This paper reviews damage tolerance in 4D-printed mechanical structures, focusing on how material selection, design strategies, and the 4D printing process influence resilience under stress. It highlights the role of smart materials, metamaterials and adaptive behaviors—such as self-sensing and shape change—in detecting and mitigating damage.
This review adopts a systematic approach to analyze recent advancements in damage tolerance within 4D-printed structures. It examines peer-reviewed literature across materials science, mechanical engineering and additive manufacturing, with a focus on self-sensing, adaptive mechanisms and fatigue behavior. The methodology includes comparative analysis of material systems, printing strategies and structural designs that enhance durability under cyclic loading. Special emphasis is placed on metamaterials and time-dependent functionalities enabled by 4D printing. By evaluating experimental and computational studies, the review identifies key design principles and fabrication methods that contribute to improved damage mitigation and long-term structural performance.
The review shows that 4D-printed structures can better handle damage when smart materials, especially metamaterials, and designs that change over time are used, allowing them to adapt to mechanical stress. Key findings highlight the effectiveness of self-sensing and shape-morphing capabilities in detecting and mitigating damage, particularly under cyclic loading and fatigue conditions. Layer-by-layer control and stimulus-responsive behaviors contribute to improved crack deflection, energy dissipation and structural recovery.
This review offers a unique synthesis of current research on damage-tolerant design in 4D-printed structures, bridging insights from materials science, additive manufacturing and structural mechanics. Its originality lies in framing damage tolerance as a multi-functional outcome enabled by 4D printing’s intrinsic capabilities—such as self-adaptivity, shape transformation and time-dependent material behavior.
1. Introduction
Since its introduction in 2013, four-dimensional (4D) printing has attracted significant interest. This advancement was driven by interdisciplinary research and the swift development of smart materials, 3D printing technologies and innovative design approaches (Joharji et al., 2022). 4D printing represents a transformative advancement in additive manufacturing by integrating smart materials that can change shape, properties, or function over time in response to external stimuli such as temperature, light, or moisture. Table 1 presents a comparative overview of the growth and competition between 3D and 4D printing technologies. In this table, the two technologies are hierarchically compared based on printing method, printer type, materials, design concept, related equipment, product flexibility, product state, equipment cost, market status and applications.
Comparative analysis between 3D and 4D printing technology (Quanjin et al., 2020)
| Category | 3D printing technology | 4D printing technology |
|---|---|---|
| Printing method | Printing repeats a 2D structure lay by lay from bottom to top | Printing is the extension of 3D printing |
| Printer type | 3D printer | Smart/multi-material 4D printer |
| Materials | Thermoplastics, ceramics, metals, paper, food, polymers, nanomaterial and biomaterials | Smart material, multi-material, self-assembled, self-actuating and self-sensing materials, shape memory polymers magnetostrictive and advanced material |
| Design concept | The 3D digital object (drawing or scanning) | 3D digital object with deformation feature |
| Related equipment | Apparatus, material extrusion, and selective laser sintering | Modified nozzle, binder and selective laser |
| Product flexibility | No | Yes, after printing in shape, color, various functions and other conditions |
| Product state | Static structure | Smart, dynamic structure |
| Equipment cost | Low | High |
| Market outlook | Medium | Medium-High |
| Applications | Engineering and design, consumer products, education, aerospace, medical, robotics, military and defense, industrial goods, fashion, and others | Construction, medical, furniture, transportation, aviation, aerospace, biomedical devices, soft robotics and others |
One critical aspect of ensuring the reliability of these structures in real-world environments is damage tolerance, which is the ability of a material or structure to resist and manage the progression of damage under various loading conditions. In 4D-printed processes, this property is influenced not only by the base materials used (e.g. shape memory polymers or composites) but also by design strategies such as metamaterial architectures and self-sensing features that allow real-time damage detection and adaptive response. Recent studies have begun to explore this complex relationship. For example, Momeni et al. (2017) provided a comprehensive overview of 4D printing technologies and discussed how material design and stimuli-responsive behavior could be engineered for better mechanical performance. The limited research conducted in this field highlights the need for a deeper understanding of damage mechanisms in 4D-printed materials, especially under cyclic or unpredictable loading scenarios, where conventional damage models may fall short.
2. Enhancing damage-tolerance via 4D printing
Various studies have explored 4D printing concepts that aid in damage tolerance or fault tolerance. Given the nature of the topic and the growing importance of designing and manufacturing 4D-printed structures with high mechanical strength, energy absorption capabilities and the ability to trap or halt crack propagation, the most significant of these concepts are outlined, including self-healing, self-adaptability, self-sensing, etc. In the study by Joharji et al. (2022), the ability of certain 4D-printed materials to self-heal after mechanical damage is highlighted. For instance, intelligent materials like self-healing polymers can repair cracks or breaks by re-establishing molecular bonds when exposed to specific stimuli like heat or light. This is particularly useful in applications where the material is subjected to repeated stress or strain. To gain a clearer understanding of the function of self-healing and its capability of repairing damage autonomously, refer to Figure 1, adapted from Kuang et al. (2018), Ma et al. (2023). Kuang et al. (2018) formulated an ink blending a photocurable resin with a semicrystalline thermoplastic polymer for direct ink writing (DIW). After printing, the structures were UV-cured to produce semi-interpenetrating polymer network (semi-IPN) elastomer composites. The self-healing capability of the fabricated samples was assessed by inducing microcracks. Upon heating, the cracks closed seamlessly without leaving visible marks, indicating successful healing performance (Figure 1a). One of the most notable characteristics of the material developed in Ma et al. (2023) is its responsiveness to various environmental stimuli, including temperature and magnetic fields. It also demonstrated impressive self-healing efficiency, recorded at 91.2% under room temperature conditions (Figure 1b). The self-healing effect is also studied in Hager et al. research (Hager et al., 2010) through the biological processes in natural organisms, which could be beneficial in preventing crack growth. Moreover, shape memory polymers (SMPs) can recover their original shape after deformation. The shape memory effect can indeed contribute to damage tolerance, as the material can return to its original form even after being deformed or damaged. Invernizzi et al. (2018) showcased the potential of a newly developed material based on polycaprolactone (PCL) and ureido-pyrimidinone (UPy) units, highlighting their mechanical, self-healing and shape memory properties. A deep scratch on the surface of the samples was completely repaired after a thermal treatment of 1 h at 80 °C. Also, the healing efficiency was measured at 53.6 ± 6.4% at 3 mm/min and 51.7 ± 11.7% at 30 mm/min, indicating the high healing efficiency of the printed samples. Self-adaptability is another feature of 4D printing and is the ability to vary the geometry and stiffness while maintaining the mass and chemical state the same (Joharji et al., 2022). This adaptability can help the structure withstand mechanical stress by redistributing forces or changing its shape to absorb impact. The variability in composition of smart materials can lead to different strains and driving forces, allowing for better control over the material’s response to stress and damage.
The image is a composite figure consisting of two main labeled sections, (a) and (b), that together demonstrate the self-healing properties of a material using various visual, microscopic, and mechanical tests. In section (a), the focus is on visual and optical microscope evidence of the material healing itself after being cut. On the left side of (a), two curled ribbon-like strips of material are shown. The left strip is labeled “Virgin” and represents the original, undamaged state. It appears smooth and coiled, with a magnified inset at the top-right showing fine surface texture, comprised of parallel lines. The right strip, labeled “Healed,” shows the same ribbon after it was cut and rejoined. This healed version appears visually continuous and also includes a similar magnified inset. Below these images, a third horizontal image shows the same strip in a cut state, with a visible separation in the center, highlighting the initial damage before healing. Blue and green curved arrows point from the cut strip to the healed and virgin states above, symbolizing the healing process. The scale bar below the images is marked by a horizontal bar with the label 1 centimeter. To the right in section (a), there is a three-column grid displaying microscope images from three successive healing cycles, labeled “1st healing,” “2nd healing,” and “3rd healing.” Each column has two vertically stacked microscope images. The top row shows the material in a “Cut” condition with a clearly visible dark fracture or gash against a yellow-green background. The bottom row shows the same region after healing, where the crack appears significantly less visible or even fully closed, indicating successful healing. Red arrows between each “cut” and “healed” pair visually link the process stages. A white scale bar labeled “1 millimeter” in the lower-right corner provides a reference for the magnification level. In section (b), two mechanical experiments are presented to test and confirm the material’s self-healing ability under load-bearing and physical linking conditions. On the left side, a sequence of photos shows a cylindrical black sample being manually fractured and repaired. The top image shows blue-gloved hands using scissors or a blade to create a vertical fracture in the sample, labeled “fracture.” The middle image shows the two halves of the fractured sample being aligned again for healing, labeled “repair.” In the bottom image, the gloved hands stretch the healed sample, showing it can be physically manipulated. Adjacent to this sequence is a vertical setup where the healed sample is shown suspending a chain of weights totaling 280 grams (100 grams, 50 grams, 50 grams, 20 grams, and 60 grams), demonstrating recovery of mechanical strength. On the right side of (b), a rectangular sample is shown in a mechanical linkage setup before and after being broken and healed. The top row shows the sample in its original and healed (post-fracture repair) states, with both ends fixed into a green clamping apparatus with red and black adjustment knobs. The bottom row shows the sample in the “fracture” state with a visible gap, followed by a “fracture-linked” image where the sample appears continuous again after healing. All mechanical stages are connected by downward or upward arrows to indicate progression from fracture to repair.(a) Illustration of the shape memory-assisted self-healing process in a 3D-printed Archimedean spiral structure, the printed strip is cut and subsequently healed across three successive healing cycles (Kuang et al., 2018), figure courtesy of Kuang et al. (2018), ACS Applied Materials and Interfaces, 2018, ACS. (b) Self-healing performance of multi-functional smart material processed through 4D printing, representation of weight diagram after fracture self-healing and the demonstration of self-healing behavior through LED light exposure (Ma et al., 2023), figure courtesy of Ma et al. (2023), Chemical Engineering Journal, 2023, Elsevier
The image is a composite figure consisting of two main labeled sections, (a) and (b), that together demonstrate the self-healing properties of a material using various visual, microscopic, and mechanical tests. In section (a), the focus is on visual and optical microscope evidence of the material healing itself after being cut. On the left side of (a), two curled ribbon-like strips of material are shown. The left strip is labeled “Virgin” and represents the original, undamaged state. It appears smooth and coiled, with a magnified inset at the top-right showing fine surface texture, comprised of parallel lines. The right strip, labeled “Healed,” shows the same ribbon after it was cut and rejoined. This healed version appears visually continuous and also includes a similar magnified inset. Below these images, a third horizontal image shows the same strip in a cut state, with a visible separation in the center, highlighting the initial damage before healing. Blue and green curved arrows point from the cut strip to the healed and virgin states above, symbolizing the healing process. The scale bar below the images is marked by a horizontal bar with the label 1 centimeter. To the right in section (a), there is a three-column grid displaying microscope images from three successive healing cycles, labeled “1st healing,” “2nd healing,” and “3rd healing.” Each column has two vertically stacked microscope images. The top row shows the material in a “Cut” condition with a clearly visible dark fracture or gash against a yellow-green background. The bottom row shows the same region after healing, where the crack appears significantly less visible or even fully closed, indicating successful healing. Red arrows between each “cut” and “healed” pair visually link the process stages. A white scale bar labeled “1 millimeter” in the lower-right corner provides a reference for the magnification level. In section (b), two mechanical experiments are presented to test and confirm the material’s self-healing ability under load-bearing and physical linking conditions. On the left side, a sequence of photos shows a cylindrical black sample being manually fractured and repaired. The top image shows blue-gloved hands using scissors or a blade to create a vertical fracture in the sample, labeled “fracture.” The middle image shows the two halves of the fractured sample being aligned again for healing, labeled “repair.” In the bottom image, the gloved hands stretch the healed sample, showing it can be physically manipulated. Adjacent to this sequence is a vertical setup where the healed sample is shown suspending a chain of weights totaling 280 grams (100 grams, 50 grams, 50 grams, 20 grams, and 60 grams), demonstrating recovery of mechanical strength. On the right side of (b), a rectangular sample is shown in a mechanical linkage setup before and after being broken and healed. The top row shows the sample in its original and healed (post-fracture repair) states, with both ends fixed into a green clamping apparatus with red and black adjustment knobs. The bottom row shows the sample in the “fracture” state with a visible gap, followed by a “fracture-linked” image where the sample appears continuous again after healing. All mechanical stages are connected by downward or upward arrows to indicate progression from fracture to repair.(a) Illustration of the shape memory-assisted self-healing process in a 3D-printed Archimedean spiral structure, the printed strip is cut and subsequently healed across three successive healing cycles (Kuang et al., 2018), figure courtesy of Kuang et al. (2018), ACS Applied Materials and Interfaces, 2018, ACS. (b) Self-healing performance of multi-functional smart material processed through 4D printing, representation of weight diagram after fracture self-healing and the demonstration of self-healing behavior through LED light exposure (Ma et al., 2023), figure courtesy of Ma et al. (2023), Chemical Engineering Journal, 2023, Elsevier
The 3D printing of vascular grafts using UV-curable composite ink, including crystalline linear chains and cross-linked networks, showed structural changes during the process (Kabirian et al., 2022). Photos and microscopic images revealed different inner and outer diameters for grafts of equal length of 10 mm. Through thermal stimulation at 70°C, the vascular pathways were temporarily stretched and compressed to half of their original diameter, with the original shape being restored upon cooling. Three recovery cycles of the printed structures were tested using air cooling after heating at 80 °C for 20 min, with SEM images showing scratched and repaired areas. The 4D-printed blood vessel, once cut and implanted into a fracture site, regains its shape through heat and connects to existing vessels, restoring blood flow. The use of epoxidized acrylate (SOEA) in photolithography-printed films confirms self-folding behavior due to a cross-linking density gradient, which enables differential swelling and crack trapping. Another utilization of 4D-printed shape memory effect in biomaterial fields has been showcased in a study conducted by Jacobson and Iroh (2021), in which poxidized acrylate (SOEA) is being used in cardiac tissue engineering to create shape memory films that enhance stem cell differentiation and integrate within damaged heart tissue. These films minimize invasiveness and trauma, improving patient comfort. Damage tolerance here is crucial, as the films can respond to physiological conditions by bending or rolling when warmed to body temperature. 4D-printed vascular grafts, reinforced with nanoparticles, also demonstrate self-healing properties, particularly in healing micro cracks. These grafts are crucial for preventing constant bleeding and reducing surgical risks, enhancing their reliability and longevity.
The self-sensing property of materials allows them to detect damage and potentially initiate healing processes. This capability can be vital in identifying cracks early and initiating the healing process and can be integrated into various materials, including concrete and plastics, to monitor their health and respond to damage, which is essential for maintaining structural integrity and preventing crack propagation (Li et al., 2017).
3. 4D printing with metamaterial characteristics
Metamaterials, due to their unique properties, have applications in various fields such as aerospace, automotive and medical industries. However, one of the main challenges in using these materials is their sensitivity to damage and failure. Zhang et al. (2020) introduced and analyzed a new type of microlattice metamaterial composed of a liquid metal-filled polymer microlattice metamaterial using micro-stereolithography (PμSL) 3D printing. The most important features of these octet metamaterials include high fracture strength, corrosion resistance and damage recovery capability. The recoverability of these metamaterials allows them to be considered as part of 4D printing structures. They filled their structure with gallium (Ga) to achieve a shape memory effect at relatively low temperatures, enabling it to recover its original shape after damage. Zhang et al.’s (2020) research on mechanical metamaterials shows that the incorporation of liquid metal improves damage recovery and fracture resistance (Figure 2a), while polymers enhance strength and flexibility. Figure 2a visually explains how the octet microlattice undergoes shape memory and recovery. It shows the material’s state before compression, after compression (deformed state) and then after recovery, indicating its ability to return to its original configuration. Figures 2b and 2c demonstrate the mechanical reusability and repetitive compression stress–strain curves after recovery, indicating the material’s ability to maintain its strength and structural integrity over multiple cycles and after significant deformation (up to 35% strain). According to these figures, these metamaterials can withstand high stresses and recover after damage, providing new insights for soft robotics, flexible electronics and biomedical applications.
The composite image consists of five labeled panels (a) through (e), visually and analytically illustrating the behavior, damage resistance, and self-healing capability of architected materials, particularly lattice structures. Panel (a), located at the top left, demonstrates the healing mechanism through a sequence of physical images. It shows three rectangular samples of a patterned lattice material across three stages, with the process labeled as compression, fusion, recovery, and solidification. The image (i) on the left shows a lattice structure before compression, where the yellow patterned geometry is clearly visible with distinct triangular and diamond-like cells. Image (ii) in the center shows the same material after compression, appearing partially deformed, alongside another solid orange sample. Image (iii) on the right shows fusion and recovery of the lattice after solidification, with the lattice structure reappearing alongside the same orange control piece. From the third image, the process loops back to the first image after solidification. A scale bar of 2 millimeters is placed in the bottom right corner, giving a size reference for the samples. Panel (b), directly below, consists of two adjacent line graphs. The graph on the left plots “Stress in megapascals” on the vertical axis with values ranging from 0 to 5 with an interval of 1. The horizontal axis is labeled “Strain in percentage,” ranging from 0 to 50 with an interval of 10. Red data points with red vertical error bars are plotted along a curve that starts from the origin and increases towards the right in a concave downward trend and peaks just above the stress of 3 megapascals at a strain of around 25 percent. After that, the curve decreases in a concave-up trend and increases after attaining a trough near the strain of 40 percent with a stress of 2.5 megapascal and ends before 50 percent strain, nearly at 3.5 megapascal of stress. The graph background is divided into two colored vertical bands: the region from 0 to 26 percent strain is shaded in blue and labeled “Fully recovered area,” while the region from 26 to 50 percent strain is shaded peach and labeled “Damaged area.” The right graph also plots “Stress in megapascals” on the vertical axis with values ranging from 0 to 5 with an interval of 1. The horizontal axis is labeled “Strain in percentage,” ranging from 0 to 20 with an interval of 10. It shows three nearly overlapping curves corresponding to mechanical tests labeled “1st,” “2nd,” and “3rd,” drawn in blue, black, and red lines, respectively. All three curves rise steeply from the origin and gradually taper, indicating that the material maintains a consistent stress response that ends before the strain of 20 percent and above the stress of 3 megapascals. Panel (c), labeled “Cycle 1” at the top, shows the hexagonal mesh is fully intact. The beam connections between hexagonal cells are clean, unbroken, and continuous throughout the frame, showing no visible defects. In the middle image, labeled “Cycle 2,” a red “X” marks near the bottom left corner and is labeled “complete fracture,” where one beam is fully severed. Further right in the same image, a small yellow cross points to a smaller defect labeled “minor crack” and positioned along the diagonal from the bottom left to the top right. In the bottom image, labeled “Cycle 6,” multiple red “X” marks appear across the structure near the bottom left corner. Several orange arrows labeled “major crack” point to partially broken or misaligned struts, especially along the diagonal from the bottom left to top right. Panel (d), positioned to the right of panel “(c)”, contains three close-up grayscale microscope images, vertically stacked. Each image provides a magnified view of damaged regions from panel (c), focusing on beam-level crack propagation within the hexagonal structure. The top image shows two adjacent hexagonal cells with distorted or split beams along the center, closely matching the region observed in “Cycle 1.” The middle image corresponds to the area seen in “Cycle 2” and is framed in a thin red border; it shows a localized beam deformation and crack. The bottom image, framed in a purple border, provides a close-up of one of the worst-damaged areas from “Cycle 6,” where several beams appear cracked or misaligned, and an orange arrow again points to a visible fracture line. Panel (e) at the bottom presents finite element simulation results in a colorful stress distribution map for different beam states. There are three rows, each showing left and right symmetrical beam segments. Each image shows a rectangular beam featuring a regular pattern of circular holes distributed throughout its body. These structures are color-mapped using a spectrum ranging from blue (minimal deformation) to red (maximum deformation), with a vertical color bar scale positioned to the far right of the figure, labeled from 0.5 at the bottom to 2 times 10 to the 6 power. In the top row, the simulation result is labeled “Max deformations of intact beams: 0.18 millimeters (left) and 0.17 millimeters (right).” The left and right beams are symmetric and undamaged. Both show a curved profile under load, with mild red zones centered near the top and bottom mid-span, indicating localized deformation. Most of the beam body remains in blue or green, suggesting minimal strain. In the middle row, the label reads “Max deformations of periodically damaged beams: 0.25 millimeters (left) and 0.18 millimeters (right).” Here, both beams exhibit more noticeable deformation than the intact ones. The left beam shows red regions spanning more broadly along the upper center, implying higher deformation likely due to introduced periodic flaws. The right beam still shows moderate red zones but is less strained than the left. In the bottom row, the label states, “Max deformations of randomly damaged beams: 0.27 millimeters (left) and 0.19 millimeters (right).” The color maps here are more irregular compared to the previous rows, with the left beam showing intense red and orange patches randomly distributed along the central horizontal axis, consistent with randomly applied damage. The right beam also shows deformation, though it is less severe and slightly more uniform. Note: All numerical data values are approximated.(a) Shape memory effect and recovery capability, (b) Stress-strain diagram under compressive loading and damage recovery, (c) Repeated compressive stress-strain curves after recovery (Zhang et al., 2020), figure courtesy of Zhang et al. (2020), Small, 2020, Wiley. (d) Crack initiation and propagation in hexagonal honeycomb PLA and PETG metamaterials across different cycles after unloading (Zhang et al., 2024), figure courtesy of Zhang et al. (2024), International Journal of Mechanical Sciences, 2024, Elsevier. (e) Comparison of the performance of reference beam structures and damage-tolerant structures (Zheng et al., 2025), figure courtesy of Zheng et al. (2025), Materials and Design, 2025, Elsevier
The composite image consists of five labeled panels (a) through (e), visually and analytically illustrating the behavior, damage resistance, and self-healing capability of architected materials, particularly lattice structures. Panel (a), located at the top left, demonstrates the healing mechanism through a sequence of physical images. It shows three rectangular samples of a patterned lattice material across three stages, with the process labeled as compression, fusion, recovery, and solidification. The image (i) on the left shows a lattice structure before compression, where the yellow patterned geometry is clearly visible with distinct triangular and diamond-like cells. Image (ii) in the center shows the same material after compression, appearing partially deformed, alongside another solid orange sample. Image (iii) on the right shows fusion and recovery of the lattice after solidification, with the lattice structure reappearing alongside the same orange control piece. From the third image, the process loops back to the first image after solidification. A scale bar of 2 millimeters is placed in the bottom right corner, giving a size reference for the samples. Panel (b), directly below, consists of two adjacent line graphs. The graph on the left plots “Stress in megapascals” on the vertical axis with values ranging from 0 to 5 with an interval of 1. The horizontal axis is labeled “Strain in percentage,” ranging from 0 to 50 with an interval of 10. Red data points with red vertical error bars are plotted along a curve that starts from the origin and increases towards the right in a concave downward trend and peaks just above the stress of 3 megapascals at a strain of around 25 percent. After that, the curve decreases in a concave-up trend and increases after attaining a trough near the strain of 40 percent with a stress of 2.5 megapascal and ends before 50 percent strain, nearly at 3.5 megapascal of stress. The graph background is divided into two colored vertical bands: the region from 0 to 26 percent strain is shaded in blue and labeled “Fully recovered area,” while the region from 26 to 50 percent strain is shaded peach and labeled “Damaged area.” The right graph also plots “Stress in megapascals” on the vertical axis with values ranging from 0 to 5 with an interval of 1. The horizontal axis is labeled “Strain in percentage,” ranging from 0 to 20 with an interval of 10. It shows three nearly overlapping curves corresponding to mechanical tests labeled “1st,” “2nd,” and “3rd,” drawn in blue, black, and red lines, respectively. All three curves rise steeply from the origin and gradually taper, indicating that the material maintains a consistent stress response that ends before the strain of 20 percent and above the stress of 3 megapascals. Panel (c), labeled “Cycle 1” at the top, shows the hexagonal mesh is fully intact. The beam connections between hexagonal cells are clean, unbroken, and continuous throughout the frame, showing no visible defects. In the middle image, labeled “Cycle 2,” a red “X” marks near the bottom left corner and is labeled “complete fracture,” where one beam is fully severed. Further right in the same image, a small yellow cross points to a smaller defect labeled “minor crack” and positioned along the diagonal from the bottom left to the top right. In the bottom image, labeled “Cycle 6,” multiple red “X” marks appear across the structure near the bottom left corner. Several orange arrows labeled “major crack” point to partially broken or misaligned struts, especially along the diagonal from the bottom left to top right. Panel (d), positioned to the right of panel “(c)”, contains three close-up grayscale microscope images, vertically stacked. Each image provides a magnified view of damaged regions from panel (c), focusing on beam-level crack propagation within the hexagonal structure. The top image shows two adjacent hexagonal cells with distorted or split beams along the center, closely matching the region observed in “Cycle 1.” The middle image corresponds to the area seen in “Cycle 2” and is framed in a thin red border; it shows a localized beam deformation and crack. The bottom image, framed in a purple border, provides a close-up of one of the worst-damaged areas from “Cycle 6,” where several beams appear cracked or misaligned, and an orange arrow again points to a visible fracture line. Panel (e) at the bottom presents finite element simulation results in a colorful stress distribution map for different beam states. There are three rows, each showing left and right symmetrical beam segments. Each image shows a rectangular beam featuring a regular pattern of circular holes distributed throughout its body. These structures are color-mapped using a spectrum ranging from blue (minimal deformation) to red (maximum deformation), with a vertical color bar scale positioned to the far right of the figure, labeled from 0.5 at the bottom to 2 times 10 to the 6 power. In the top row, the simulation result is labeled “Max deformations of intact beams: 0.18 millimeters (left) and 0.17 millimeters (right).” The left and right beams are symmetric and undamaged. Both show a curved profile under load, with mild red zones centered near the top and bottom mid-span, indicating localized deformation. Most of the beam body remains in blue or green, suggesting minimal strain. In the middle row, the label reads “Max deformations of periodically damaged beams: 0.25 millimeters (left) and 0.18 millimeters (right).” Here, both beams exhibit more noticeable deformation than the intact ones. The left beam shows red regions spanning more broadly along the upper center, implying higher deformation likely due to introduced periodic flaws. The right beam still shows moderate red zones but is less strained than the left. In the bottom row, the label states, “Max deformations of randomly damaged beams: 0.27 millimeters (left) and 0.19 millimeters (right).” The color maps here are more irregular compared to the previous rows, with the left beam showing intense red and orange patches randomly distributed along the central horizontal axis, consistent with randomly applied damage. The right beam also shows deformation, though it is less severe and slightly more uniform. Note: All numerical data values are approximated.(a) Shape memory effect and recovery capability, (b) Stress-strain diagram under compressive loading and damage recovery, (c) Repeated compressive stress-strain curves after recovery (Zhang et al., 2020), figure courtesy of Zhang et al. (2020), Small, 2020, Wiley. (d) Crack initiation and propagation in hexagonal honeycomb PLA and PETG metamaterials across different cycles after unloading (Zhang et al., 2024), figure courtesy of Zhang et al. (2024), International Journal of Mechanical Sciences, 2024, Elsevier. (e) Comparison of the performance of reference beam structures and damage-tolerant structures (Zheng et al., 2025), figure courtesy of Zheng et al. (2025), Materials and Design, 2025, Elsevier
Zhang et al. (2024) developed a reusable SMP metamaterial using 3D/4D printing, utilizing fused deposition modeling (FDM) to create structures that effectively absorb energy and return to their original shape after deformation. The metamaterial shape memory properties enable its versatile applications. Zhang et al.’s (2024) study on the reusability of SMP metamaterials under cyclic mechanical degradation found that hexagonal honeycomb polylactic acid (PLA) dissipates 22% more energy compared to its polyethylene terephthalate glycol (PETG) counterpart due to its higher elastic modulus. Additionally, the re-entrant PETG honeycomb dissipated 25% more energy than its hexagonal counterpart due to its negative Poisson’s ratio and uniform overall deformation pattern. Furthermore, as shown in Figure 2d, cracks appeared on the tested samples after two complete cycles, which grew with an increasing number of cycles. However, crack initiation and propagation were contained within samples due to the shape memory effect in 4D printing.
Zheng et al. (2025) developed damage-tolerant mechanical metamaterials using a fail-safe topology optimization approach. They considered various failure scenarios and used finite element analysis (FEA) to evaluate the performance of the 4D-printed metamaterials under different damage conditions. The structures, designed with symmetry, uniform stress distribution and redundancy, maintain functionality even when partially damaged, demonstrating high mechanical performance and resistance to minor damages. Figure 2e shows a significant improvement in structural load-bearing performance of damage-tolerant materials under three-point bending in FE simulations, while stress field patterns in locally damaged structures remain unaffected, preserving high load-bearing capacity.
Gao et al. (2024) studied designing metamaterials with damage-programmable capabilities, inspired by natural crack-resisting mechanisms. Their goal was to create materials intelligently and controllably resisting damage and preventing crack propagation, similar to mechanisms seen in natural structures such as bones, seashells, or the shells of living organisms. These mechanisms include energy distribution, reduction of crack growth and crack trapping. They used numerical simulation and topology optimization to design microscopic metamaterials mimicking natural mechanisms, which were then fabricated using 4D printing and tested under various mechanical conditions. The simulation results showed that the metamaterials distribute stress evenly, reducing crack growth and improving damage tolerance. As a result, they have a longer lifespan and lower maintenance costs. In the studies reviewed in Wallbanks et al. (2021), it has been shown that auxetic composite metamaterial panels can significantly increase energy dissipation and reduce displacement under blast loading. For instance, an auxetic core absorbed 19.1% more energy than a conventional core in drop weight impact tests. The article discusses the potential for recoverable auxetic structures, especially when incorporating shape memory effects. Dual-material sandwich structures, with alternating hard and soft layers, can provide non-linear stiffness and energy dissipation, with softer layers offering elastic absorption for low-energy impacts and load spreading for high-energy impacts. These structures can also demonstrate shape recovery through thermal means.
In addition to smart materials and metamaterials which have been fabricated in a smart way to achieve the goals of 4D printing, there are other materials such as PLA and PA12 that show smart behavior via a simple heating-cooling process. Molina et al. (2023), in their research, investigated the behavior of thermally responsive smart materials based on PLA/PCL blends in terms of shape memory properties as well as resistance to damage. The main objective of their study was the development of multiphase materials that, in addition to being capable of shape change under thermal stimulation, exhibit high resistance to fracture in the presence of initial cracks, which is a crucial characteristic for structural applications in 4D printing. Specimens were prepared in different weight ratios (70/30, 50/50 and 30/70 w/w%), and mechanical, thermal and shape memory tests were conducted on them. Results from DSC and DMA tests indicated that PCL, with its low melting point (∼60 °C), effectively acts as the activating phase for shape memory behavior. Moreover, the 70/30 PLA/PCL sample demonstrated the highest shape recovery ratio during thermal activation cycles. Alongside the shape memory properties, mechanical tests confirmed a significant improvement in impact resistance and stress distribution in the presence of PCL, such that the 70/30 w/w% sample showed clearer signs of high energy absorption and prevention of crack propagation compared to other ratios. This behavior indicates enhanced damage tolerance in these blended systems, as the presence of the elastic PCL phase prevents sudden and complete failure even in the presence of minor cracks. Therefore, Molina et al. (2023) showed that PLA/PCL blends, particularly those with a 70/30 ratio, are suitable candidates for applications where simultaneous requirements of thermally induced shape adaptability and high mechanical damage resistance are needed. In another study, Hamzehei et al. (2023) investigated the design of smart metamaterials inspired by the structure of a parrot’s beak to achieve maximum energy absorption and dissipation. In this research, by combining frictional and interlocking mechanisms at micro and macro scales, 3D/4D-printed metamaterials were developed that exhibited very high damage tolerance. Results from mechanical tests showed that these structures are capable of absorbing significant amounts of energy and dissipating them effectively even after the formation of initial cracks, without experiencing complete collapse. This property is achieved thanks to the complex interactions between the constituent elements of the metamaterial, including frictional contacts and nonlinear deformations. Additionally, by utilizing 4D printing technology, the possibility of automatic structural adaptation to environmental loads was enabled, which further improved resistance to progressive failure and increased structural lifespan. Therefore, the investigation in Hamzehei et al. (2023) introduced important innovations in the field of designing structural materials with high damage tolerance, offering applications in areas such as impact protection, aerospace structures and intelligent robotics.
4. Fatigue behavior in 4D-printed materials
Investigating damage tolerance in 4D-printed materials that display fatigue stress behavior is essential for understanding their durability and reliability under repeated stress or changing environmental conditions. Nevertheless, this phenomenon has received relatively little attention in research so far. This section aims to provide a foundational literature review that supports advancements in material science and manufacturing research, which can enhance the understanding of damage tolerance in 4D-printed materials exposed to fatigue stress. Zhang et al. (2021) investigated a 4D-printable SMP using a 3D printing technique based on digital light processing (DLP). This study aims to enhance the mechanical durability, flexibility and fatigue resistance of a newly developed tert-Butyl Acrylate (tBA) aliphatic urethane diacrylate (AUD) SMP tailored for 4D printing applications. Mechanical tensile tests were conducted to assess the material’s strength and elasticity, while fatigue testing evaluates its shape-memory properties and durability over thousands of loading cycles. Unlike previously reported UV-curable SMPs, the tBA–AUD SMP demonstrated outstanding fatigue resistance, enduring over 10,000 loading cycles without sustaining any damage.
Chapuis and Shea (2023) discuss using polylactic acid (PLA) in direct 4D printing to create bilayer actuators, utilizing fused filament fabrication (FFF) to induce bending or twisting. The springs demonstrated exceptional fatigue resistance during extensive testing, showing minimal damage even after enduring 10,000 cycles. Upon closer examination, initial fracture nucleation was detected, indicating the onset of fatigue damage. However, cracks and fatigue striations were observed after the deployments. This observation emphasizes the considerable impact of thermal stresses on the material’s durability during the redeployment process. Unlike traditional printed parts, the failure of these 4D-printed springs was not due to layering, showing that this printing method can enhance the lifespan of components under repeated stress. Figure 3 shows analysis of fatigue behavior and redeployment performance in 4D-printed PLA wave springs in Chapuis and Shea (2023). Van Hoa (2019) employed a 4D-printing technique that embeds long fibers in polymeric resins to create rigid, fatigue-resistant and robust composites. Specifically, this approach utilizes carbon/epoxy materials, automated fiber placement and a curing temperature of 177 °C to showcase how the anisotropic characteristics of layered materials can be leveraged for the efficient fabrication of intricate composite structures through 4D printing. In this study, a 24-inch composite specimen subjected to 175,000 cycles of three-point deformation and recorded maximum and minimum displacements of 2.4 mm and 0.24 mm, respectively. The results demonstrated that the material maintained its integrity despite extensive cyclic loading. This suggests a robust damage tolerance, as the material was able to endure significant stress without catastrophic failure, which is essential for applications requiring durability and reliability. Yousuf et al. (2020) emphasizes that the mechanical properties of 4D- printed materials, such as thermoplastic SMPs, are affected by repeated programming and cyclic loading. The accumulation of residual strain during these cycles can lead to mechanical property deterioration, which is a critical factor in assessing damage tolerance. The findings indicate that the frequency of cycles and the intensity of programming significantly influence the material’s ability to tolerate damage over time.
The figure presents six microscope images labeled “(a)” through “(f),” arranged in two rows of three columns each. These images document the progressive fatigue and cracking behavior in a blue 3D-printed polymer hinge structure over different numbers of mechanical cycles and deployments. All images show close-up side views of the same hinge surface, with emphasis on the curved inner layer. The top row corresponds to increasing mechanical exposure from left to right: “No cycles per 1 deployment,” “10 to the 4 power cycles per 1 deployment,” and “10 to the 4 power cycles per 10 deployments.” In the top-left image, labeled “(a),” the hinge is in pristine condition with “No cycles per 1 deployment.” The surface appears clean and smooth, with a slightly textured finish and no visible defects. The curvature of the blue structure is intact, and a scale bar marked “5 millimeters” is shown at the bottom right. In the middle image of the top row, labeled “(b),” representing “10 to the 4 power cycles per 1 deployment,” the surface texture appears slightly roughened, but there are still no major visible cracks. Microtexture is more pronounced, indicating minor surface wear, and the same 5-millimeter scale bar is present. The top-right image, labeled “(c),” corresponds to “10 to the 4 power cycles per 10 deployments” and shows clear damage. A large diagonal crack is visible on the tension side of the curved surface, disrupting the continuity of the layer. A white rectangular label at the bottom right reads “crack on tension side,” identifying the fracture location. The second row shows three additional angled views of similar samples. Image “(d)” on the bottom-left is another view under “No cycles per 1 deployment,” showing a clean, undamaged inner surface with gentle curvature and fine striations from manufacturing, along with the same 5-millimeter scale bar. Image “(e),” in the center of the bottom row, corresponds to “10 to the 4 power cycles per 1 deployment” and contains a white label reading “crack nucleation” in the bottom right. A zoom-in inset is overlaid in the upper right of the image, marked with a dashed square and an arrow, which highlights a small surface defect at the microscopic level—likely the point of early-stage crack initiation. The final image, labeled “(f),” corresponds to “10 to the 4 power cycles per 10 deployments” and includes a white label in the lower right reading “fatigue striations.” The image shows an elongated view of the curved hinge surface with faint, evenly spaced lines along the tension side.(a) The spring after its initial deployment, displayed in its original state, (b) The tension side of the wave ring after 104 cycles without redeployment, showing no apparent signs of damage, (c) The tension side of the spring after undergoing redeployment tests, showing signs of cracking and failure in the active PLA material, (d) A different section of the wave spring’s tension side shown in its original printed condition, (e) The tension side of the same wave ring after 104 cycles, showing a small crack initiation upon close examination, (f) Fatigue striations observed on the tension side of a spring following redeployment tests, highlighting signs of fatigue damage. Reproduced with permission from the original source (Molina et al., 2023), figure courtesy of Zhang et al. (2021), Advanced Materials, 2021, Wiley
The figure presents six microscope images labeled “(a)” through “(f),” arranged in two rows of three columns each. These images document the progressive fatigue and cracking behavior in a blue 3D-printed polymer hinge structure over different numbers of mechanical cycles and deployments. All images show close-up side views of the same hinge surface, with emphasis on the curved inner layer. The top row corresponds to increasing mechanical exposure from left to right: “No cycles per 1 deployment,” “10 to the 4 power cycles per 1 deployment,” and “10 to the 4 power cycles per 10 deployments.” In the top-left image, labeled “(a),” the hinge is in pristine condition with “No cycles per 1 deployment.” The surface appears clean and smooth, with a slightly textured finish and no visible defects. The curvature of the blue structure is intact, and a scale bar marked “5 millimeters” is shown at the bottom right. In the middle image of the top row, labeled “(b),” representing “10 to the 4 power cycles per 1 deployment,” the surface texture appears slightly roughened, but there are still no major visible cracks. Microtexture is more pronounced, indicating minor surface wear, and the same 5-millimeter scale bar is present. The top-right image, labeled “(c),” corresponds to “10 to the 4 power cycles per 10 deployments” and shows clear damage. A large diagonal crack is visible on the tension side of the curved surface, disrupting the continuity of the layer. A white rectangular label at the bottom right reads “crack on tension side,” identifying the fracture location. The second row shows three additional angled views of similar samples. Image “(d)” on the bottom-left is another view under “No cycles per 1 deployment,” showing a clean, undamaged inner surface with gentle curvature and fine striations from manufacturing, along with the same 5-millimeter scale bar. Image “(e),” in the center of the bottom row, corresponds to “10 to the 4 power cycles per 1 deployment” and contains a white label reading “crack nucleation” in the bottom right. A zoom-in inset is overlaid in the upper right of the image, marked with a dashed square and an arrow, which highlights a small surface defect at the microscopic level—likely the point of early-stage crack initiation. The final image, labeled “(f),” corresponds to “10 to the 4 power cycles per 10 deployments” and includes a white label in the lower right reading “fatigue striations.” The image shows an elongated view of the curved hinge surface with faint, evenly spaced lines along the tension side.(a) The spring after its initial deployment, displayed in its original state, (b) The tension side of the wave ring after 104 cycles without redeployment, showing no apparent signs of damage, (c) The tension side of the spring after undergoing redeployment tests, showing signs of cracking and failure in the active PLA material, (d) A different section of the wave spring’s tension side shown in its original printed condition, (e) The tension side of the same wave ring after 104 cycles, showing a small crack initiation upon close examination, (f) Fatigue striations observed on the tension side of a spring following redeployment tests, highlighting signs of fatigue damage. Reproduced with permission from the original source (Molina et al., 2023), figure courtesy of Zhang et al. (2021), Advanced Materials, 2021, Wiley
A numerical study performed in Simoes et al. (2022) presents a novel phase-field model for predicting fatigue crack growth in shape memory alloys (SMAs). The proposed model allows for a comprehensive simulation of crack growth under cyclic loading, considering the unique properties of SMAs. The study generated virtual Δε-N (strain range vs. number of cycles to failure) curves for three material scenarios (C1: reference material at 320K, C2: modified hysteresis at 320K, C3: reference material at 293K). A strain range of Δε/εc = 0.4 resulted in fatigue lives of 16,100 cycles (C1), 3533 cycles (C2) and 1761 cycles (C3). This demonstrates a significant reduction in fatigue life with a smaller hysteresis loop (C2) and lower temperature (C3), highlighting the influence of material parameters on damage tolerance. The paper aims to provide a generalized framework by incorporating both the AT1 and AT2 phase field models, which are defined by the choice of a geometric crack function, w(). This difference in the geometric crack function leads to a crucial distinction regarding damage initiation. The AT2 model does not have a damage threshold, while the AT1 model exhibits a linear elastic regime prior to the onset of damage, implying a damage threshold. The study simulated crack propagation in a square plate with an initial crack under cyclic loading using both AT1 and AT2 phase-field models (Figure 4a). The results showed that crack initiation occurred earlier for the AT2 model due to the absence of a damage threshold in AT2 compared to AT1. However, the fatigue crack growth rates were higher for the AT2 model in some load ranges, leading to a shorter fatigue life in certain cases. The model also successfully simulated fatigue failure in a complex 3D diamond lattice structure with over 7 million degrees of freedom. The simulation captured the growth and coalescence of multiple defects, leading to crack nucleation and loss of load-carrying capacity. The deformed shape of the lattice undergoing compression is shown in Figure 4b, and Figure 4c shows the initial distribution and evolution of defects in time.
The figure contains three main panels, labeled “(a),” “(b),” and “(c),” arranged in a grid layout with panel (a) occupying the top half and panels (b) and (c) placed below side-by-side. Panel “(a)” consists of two sub-figures illustrating the simulation of fatigue crack growth in a material. On the left, there is a schematic diagram showing a square specimen under uniaxial tensile loading. The square has a centered horizontal crack and is loaded vertically at the top with an array of upward-pointing arrows labeled “delta u superscript infinite.” The bottom of the square is hinged with multiple triangular symbols with hatched boundaries representing full constraint. The horizontal dimensions of the square are marked as “0.5” on both the left and right halves, and the vertical sides also indicate “0.5” on both the top and bottom halves. To the right of the schematic, there is a plot of “Crack extension, delta a (millimeters)” on the vertical axis with the values ranging from 0 to 0.5 with an interval of 0.1. The horizontal axis is labeled “Number of cycles, N” and ranges from 0 to 200 with an interval of 50. Three curves are shown representing different initial displacement values: a red dotted line for “delta u superscript infinite equals 0.02 millimeters,” a green dashed line for “delta u superscript infinite equals 0.016 millimeters,” and a solid black line for “delta u superscript infinite equals 0.012 millimeters.” The black line rises gradually from the bottom left to the top right, and this line runs horizontally for a small distance at the starting and ending points. The green curve starts from the origin and rises rapidly, ending at the top before 50 cycles. The red line runs vertically along the vertical axis. Two inset images are overlaid along the curve: one inset near the early part of the crack curve and one near the end. These show rectangular specimens with elliptical cracks represented by a colormap labeled “phi,” where red indicates high damage and blue indicates undamaged material. The crack shape grows longer in the second inset. Panel “(b)” is located at the bottom left and consists of two 3D rectangular structures, each resembling a stack of parallel, slightly skewed prism-like slabs arranged diagonally. The left model is shaded uniformly in dark green. The right model has the same geometry but includes a full-surface color map overlay, mostly in light green with some red, orange, and yellow patches on the outer surface. The red zones appear concentrated toward the upper and right edges, while the yellow zones are more at the center. Both structures are identical in shape and size, composed of grid-like layers that interlock at a slanted angle. Panel “(c)” is placed at the bottom right and displays four 3D-rendered models arranged horizontally from left to right. Each model has the same angular lattice geometry as the structures in panel (b), consisting of stacked, diagonally sliced volumes made of light gray semi-transparent material. These are labeled in order below each model: “N equals 0,” “N equals 100,” “N equals 200,” and “N equals 300.” The first model, labeled “N equals 0,” shows an entirely gray structure with no markings. In the second model, “N equals 100,” small red elements are scattered sparsely throughout the interior. By “N equals 200,” the red cubes are more numerous and occupy a wider area of the internal volume. In “N equals 300,” the structure contains a dense field of red elements, covering much of the upper and central regions. These red voxel-like patches are embedded irregularly within the lattice, creating a visibly increasing pattern from left to right across the four frames. Note: All numerical data values are approximated.(a) Dimensions (in mm), loading configuration and crack extension versus the number of cycles results for different load ranges have been obtained using the AT1 model, (b) 3D lattice with finite element mesh and deformed shape at a scale factor of 10, (c) Contours of defects in 3D lattice structure (regions with ϕ > 0.95) as a function of the number of loading cycles. Reproduced with permission from the original source (Simoes et al., 2022), figure courtesy of Simoes et al. (2022), Fatigue and Fracture of Engineering Materials and Structures, 2022, Wiley
The figure contains three main panels, labeled “(a),” “(b),” and “(c),” arranged in a grid layout with panel (a) occupying the top half and panels (b) and (c) placed below side-by-side. Panel “(a)” consists of two sub-figures illustrating the simulation of fatigue crack growth in a material. On the left, there is a schematic diagram showing a square specimen under uniaxial tensile loading. The square has a centered horizontal crack and is loaded vertically at the top with an array of upward-pointing arrows labeled “delta u superscript infinite.” The bottom of the square is hinged with multiple triangular symbols with hatched boundaries representing full constraint. The horizontal dimensions of the square are marked as “0.5” on both the left and right halves, and the vertical sides also indicate “0.5” on both the top and bottom halves. To the right of the schematic, there is a plot of “Crack extension, delta a (millimeters)” on the vertical axis with the values ranging from 0 to 0.5 with an interval of 0.1. The horizontal axis is labeled “Number of cycles, N” and ranges from 0 to 200 with an interval of 50. Three curves are shown representing different initial displacement values: a red dotted line for “delta u superscript infinite equals 0.02 millimeters,” a green dashed line for “delta u superscript infinite equals 0.016 millimeters,” and a solid black line for “delta u superscript infinite equals 0.012 millimeters.” The black line rises gradually from the bottom left to the top right, and this line runs horizontally for a small distance at the starting and ending points. The green curve starts from the origin and rises rapidly, ending at the top before 50 cycles. The red line runs vertically along the vertical axis. Two inset images are overlaid along the curve: one inset near the early part of the crack curve and one near the end. These show rectangular specimens with elliptical cracks represented by a colormap labeled “phi,” where red indicates high damage and blue indicates undamaged material. The crack shape grows longer in the second inset. Panel “(b)” is located at the bottom left and consists of two 3D rectangular structures, each resembling a stack of parallel, slightly skewed prism-like slabs arranged diagonally. The left model is shaded uniformly in dark green. The right model has the same geometry but includes a full-surface color map overlay, mostly in light green with some red, orange, and yellow patches on the outer surface. The red zones appear concentrated toward the upper and right edges, while the yellow zones are more at the center. Both structures are identical in shape and size, composed of grid-like layers that interlock at a slanted angle. Panel “(c)” is placed at the bottom right and displays four 3D-rendered models arranged horizontally from left to right. Each model has the same angular lattice geometry as the structures in panel (b), consisting of stacked, diagonally sliced volumes made of light gray semi-transparent material. These are labeled in order below each model: “N equals 0,” “N equals 100,” “N equals 200,” and “N equals 300.” The first model, labeled “N equals 0,” shows an entirely gray structure with no markings. In the second model, “N equals 100,” small red elements are scattered sparsely throughout the interior. By “N equals 200,” the red cubes are more numerous and occupy a wider area of the internal volume. In “N equals 300,” the structure contains a dense field of red elements, covering much of the upper and central regions. These red voxel-like patches are embedded irregularly within the lattice, creating a visibly increasing pattern from left to right across the four frames. Note: All numerical data values are approximated.(a) Dimensions (in mm), loading configuration and crack extension versus the number of cycles results for different load ranges have been obtained using the AT1 model, (b) 3D lattice with finite element mesh and deformed shape at a scale factor of 10, (c) Contours of defects in 3D lattice structure (regions with ϕ > 0.95) as a function of the number of loading cycles. Reproduced with permission from the original source (Simoes et al., 2022), figure courtesy of Simoes et al. (2022), Fatigue and Fracture of Engineering Materials and Structures, 2022, Wiley
5. Conclusion
In conclusion, 4D printing offers a promising avenue for the development of advanced mechanical structures with enhanced damage tolerance, primarily through the integration of smart materials, adaptive designs and self-sensing capabilities. The ability to fabricate structures that respond to external stimuli, combined with the use of innovative materials like metamaterials, provides significant potential for improving the durability and resilience of these systems under dynamic stress conditions. While substantial progress has been made in understanding the fatigue behavior and cyclic loading effects on 4D-printed parts, challenges remain in optimizing the interplay between material properties, design strategies and damage mitigation mechanisms. By advancing these areas, 4D printing could revolutionize industries requiring high-performance materials with self-healing capabilities, paving the way for more resilient and sustainable engineering solutions.
The main objective of the present study is to identify factors influencing damage tolerance in 4D-printed structures and to propose strategies for enhancing durability and resistance to damage. In this context, the roles of self-healing, self-sensing, adaptability and metamaterial-based designs have been considered. Overall, the review of published works on damage tolerance using 4D printing can be summarized as follows:
4D printing enables the fabrication of structures capable of dynamically responding to environmental stimuli, which leads to increased durability and resistance to damage.
The use of smart materials such as SMPs and metamaterials plays a significant role in improving energy absorption, self-healing capabilities and resistance to crack propagation.
Metamaterials designed with bio-inspiration mechanisms demonstrate superior resistance to damage, and by employing uniform stress distribution, they extend the lifespan of structures.
Investigations into the damage tolerance behavior of 4D-printed materials show that certain materials, such as PLA and tBA–AUD SMP, are capable of enduring hundreds of thousands of loading cycles without experiencing complete damage.
There are still challenges in improving damage tolerance in 4D-printed structures, such as optimizing the interaction between material properties, design strategies and damage mitigation mechanisms, but current advancements have positioned this technology as promising for novel applications.
