path designs are described in several examples.
Chapter 6 introduces the high‐fidelity modeling of key aspects of metal AM, including powder spreading, powder pre‐sintering, powder melting, spattering, denudation, and thermal stress evolution. The underlying physical mechanisms at different stages of a printing process, as well as strategies for mitigating defect formation, are highlighted and discussed.
Chapter 7 reports the recent progress in modeling polymer powder‐based AM processes, in particular, powder recoating, melting, and cooling stages. A discrete element model for simulating powder recoating processes is introduced, and the effects of the recoating process parameters on powder‐bed quality are analyzed. Additionally, a finite‐element model for optimizing printing process parameters and predicting the temperature field, degree of recrystallization, and strain and stress fields within printed parts is presented.
I would like to thank the contributing authors of all the chapters and Lifen Yang and Katrina Maceda at Wiley‐VCH. I would also like to thank the members of my research group, with whom my discussions have always been fruitful. In particular, I appreciate the efforts of Changjun Han, Wei Zhu, Wei Shian Tey, Devesh Kripalani, Yujia Tian, Raj Kiran, Priyanka Vivegananthan, Han Zheng, Liming You, and Asker Jarlöv.
Kun Zhou
1Introduction to 4D Printing: Concepts and Material Systems
Xiao Kuang Liang Yue, and H. Jerry Qi
Georgia Institute of Technology, The George W. Woodruff School of Mechanical Engineering, 801 Ferst Dr., Atlanta, GA, 30332, USA
1.1 Background
In 2013, Tibbits introduced the concept of “four‐dimensional printing” (or 4D printing) [1]. He used an inkjet printer to print active (or programmable) polymer composites, whose shape could evolve with time under the water. Soon after, Qi and coworkers presented the concept of printed active composites (PACs), which can shift into various complex configurations by leveraging shape‐memory polymers (SMPs) [2]. These pioneering works open the new field of 4D printing, which attracts increasing attention in research communities and industry.
In Figure 1.1a, the schematic illustration shows the difference of structures from one‐dimensional (1D) to 4D. The structures show improved complexity in dimensions from 1D to three‐dimensional (3D). 4D printing is initially defined as “3D‐printed shape + time,” where the fourth dimension is time [2–6]. Currently, the definition of 4D printing has been broadened to include not only the shape but also the property and functionality of 3D‐printed structures that would change with time under a predetermined stimulus after printing. In 4D printing technique, stimuli‐responsive materials and proper structural design are usually used for 3D printing of shape‐programmable structures. Compared with conventional 3D‐printed static objects, 4D‐printed structures are able to change their shape, size, color, or other functional properties with time under external stimuli. The on‐demand shape and property changes after printing enable several prominent advantages. First, it allows the direct manufacturing of smart and intelligent structures/devices. Second, it saves printing time and materials, particularly, for thin‐wall structure fabrication. Third, it can save storage and transportation space for printed parts [7]. Due to these reasons, 4D printing has become a fast‐growing research field in various disciplines, such as smart materials and advanced manufacturing.
4D printing has witnessed significant progress during the past years, thanks to the tremendous advances in 3D printing techniques, stimuli‐responsive materials, and design and modeling‐based methods [3,8–11]. 3D printing, or additive manufacturing (AM), becomes a disruptive technology for advanced manufacturing [12, 13]. According to predetermined design models (such as computer‐aided design [CAD]), raw materials in various forms (powder, filament, or liquid) can be deposited by different printing modalities, such as extrusion‐based printing, inkjet‐based printing, and vat photopolymerization‐based printing (Figure 1.2). Notably, multi‐material 3D printing by constructing heterogeneous structures with spatial control of material distributions becomes a leading direction for 4D printing. Metals [14], ceramics [15, 16], and polymers [2, 4, 17] have been used for 4D printing. However, polymers are still the primary materials for 4D printing due to their cost‐effectiveness, diverse stimuli‐responding, and large deformability [14]. For example, shape‐programmable polymers can be engineered to respond to a wide range of physical and/or chemical stimuli, such as temperature, chemical, light, and magnetic field. The most extensively studied shape‐programmable smart polymers for 4D printing include SMPs, hydrogels, liquid crystal elastomers (LCEs), and magnetoactive soft materials (MSMs). The 4D‐printed structures with on‐demand complex geometry and stimuli‐responsive capability find applications in various fields, including actuators, soft robots, active metamaterials, smart electronics, self‐folding structures, biomedical devices, and tissue engineering [18–24]. The shape‐shifting performance of 4D‐printed structures is highly dependent on both the properties of shape‐programmable materials and structures. Several review papers in 4D printing can be found with different focuses on stimuli‐responsive materials [7, 25, 26], shape‐changing mechanisms [3, 27, 28], and applications [18, 29]. This chapter provides a fundamental understanding and recent advances in programmable polymeric material systems for 4D printing. It is organized by starting with an overview of 3D printing techniques, followed by the advances in smart material systems for 4D printing. Particular attention is paid to the use of the single‐material and multi‐material design of smart materials with different shape‐changing mechanisms for shape‐changing. In addition, we briefly introduce the modeling‐guided design for 4D printing to predict the shape‐shifting. To close, we discuss the major challenges and perspectives in 4D printing.
Figure 1.1 (a) Schematic illustration of 1D to 4D. (b) Flowchart showing the basic elements of 4D printing.
Source: Momeni et al. [3]/with permission of Elsevier.
Figure 1.2 Schematic summary of the primary 3D printing techniques, various shape‐programmable materials, and commonly used design approaches for 4D printing and their applications.
1.2 Overview of 3D Printing Techniques
According to International Organization for Standardization (ISO Technical Committee 261) and American Society for Testing and Materials (ASTM) International (Committee F42), AM technologies are classified into seven groups, including binder jetting, directed energy deposition, material extrusion, material jetting, powder bed fusion, sheet lamination, and vat photopolymerization [30]. In the following section, we introduce the 3D printing methods for polymers and composites most relevant to 4D printing. In most cases, 3D printers are only compatible with single‐material processing, meaning a single material is printed by one printing technique in one printing job. By contrast, multi‐material 3D printers have been developed to fabricate heterogeneous structures with precisely controlled materials distribution to manipulate more complex shape evolution and pathway.
1.2.1 Single‐Material 3D Printing Techniques
Extrusion‐based printing, inkjet printing, and vat photopolymerization‐based printing are extensively used 3D printing techniques for 4D printing (Figure 1.3). Among them, the most versatile printing technique is extrusion‐based printing, which constructs the 3D object in a line‐by‐line and then a layer‐by‐layer manner. Depending on the ink, extrusion‐based printing is divided into fused filament fabrication (FFF) (or fused deposition modeling [FDM]) and direct‐ink‐writing (DIW). In the FFF process, a solid filament is fed into a heating nozzle to form a polymer melt, which is continuously deposited onto a building tray with a controlled temperature and then solidified by environmental cooling. For example, engineering thermoplastics and composites, such as acrylonitrile butadiene styrene (ABS), polylactic acid (PLA), polyurethane (PU), as well as fiber or particle‐embedded composites, can be printed by FFF [32]. In FFF, residual stress usually exists due to the shearing and moving nozzle's temperature gradient and polymer chain alignment [33, 34]. This residual stress can be utilized to induce shape‐shifting by stress releasing after printing [35, 36]. For FFF‐based 4D printing, the shape memory effect (SME) of printed plastics is also frequently used to accommodate shape change [37]. By contrast, DIW uses a mechanical extruder or pressure to deposit paste or solution ink, solidified later by solvent evaporation, UV curing, or thermal curing. The prominent advantage of extrusion‐based methods is their applicability to a broad width of inks with different curing chemistry and viscosity. Assisted by post‐curing, DIW has been used to print different engineering thermosetting polymers [38–42], and functional materials, such as MSMs [43–47] and LCEs [48–53]. Compared with FFF printing with weak interfaces between filaments [54], DIW‐printed materials with post‐curing generally present a strong interface. The resolution of FFF and DIW is typically in the range of 100–200 μm, limited by the nozzle diameter. In addition, the extrusion‐based methods usually show a low printing speed due to the line‐by‐line fabrication manner.
Figure 1.3 Schematics of three major 3D printing techniques for polymers: extrusion‐based printing, inkjet‐based printing, and vat photopolymerization‐based printing.
Source: Kuang [31]/with permission of Elsevier.
Inkjet 3D printing is another popular method for photopolymer printing. During inkjet printing, photocurable ink drops (in the size of 20–40 μm) are deposited onto the building bed from printing nozzles controlled by the piezoelectric device, heating modules, or electromagnetic unit, followed by UV curing to form a solid layer [55]. The process is repeated until the whole structure is built. Various photocurable acrylate‐based monomers and crosslinkers are formulated as low‐viscosity inks to print materials with different properties [56]. Inkjet printing has high resolution with a typical in‐plane resolution of 30–40 μm [57]. Usually, a support material made of weak and water‐soluble polymer is used to allow complex structure printing. Despite its many advantages, inkjet printing suffers from the high equipment cost and the stringent requirement on ink viscosity [58].
Vat photopolymerization‐based printing is a fast‐growing method for 3D printing polymers. This printing technique includes several different printing modalities, including stereolithography (SLA), digital light processing (DLP), and two‐photon polymerization (TPP), which relies on the light to selectively cure photo‐sensitive polymer resins to build 3D structures. SLA is the earliest 3D printing method, which employs a UV laser beam to rapidly solidify the photopolymers inks [56, 57]. However, the line‐by‐line scanning‐based SLA printing is usually slow, especially in large part. By contrast, DLP exploits dynamic light patterns by digital micromirror devices (DMDs) to cure a layer of resin at a time, enabling fast printing [59]. The emergence of continuous liquid interface production (CLIP) is a breakthrough for DLP, which further enhances the printing speed and is among the fastest 3D printing technology suitable for large‐scale industrial production [60, 61]. CLIP uses an oxygen‐permeable film to form a dead zone between the transparent window and liquid, allowing continuous build stage elevation without ink renewal step. The in‐plane resolution of DLP falls in the range of 50–100 μm, determined by the DMDs and focusing lens used in the projector. By coupling a proper lens system with a DLP projector, micro‐DLP (μDLP; or projection micro‐stereolithography, PμSLA) has been developed to realize higher resolution up to 0.6 μm [59, 62]. Nanoscale printing resolution is achieved by using TPP‐based printing. The simultaneous absorption of two photons at the high‐intensity focal point of two lasers allows printing structures with a submicron resolution typically around 40–100 nm [63].
1.2.2 Multi‐Material 3D Printing
Driven by the need to fabricate heterogeneous functional structures and devices, multi‐material 3D printing has been developed and attracted great attention [64–69]. The direct approach to multi‐material printing uses multiple nozzle extruders [67,69–73]. Microfluidics‐extrusion [74] and micromixer‐based co‐extruders [66,75–77] have also been developed for extrusion‐based multi‐material printing. Espalin et al. [72] developed a multi‐material FFF system to print parts either using discrete multi‐materials or varying building processes. Recently, Lewis and coworkers developed a multi‐material multi‐nozzle DIW printing approach to realize high‐resolution, high‐speed multi‐material printing [67]. Besides, multi‐material DIW printing was achieved using photothermal dual‐cure resins [78].
The PolyJet technology by Stratasys enables inkjet printing of digital materials and multi‐materials using multiple print heads and inks [56]. To achieve this, multiple inks were deposited in a predetermined ratio and cured together, generating so‐called digital materials with digitalized mechanical properties within a certain range. This technique allows for the facile fabrication of parts composed of materials with widely tunable mechanical and thermomechanical properties [56, 57]. However, the resolution of multi‐material printing by PolyJet printer is reduced to 200–400 μm [79].
Multi‐material printing can be achieved by switchable multiple resin vats [80–82]. Wicker and coworker [80] utilized the scanning SLA system with multiple vat carousel designs to print 3D multi‐material objects. The process requires a cleaning step (in a cleaning vat) before being immersed in a different material vat to reduce contamination. Recently, Ge and coworkers developed multi‐material PμSLA printing by switching between different ink droplets and using high‐pressure air for surface cleaning [81, 82]. Instead of using multiple resin vats, single‐vat DLP printing of multi‐materials has been achieved by selective wavelength photocuring [83, 84], and grayscale printing [85, 86]. Particularly, grayscale DLP printing using grayscale images for spatially controlled light dose correlated with different crosslinking densities and mechanical properties. The monochromic images with grayscale red, green, and blue (RGB) values ranging from 255 to 0 (brightness from 1 to 0) indicate full light intensity to completely dark. By leveraging the material properties gradients by the grayscale DLP, various shape‐shifting materials using different mechanisms can be created for 4D printing [87–89].
Besides, integrated multiple printing technologies (or hybridizing) can provide or improve spatial control of material, geometry, and functionality. Early in 2005, Wicker's group [90] integrated commercial SLA machines with DIW for automated and efficient hybrid manufacturing of complex electrical devices. Recently, Peng et al. [91] reported a hybrid printing system consisting of top‐down DLP printing and DIW printing for multi‐material 3D printing (Figure 1.4a). The DLP module enabled high‐resolution, high‐speed printing of geometrical complex structures using various photopolymer inks. The DIW printing module was used for printing functional materials, such as LCEs and conductive silver ink. With this technique, multi‐material soft robots and actuators could be directly printed in one print job. Roach et al. [92] developed a multi‐material multi‐method (m4) AM platform by integrating four different printing modules (inkjet printing, FFF, DIW, and aerosol jetting), and robotic arms for pick‐and‐place (PnP), as well as intense pulsed light (IPL) sintering system (Figure 1.4b). With this platform, complex structures and functional devices, including actuators, soft robotics, and electronics, could be readily printed.
Figure 1.4 Typical examples of multi‐material printing techniques. (a) Hybrid 3D printer integrating top‐down DLP printing and DIW printing techniques.
Source: Peng et al. [91]/with permission of Elsevier.
(b) Picture of a multi‐material multi‐method 3D printing platform.
Source: Roach et al. [92]/with permission of Elsevier B.V.
1.3 Shape‐Programmable Materials for 4D Printing
Shape‐programmable materials are widely used as stimuli‐responsive materials for 4D printing. Four different types of shape‐programmable materials, namely SMPs, hydrogels, LCEs, and MSMs and their composites, are extensively studied [93]. These materials have different shape‐shifting mechanisms. SMPs are mechanically programmed in a temporary shape, which is triggered by external stimuli for shape recovery due to the entropic elasticity of the polymer network [94, 95]. Shape‐changing of hydrogels originates from water uptake/release by swelling and shrinkage under external stimuli [96]. LCEs enable reversible shape change via the phase transition between the nematic (N) state and isotropic (I) state [97, 98]. MSMs composed of magnetic particles embedding soft polymer matrix can undergo rapid and reversible shape actuation, owing to the interactions between magnetic particles and magnetic fields [99, 100]. Although there are some other materials and shape‐morphing mechanisms, such as polymerization‐induced volume shrinkage [87], evaporation‐induced shrinkage [101, 102], and thermal expansion mismatch [103], we will focus on using the aforementioned shape‐programmable materials for 4D printing in this chapter. This section will summarize advances in these shape‐programmable materials, and typical examples will be provided.
1.3.1 Shape‐Memory Polymers and Composites
SMPs are smart materials showing the SME, which has been extensively used for 4D printing. For SMPs, temporary shapes can first be programmed, and then the initial shape can be recovered in response to external stimuli, such as heat [104–109], solvent [110–114], and light [115–118]. Vernon first discovered the SME in 1941, when he used e‐beam or peroxide crosslinked high‐density polyethylene to make heat‐shrinkable tubes and films [119].
SME can be understood by the concept of “fixing phase” and “switching phase” [94, 95]. In the form of chemical or physical crosslinking points, the fixing phase can hold the permanent shape of the material. By contrast, the switching phase can be either phase level (amorphous and crystalline) or molecular level (supramolecular entities and reversible molecular units). The switching phase can transform between an active state and a frozen state featuring different chain mobility. The shape fixing and recovery of SMPs are realized by altering the chain mobility via applying and eliminating external stimuli. Heat is the most common trigger for SMPs, which can be achieved by direct heating or indirect heating [120]. Phase transition temperature (Tt), including glass transition temperature (Tg) and melting temperature (Tm), is employed by heating to trigger the shape change (or shape recovery) in SMPs. In thermally activated SMPs, the initial shape is in the thermodynamically stable conformation with the highest entropy. Chain mobility is significantly enhanced upon heating above Tt, allowing for deformation under external force. The programmed shapes possess lower entropy. When SMPs are cooled down to a temperature lower than Tt and undergo the phase transition (glass transition or crystallization), a metastable state with relatively low energy is obtained, leading to the temporary shape fixing of SMP. Upon reheating above Tt, SMPs regain high chain mobility for shape recovery driven by entropic elasticity.
1.3.1.1 Single SMP
Various semicrystalline polymers (such as PLA and PCL) [121, 122] and amorphous polymers (such as polyacrylate and epoxy) [123] with tunable thermomechanical properties have been used as thermally triggered SMPs, which are good candidates for [124] 4D printing. FFF can print physically crosslinked semicrystalline polymers for 4D printing, while chemically crosslinked amorphous SMPs with better shape memory performance are mainly printed via vat photopolymerization‐based techniques using various photopolymer inks. The Tg and stretchability of polyacrylate‐based photopolymers can be tuned by the rigidity of acrylate monomers and crosslinker content [124, 125]. For example, Ge et al. [68] used benzyl methacrylate (BMA) and different difunctional (meth)acrylates for high‐resolution PμSL printing of SMPs with tunable mechanical and thermomechanical properties (Figure 1.5a). The rubbery modulus increased from 1 to 100 MPa by increasing the crosslinker content. In addition, by using crosslinkers with different chain rigidity, the Tg of the polymer was tuned from −50 to 180 °C. However, the aforementioned methacrylate‐based resins required very high exposure energy (or light dose) to accommodate adequate curing due to slow crosslinking. Figure 1.5a also shows the shape recovery of 3D‐printed Eiffel Tower model from a programmed bent shape.
Figure 1.5Design examples of SMP for 4D printing of SMP. (a) The chemical structures of a rigid mono‐functional monomer of several and difunctional oligomers as crosslinkers for PμSL printing of SMPs. The printed high‐resolution Eiffel Tower with shape memory effect.
Source: Ge et al. [68]/with permission of Springer Nature.
(b) A microphase separation SMP can be printed by DLP via photopolymerization‐induced microphase separation. The use of the printed SMP with two different Tg for selective feeding process using triple SME devices.
Source: Peng et al. [126]/with permission of American Chemical Society.
Multiple shape‐shifting by multi‐SME in single‐material SMPs has also been achieved by 3D printing. For example, polymers with a broad phase transition temperature can realize multi‐SME [127–129]. Yu et al. [130] used Objet Connex printer material library to print a digital material Gray 60 with a broad Tg (a range of ∼40 °C) with multi‐SME. The printed SMP was programmed into different temporary shapes at different temperatures to obtain sequential shape‐changing. Recently, Peng et al. [126] reported the DLP printing of a microphase‐separated material for a triple SME. An ion–pair comonomer was introduced and served as a physical crosslinker in ink. The photopolymerization‐induced microphase separation could rapidly occur during printing, and two separated glass transition temperatures were obtained in the material. It was demonstrated that the printed microfluidic devices could be used as selective feeding devices using temperature‐dependent shape‐shifting (Figure 1.5b).
To enhance the properties of printed SMPs, inks can be rationally designed to modulate the material network architectures. To this end, the molecular engineering of interpenetrating polymer network (IPN) and semi‐interpenetrating polymer network (semi‐IPN) has been widely used. Kuang et al. [131] developed a new photopolymer ink containing aliphatic urethane diacrylate (AUD), n‐butyl acrylate, and semicrystalline polycaprolactone (PCL) as well as fumed silica (rheology modifier) for UV‐assisted DIW printing (Figure 1.6a). The composite ink was deposited at around 70 °C and then crosslinked by photocuring. The obtained semi‐IPN polymer composite contains a percolating network of nanoscale crystals and a covalent network. The loosely crosslinked chemical network and PCL crystals acted as fixing and switching phases for the SME with large deformation, respectively. Besides, the PCL nanocrystals played the role of a healing agent for material self‐healing. The SME could facilitate crack closing and assist the material healing process. It was shown shape memory tubular structures can be printed with on‐demand size for vascular repair applications (Figure 1.6b). Zhang et al. [132] used DLP for high‐resolution 4D printing using similar material systems. Similarly, PCL is incorporated into a methacrylate photopolymer ink for high‐resolution (up to 30 μm) printing of SMPs.
Figure 1.6 SMP composites with hybrid polymer network design. (a) Semi‐interpenetrating polymer network SMP was printed by UV‐assisted DIW printing [131]. (b) DIW‐printed tubes with shape memory effect [131]. (c) Interpenetrating polymer network SMP was printed by DIW via a photothermal dual‐cure approach [39]. (d) The results shape the recovery of printed epoxy SMP in a “GT” logo in an oil bath [39].
Source: (a) and (b) Kuang et al. [131]/with permission of American Chemical Society. (c) and (d) Chen et al. [39]/with permission of Royal Society of Chemistry.
IPN can be obtained by dual‐curing or photothermal two‐stage curing approaches. Yu et al. [133] reported the use of epoxy‐acrylate hybrid photopolymer to print SMP via the SLA 3D printing technique. A polyacrylate‐co‐epoxy particle was first performed and dispersed in epoxy resin to enhance the toughness. Then, both free radical and cationic initiators are used to simultaneously cure the acrylates and epoxy resin by UV irradiation during printing. Finally, the printed SMP shows good thermal stability, high strength, and good toughness. To further enhance the mechanical properties, dual‐stage curing was adopted to fabricate IPN [39, 134, 135]. Chen et al. [39] developed a hybrid ink containing photocurable acrylates and thermal‐curable epoxy for UV‐assisted DIW printing. The UV curing leads to a first polymer network in the green part, which is further treated with the second‐stage (thermal‐curing) to boost the mechanical properties (Figure 1.6c). The modulus and Tg of SMPs can be tuned by altering the ratio of the photocurable and thermal‐curable components. With this approach, IPN‐based SMPs with high toughness and high resolution can be printed (Figure 1.6d).
1.3.1.2 SMP Nanocomposites
Thermal activation of SMPs for shape change relies on thermal energy conduction for the material. As pure polymers usually possess low thermal conductivities, the shape recovery rate of large‐size SMPs is usually low. To improve the shape recovery speed of SMPs, indirect heating methods have been explored. This can be achieved by adding functional fillers or particulates into SMPs. The functional fillers transform stimuli (electrical, magnetic, or optical) into thermal energy for internal material heating. The SMP nanocomposites exhibit improved mechanical and multi‐stimuli‐responsive properties depending on the type and loading of the nanocomposites. The carbon‐based nanomaterials (i.e., carbon nanotube (CNT) and graphene oxide) and metal nanoparticles (i.e., gold and silver nanoparticles) have been used for photothermal heating of SMPs [136, 137]. For example, Yang et al. [137] used FFF printing to fabricate photoresponsive SMP containing /9 wt% carbon black (CB) in . Owing to the outstanding photothermal conversion efficiency of (92 ± 3%) [138], PU/CB composites showed high photothermal conversion efficiency. It was demonstrated the 3D‐printed sunflower with photoresponsive shape memory petals can be triggered to recover its original state with light illumination of 87 mW cm−2. Iron oxides (i.e., Fe2O3 and Fe3O4) and CNT have been used for inductive heating of SMPs by alternating magnetic fields [139–144]. As an example, Wei et al. [145] reported the DIW printing of UV‐curable PLA/Fe3O4 composite for thermally and remotely actuated SMP. The composite ink viscosity with added highly volatile solvent was extruded, followed by fast solvent removal and in situ UV curing (Figure 1.7a). The printed scaffolds with remote activation find potential biomedical applications as intravascular stents (Figure 1.7b). Similarly, Hua et al. [146] used FFF to print photoresponsive PLA/CNT SMP composites on paper substrates as photothermal‐responsive actuators. It is also noted that, instead of utilizing nanoparticles, selectively coating colorful inks on SMPs can also realize effective photothermal heating for the activation of SMPs [117, 118].
Figure 1.7 4D printing of SMP nanocomposites. (a) Schematics of extrusion of PLA/iron oxide composite ink with fast solvent evaporation and in situ UV crosslinking [145]. (b) Application demonstration of the 4D‐printed scaffold as an intravascular stent.
Source: Wei et al. [145]/with permission of American Chemical Society.
1.3.1.3 Printed Active Fiber‐Reinforced Composites
The SMP‐based PACs have been extensively studied for 4D printing [2]. The bilayered PACs, fabricated by a PolyJet printer, consist of parallel glassy polymer fibers (i.e., VeroWhite) embedded in a rubbery matrix (i.e., TangoBlack). The glassy polymer fiber is an SMP with a Tg of 60 °C. After printing, the bilayer lamina was trained for shape change by heating, stretching, cooling, and releasing sequence. Finally, the composite laminates turn to curled shapes due to the strain mismatch between the rubbery matrix and the glassy polymer fibers. By regulating fiber architecture and orientation, complex 3D configurations can be obtained, including bent, coiled, twisted, and folded shapes. The SMP composites laminates were used as smart hinges for active origami, morphing 2D structures into 3D architectures [17, 147]. Figure 1.8b shows a 2D origami airplane with PAC‐based smart hinges that can be morphed into a 3D‐shaped plane [17].
Figure 1.8 4D printing by printed active fiber‐reinforced composites. (a) Schematics of the laminate architectures and shape‐programming process of PAC.
Source: Ge et al. [2]/with permission of AIP Publishing LLC.
(b) A self‐folding airplane fabricated by printing different PACs as active hinges connecting inactive stiff plates.
Source: Qi et al. [17]/with permission of IOP Publishing.
(c) A smart hook realized by multi‐SME of PAC stripe at different temperatures.
Source: Wu et al. [148]/with permission of Springer Nature.
(d) Bending behavior of the multicolor PAC‐based SMP composites. The composite structure has bias‐distributed yellow fibers on the top and blue fibers on the bottom for selective heating under light with different wavelengths.
Source: Jeong et al. [149]/with permission of Springer Nature.
Similarly, Wu et al. [148] reported the use of PACs SMP composites that shows multiple shapes change via digital SMPs. Digital SMPs with tunable Tg were printed by digital material printing on an Objet Connex printer. To do so, two materials, including a rigid plastic (VeroWhite) and a soft rubber (TangoBlack), were jetted at specific ratios, followed by UV curing to print digital materials with different Tg. With this method, SMP fibers with different Tg were printed into laminated composite structures to achieve multiple and sequential shape‐shifting after a one‐step shape programming (Figure 1.8c). In addition, PACs with proper arrangements can be used for metamaterial lattice, tubular grippers, and stents for self‐expanding and self‐shrinking shape changes [150, 151]. More recently, Jeong et al. reported 4D printing of photoresponsive PACs using selective light absorption/heating in multi‐color PACs for remote‐controlled shape‐shifting [149]. The multi‐material 3D printer (Stratasys, J750) was used to print yellow fibers (VeroYellow) and blue fibers (VeroCyan) in a rubber‐like transparent material (Tango +), and the colored fibers were biasedly distributed on the top and bottom. The yellow fibers can absorb blue light, and the blue fiber absorbs red light for selective heating in the composites. As a result, the laminated composites bent to an n‐shape under the red light illumination and then recovered to an initial flat state by blue light illumination. The illumination blue‐red light sequence enabled the structure to bend to a U‐shape and recover to the initial state (Figure 1.8d).
1.3.1.4 Bilayer SMPs
Bilayer SMP composites made of SMPs as an active layer and passive rubbery layers are simple and versatile designs for shape‐shifting [152]. Besides, the bilayer can be used to realize direct 4D printing, where the residual stress can be incorporated during the printing or heating step without additional shape programming. Ding et al. [153] presented the direct 4D printing of bilayer laminate by an Objet 500 Connex3 printer (Stratasys). The bilayer strip was printed by VeroClear as the SMP and TangoBlack+ (or Tango+) as the elastomer. During printing, the elastomer layer contained a compressive strain regulated by printing parameters (such as the layer printing time). The release of the residual stress led to laminate bending into new permanent shapes (Figure 1.9a). Figure 1.9b shows some typical examples of direct 4D‐printed structures. The lattice with an unsymmetrical bilayer design was printed to achieve both expanding and bending upon heating. For example, upon heating, a printed flat star‐shaped laminated structure and multi‐layer flower could be deployed into a 3D dome shape and a blossom configuration, respectively. Ding et al. [155] further exploited the bilayer composite‐based rods for direct 4D printing. Besides, the thermal expansion mismatch between the rubber and SMP layer in printed bilayer composites could also be harnessed for shape change [156]. The morphed bilayer structures were stable even after being cooled down. These examples suggested a great advantage of the 4D printing technique, which can tremendously reduce the printing time and material consumption up to 70–90% for thin‐wall 3D structures.
Figure 1.9 4D printing of SMP‐based bilayer composites. (a) Schematics of direct 4D printing of multi‐material bilayer composites. (b) Similar lattice structure with both expanding and bending upon heating with the unsymmetrical architecture. A flat star‐shaped structure transforms into a 3D dome. Printed flower blooms into a blossom shape upon heating.
Source: Ding et al. [153]/with permission of American Association for the Advancement of Science – AAAS.
(c) FFF printing Thermorph material causes bending using an active PLA layer and passive TPU layer. A printed flat sheet self‐folded into a 3D rose.
Source: An et al. [154]/with permission of ACM SIGCHI.
(d) FFF‐printed PLA filaments with different orientations in layers can simultaneously shrink in length and thickness upon heating to a temperature above Tg. The two‐step folding of the initially flat petals creates a tulip.
Source: van Manen et al. [35]/from Royal Society of Chemistry/CC BY 3.0.
Heat shrinkage of SMPs has also been utilized for direct 4D printing of bilayer composites without shape programming. The SMP chains (such as PLA) can be stretched and aligned along the direction of extrusion during the FFF printing process, storing internal residual stress in the polymer. Upon heating to a temperature above its Tg, the printed parts can show macroscopic contraction along the chain alignment direction due to residual stress release. For example, An et al. [154] reported the concept of Thermorph by FFF printing of bilayers consisting of an active PLA layer and a passive thermoplastic polyurethane (TPU) layer to form an actuator (Figure 1.9c). The printed 2D bilayer composites could self‐fold into 3D configurations upon heating. With this Thermorph approach, complex geometries, including 3D Stanford Bunny and 3D rose, were designed, printed, and self‐folded from 2D flat sheets. Zhang et al. [36] reported heat‐triggered shape transformation of printed 2D lattice patterns. When the paper was used as the passive material, it could be removed after shape‐shifting, yielding complex lightweight structures [157]. Besides, the heat‐shrinkage property of printed SMPs can combine with geometry control for anisotropic deformation and more complex shape‐shifting. Van Manen et al. [35]
