*2.3. Metal-Based Materials*

For flexible strain sensors, low-dimensional metal nanostructures are very attractive due to their excellent electrical conductivity. In general, silver has better conductivity and stability than copper, and has a lower cost than other precious metals, such as gold. Copper nanowires (CuNWs) are considered as a promising alternative to silver nanowires (AgNWs) due to their comparable electrical and thermal conductivity, abundance and low cost. However, CuNWs have high inherent resistance and contact resistance due to their sensitivity to oxygen and moisture [47]. In addition, liquid metal has been used to prepare strain-sensing yarns. Zhu et al. reported super-stretched conductive fibers by injecting liquid alloy (EGaIn) into hollow SEBS fibers [48]. Due to the electrical continuity of the liquid metal, the fiber can maintain a certain degree of conductivity at a strain of more than 700%. Additionally, its resistance change mainly depends on the real-time geometrical size change when the fiber is stretched, showing less hysteresis and a higher durability. However, the limitation of this method is that the liquid core of the fiber will collapse under concentrated pressure or large strain, although the conductivity can be restored.

Metal nanomaterials can be assembled on the surface of fibers or yarns by methods such as in situ reduction, sputtering, electrochemical deposition and chemical deposition [67]. However, the bonding force between the conductive coating and the polymer fiber layer is usually poor, and the conductive coating easily peels off due to mechanical deformation, resulting in poor stability. Another method is to prepare stretchable conductive composite fibers by filling metal nanomaterials into a polymer matrix with elasticity through traditional spinning technology. However, the poor dispersibility of metal nanomaterials in the polymer matrix can easily lead to the clogging of the spinneret and poor performance of the composite fiber. To solve this issue, Lu et al. proposed using surface-modified AgNWs and elastic polyurethane (PU) to prepare stretchable conductive composite fibers, in which polyethylene glycol (PEG) derivatives were used to modify the surface of AgNWs [43]. The compatibility between the PU and AgNWs was remarkably improved, resulting in a high filling load and the effective dispersion of AgNWs in the PU. It was found that the electrical conductivity of the yarn without surface modification is 147 S/cm, while the electrical conductivity of the yarn with modified AgNWs was 331 S/cm. Although metal nanomaterials can realize the preparation of flexible electronics with good electrical conductivity, metal-based strain sensors are prone to failure due to the fragility and weak interfacial forces of metal. Therefore, it is worth make efforts to

enhance interfacial adhesion, such as the improvement of the interactions between metal nanoparticles and fiber functional groups.

#### *2.4. MXene*

MXene has shown good potential in the field of wearable electronics due to its excellent properties, such as metal-like electrical conductivity, large specific surface area, excellent thermal conductivity, layered structure, etc. [68]. In addition, it has good dispersibility in aqueous solutions due to the large number of functional groups formed on the surface of MXene by hydrofluoric acid etching. Therefore, it is suitable for modifying textiles through solution processing methods. However, exposure to high humidity or air may cause the oxidation of MXene, thereby reducing its various properties, especially electrical properties [16,49]. For example, Gong et al. developed a spandex composite yarn sensor with a composite coating using MXene nanosheets as "bricks" and PDA/Ni2+ as "mortars" through alternate dip-coating methods [69]. The yarn strain sensor has high sensitivity, a low detection limit (0.11%) and a wide sensing range (0.11–61.2%). However, due to the poor oxidation stability of MXene in water, the conductivity of the yarn gradually deteriorates at a temperature of 30–50 ◦C over a 20 h washing cycle.

#### **3. Fabrication and Structure Design**

Fiber- and yarn-based strain sensors are mainly manufactured by spinning and coating. For example, the conductive filler is mixed into the spinning solution to prepare conductive composite fibers. The structure of composite fibers prepared by spinning is round with uniformly distributed conductive materials, or coaxial, porous, hollow, and so on. In terms of coating conductive materials on fibers and yarns, the conductive coating can be designed as a microcrack, fold buckling, multilayer composite structure. Additionally, the geometry of the yarns was designed to control the sensing performance of strain sensors. These preparation strategies and structural design features will be discussed in the following sections. The performances of fiber and yarn strain sensors reported in the literature are summarized in Tables 4–6.

#### *3.1. Conductive Composite Fibers*

#### 3.1.1. Uniform Mixing of Conductive Materials

Traditional spinning techniques, such as wet spinning, dry spinning and melt spinning, are the most common methods to prepare a 1D stretchable conductive composite materials; they mix the conductive filler and the elastic matrix directly and uniformly, and then extrude it through the spinneret hole to a coagulating bath to form the composite fiber. Li et al. uniformly mixed Gr into SBS and prepared SBS/Gr composite fiber flexible strain sensors by a simple wet-spinning method, and the Gr content had a significant impact on the morphology, mechanical properties and electromechanical properties of the composite fiber (Figure 1) [70]. The fiber with the 5 wt% graphene content has a wide working strain, which reaches 100%. However, its sensitivity increases with the increase in strain, and the sensitivity within 50% strain is changeable at different stretching speeds. He et al. proposed multiwalled carbon nanotube/thermoplastic polyurethane (MWCNT/TPU) fibers by wet spinning [71]. The gauge factors (GF) of the MWCNT/TPU fiber are about 550 and 2800 in the strain ranges of 1 to 4% and 5 to 100%, respectively. The strain of the MWCNT/TPU fibers decreases significantly under large hysteresis after multiple stretching–releasing cycles, indicating poor sensing repeat stability. At the same time, the influence of different weight ratios of MWCNTs to TPU on the mechanical and electrical properties of composite fibers has been studied. It was found that the concentration and arrangement of MWCNT would change the working strain range and GF of the sensor [72]. Wang et al. manufactured a fiber strain sensor with a wide response range (320%) and a fast response time (<200 ms) based on MWCNTs and TPU by a simple wet-spinning method [39]. However, the electrical response of the MWCNT/TPU strain sensor decreased slightly in the initial stage when multiple stretching–releasing cycles were carried out

at 100% strain, and it exhibited unstable sensitivity at the same time. To improve the conductivity and the stability of the conductive network, hybrid conductive fillers have been used to achieve a composite synergistic effect to prepare strain-sensing fibers. For instance, Zhang et al. demonstrated a highly conductive AgNW/MWCNT/TPU composite fiber by wet spinning, in which MWCNTs were regarded as the sensitive materials and silver nanowires were used to improve electrical conductivity [73]. When the contents of AgNWs reached the optimal amount (3%), the working strain range was 254%, and the conductivity was 0.0803 S/cm (Figure 2). Compared with single-filler composite fibers, the increase in AgNWs improves the conductivity and working strain range of the composite fiber, but its sensitivity decreases. In the case of a strain range of 50–150%, the relative resistance change of the sensor continues to decrease in stretching–releasing tests within 1000 s, showing poor stability. the conductivity and the stability of the conductive network, hybrid conductive fillers have been used to achieve a composite synergistic effect to prepare strain-sensing fibers. For instance, Zhang et al. demonstrated a highly conductive AgNW/MWCNT/TPU composite fiber by wet spinning, in which MWCNTs were regarded as the sensitive materials and silver nanowires were used to improve electrical conductivity [73]. When the contents of AgNWs reached the optimal amount (3%), the working strain range was 254%, and the conductivity was 0.0803 S/cm (Figure 2). Compared with single-filler composite fibers, the increase in AgNWs improves the conductivity and working strain range of the composite fiber, but its sensitivity decreases. In the case of a strain range of 50–150%, the relative resistance change of the sensor continues to decrease in stretching–releasing tests within 1000 s, showing poor stability.

fiber are about 550 and 2800 in the strain ranges of 1 to 4% and 5 to 100%, respectively. The strain of the MWCNT/TPU fibers decreases significantly under large hysteresis after multiple stretching–releasing cycles, indicating poor sensing repeat stability. At the same time, the influence of different weight ratios of MWCNTs to TPU on the mechanical and electrical properties of composite fibers has been studied. It was found that the concentration and arrangement of MWCNT would change the working strain range and GF of the sensor [72]. Wang et al. manufactured a fiber strain sensor with a wide response range (320%) and a fast response time (<200 ms) based on MWCNTs and TPU by a simple wetspinning method [39]. However, the electrical response of the MWCNT/TPU strain sensor decreased slightly in the initial stage when multiple stretching–releasing cycles were carried out at 100% strain, and it exhibited unstable sensitivity at the same time. To improve

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**Figure 1.** ΔR/R0–strain curve and GF–strain curve of SBS-xGr composite fiber with different graphene contents. (**a**,**d**) SBS-1Gr composite fiber; (**b**,**e**) SBS-3Gr composite fiber; (**c**,**f**) SBS-5Gr composite fiber [70]. **Figure 1.** ∆R/R0–strain curve and GF–strain curve of SBS-xGr composite fiber with different graphene contents. (**a**,**d**) SBS-1Gr composite fiber; (**b**,**e**) SBS-3Gr composite fiber; (**c**,**f**) SBS-5Gr composite fiber [70]. *Textiles* **2022**, *2*, FOR PEER REVIEW 8

**Figure 2.** (**a**) Suspension preparation process; (**b**) AgNW/MWCNT/TPU spinning process; (**c**) the relative change resistance–strain curve of the fiber strain sensor with different AgNW contents [73]. **Figure 2.** (**a**) Suspension preparation process; (**b**) AgNW/MWCNT/TPU spinning process; (**c**) the relative change resistance–strain curve of the fiber strain sensor with different AgNW contents [73].

The conductive network was also designed by controlling the distribution of the fillers, such as selective positioning in multiple phases to form a co-continuous structure or

ing of the fillers at the interface of the co-continuous polymer structure can further reduce the filler content, which is required to form the continuous conductive network. Zhou et al. used the coaxial wet-spinning method and post-treatment process to prepare the thermoplastic elastomer/single-walled carbon nanotube (TPE/SWCNT) ribbon coaxial fiber with good stretchability and high sensitivity (Figure 3a) [38]. The strain sensor composed of this fiber has a GF of 48 at 0–5% strain and a GF of 425 at 20–100% strain; a linear change cannot occur in in the full strain range. Tang et al. designed a stretchable core sheath fiber using a one-step coaxial wet-spinning assembly method, in which a high-stretch polymer elastomer Ecoflex wrapped CNT/Ecoflex composite material [74]. Similar to traditional cables, the outer insulating sheath effectively avoids short circuits and the falling off of conductive fillers. At the same time, it can have good conductivity under a low permeability threshold (0.74 vol%). Strain sensors made of this fiber achieve a high sensitivity of 1378 under 300% strain and show high durability under 100% strain, but they exhibit low sensitivity in a small strain range, non-linear resistance change and obvious overshoot behavior. Yue et al. demonstrated a highly stretchable TPU-CB@TPU fiber strain sensor with a porous core–sheath structure through the coaxial wet-spinning method (Figure 3b,c) [37]. Due to the countercurrent diffusion and coagulation of the solvent, this fiber has a porous structure with a wide strain range. The highest GF is 28,084 when the strain is 204%. However, its sensitivity is not large enough in a small strain range, and the resistance change gradually declines over multiple cycles of stretching. A coaxial fiber with an outer layer of MXene/PU composite and an inner layer of PU was prepared by Seyedin et al. [75]. Compared with the non-coaxial composite fiber, the coaxial fiber shows a larger strain range, a smaller data drift, and an improvement in the cyclic stability of the sensor response. Gao et al. fabricated a coaxial stretchable composite fiber with a double-layer hollow structure (Figure 3d), in which the conductive outer layer has a CNT/TPU composite as the sensitive area, and the insulating inner layer is made of pure TPU with a hollow core to serve as a flexible support [76]. The prepared composite fiber (TPU-8CNT@TPU) has an ultralow percolation threshold (0.17 wt%), good durability, and small compression deformation that can be detected. With an increase in the stretching speed, the relative resistance differently changes under the same strain. Additionally, there is an obvious shoulder phenomenon, which may disturb signal identification in an accurate strain monitoring. However, the reason for this shoulder phenomenon is still not clear. The mainstream is attributed to the competition between the destruction and reconstruction of CNT

conductive networks in the fiber, which needs further verification.

3.1.2. Selective Localization of Conductive Materials

#### 3.1.2. Selective Localization of Conductive Materials

The conductive network was also designed by controlling the distribution of the fillers, such as selective positioning in multiple phases to form a co-continuous structure or a sea-island structure. In this case, the conductivity of the composite is improved by forming a double or triple permeation structure in the polymer matrix. The selective positioning of the fillers at the interface of the co-continuous polymer structure can further reduce the filler content, which is required to form the continuous conductive network. Zhou et al. used the coaxial wet-spinning method and post-treatment process to prepare the thermoplastic elastomer/single-walled carbon nanotube (TPE/SWCNT) ribbon coaxial fiber with good stretchability and high sensitivity (Figure 3a) [38]. The strain sensor composed of this fiber has a GF of 48 at 0–5% strain and a GF of 425 at 20–100% strain; a linear change cannot occur in in the full strain range. Tang et al. designed a stretchable core sheath fiber using a one-step coaxial wet-spinning assembly method, in which a high-stretch polymer elastomer Ecoflex wrapped CNT/Ecoflex composite material [74]. Similar to traditional cables, the outer insulating sheath effectively avoids short circuits and the falling off of conductive fillers. At the same time, it can have good conductivity under a low permeability threshold (0.74 vol%). Strain sensors made of this fiber achieve a high sensitivity of 1378 under 300% strain and show high durability under 100% strain, but they exhibit low sensitivity in a small strain range, non-linear resistance change and obvious overshoot behavior. Yue et al. demonstrated a highly stretchable TPU-CB@TPU fiber strain sensor with a porous core–sheath structure through the coaxial wet-spinning method (Figure 3b,c) [37]. Due to the countercurrent diffusion and coagulation of the solvent, this fiber has a porous structure with a wide strain range. The highest GF is 28,084 when the strain is 204%. However, its sensitivity is not large enough in a small strain range, and the resistance change gradually declines over multiple cycles of stretching. A coaxial fiber with an outer layer of MXene/PU composite and an inner layer of PU was prepared by Seyedin et al. [75]. Compared with the non-coaxial composite fiber, the coaxial fiber shows a larger strain range, a smaller data drift, and an improvement in the cyclic stability of the sensor response. Gao et al. fabricated a coaxial stretchable composite fiber with a double-layer hollow structure (Figure 3d), in which the conductive outer layer has a CNT/TPU composite as the sensitive area, and the insulating inner layer is made of pure TPU with a hollow core to serve as a flexible support [76]. The prepared composite fiber (TPU-8CNT@TPU) has an ultralow percolation threshold (0.17 wt%), good durability, and small compression deformation that can be detected. With an increase in the stretching speed, the relative resistance differently changes under the same strain. Additionally, there is an obvious shoulder phenomenon, which may disturb signal identification in an accurate strain monitoring. However, the reason for this shoulder phenomenon is still not clear. The mainstream is attributed to the competition between the destruction and reconstruction of CNT conductive networks in the fiber, which needs further verification.

**Figure 3.** (**a**) The image of a typical coaxial fiber stretched from 0 to 250% strain and relaxed after unloading; D and Lc are the average crack spacing and the average crack opening displacement, respectively [38]. (**b**) Fiber cell structure evolution process (**c**) Schematic diagram of the TCTF preparation process [37]. (**d**) Schematic diagram of TPU-8CNT@TPU structure [76]. **Figure 3.** (**a**) The image of a typical coaxial fiber stretched from 0 to 250% strain and relaxed after unloading; D and Lc are the average crack spacing and the average crack opening displacement, respectively [38]. (**b**) Fiber cell structure evolution process (**c**) Schematic diagram of the TCTF preparation process [37]. (**d**) Schematic diagram of TPU-8CNT@TPU structure [76].

The characteristics of various fiber-based strain sensors prepared by spinning technology are summarized in Table 4. In general, the preparation of stretchable conductive composite fibers as strain sensors by mixing conductive materials and spinning is a process technology that can be produced on a large scale and is widely used in industry. However, the addition of conductive filler will enhance the rigidity of the elastic matrix, and shrink the tensile strain range of the fiber, which leads to the narrow working strain range of the fiber sensor. On the contrary, if the amount of conductive material is too low, the conductivity of the composite fiber will also limit its working strain range. Therefore, there is a paradox between the conductivity and the working strain range of the stretchable conductive fiber, which needs to be balanced. According to the percolation theory [60,77–81], the content of conductive materials in stretchable conductive composites has a percolation threshold. When the percolation threshold is exceeded, the polymer elastomer changes from an insulator to a conductor, and the conductivity increases with the increase in the content of conductive materials. When the content is near the percolation threshold, the sensitivity of the material is at its greatest [82]. Therefore, it is still a huge challenge to achieve a high strain range and high sensitivity at the same time for conductive composite fibers. In addition, there is a limit on the production costs of practical commercial applications with the increase in conductive fillers. To reduce the permeation threshold while achieving high conductivity, different strategies have been studied [50,83,84], such as functionalizing conductive fillers' surfaces, increasing the aspect ratio of fillers, controlling the arrangement of fillers, and using different mixture of fillers. However, such permeation-based composite strain sensors rarely exhibit good linearity. When the composite fiber is stretched, its resistance is mainly caused by changes in geometry and tunnel theory [37,39,85]. With an increase in tunneling distance and the destruction of the conductive path, the resistance of composites increases significantly during the tensile process. The maximum GF usually occurs when the conductive material content is close to the permeation threshold. Other shortcomings of strain sensors made of composite fibers include hysteresis, fatigue and so on, which are mostly due to the viscoelasticity and elastic recov-The characteristics of various fiber-based strain sensors prepared by spinning technology are summarized in Table 4. In general, the preparation of stretchable conductive composite fibers as strain sensors by mixing conductive materials and spinning is a process technology that can be produced on a large scale and is widely used in industry. However, the addition of conductive filler will enhance the rigidity of the elastic matrix, and shrink the tensile strain range of the fiber, which leads to the narrow working strain range of the fiber sensor. On the contrary, if the amount of conductive material is too low, the conductivity of the composite fiber will also limit its working strain range. Therefore, there is a paradox between the conductivity and the working strain range of the stretchable conductive fiber, which needs to be balanced. According to the percolation theory [60,77–81], the content of conductive materials in stretchable conductive composites has a percolation threshold. When the percolation threshold is exceeded, the polymer elastomer changes from an insulator to a conductor, and the conductivity increases with the increase in the content of conductive materials. When the content is near the percolation threshold, the sensitivity of the material is at its greatest [82]. Therefore, it is still a huge challenge to achieve a high strain range and high sensitivity at the same time for conductive composite fibers. In addition, there is a limit on the production costs of practical commercial applications with the increase in conductive fillers. To reduce the permeation threshold while achieving high conductivity, different strategies have been studied [50,83,84], such as functionalizing conductive fillers' surfaces, increasing the aspect ratio of fillers, controlling the arrangement of fillers, and using different mixture of fillers. However, such permeation-based composite strain sensors rarely exhibit good linearity. When the composite fiber is stretched, its resistance is mainly caused by changes in geometry and tunnel theory [37,39,85]. With an increase in tunneling distance and the destruction of the conductive path, the resistance of composites increases significantly during the tensile process. The maximum GF usually occurs when the conductive material content is close to the permeation threshold. Other shortcomings of strain sensors made of composite fibers include hysteresis, fatigue and so on, which are mostly due to the viscoelasticity and elastic recovery rate of composite fibers.

ery rate of composite fibers.


**Table 4.** Characteristics of conductive composite fiber-based strain sensors prepared by spinning technology.

### *3.2. Conductive Coated Fibers*

#### 3.2.1. Microcrack Structure

Coating conductive materials on stretchable fibers or yarns is another way to prepare one-dimensional strain sensors by dipping, spraying, and in situ chemical polymerization, etc. The dip-coating method is one of the easiest and most widely used methods among them, due to its simple, fast and cost-effective characteristics. For example, Lee et al. reported a conductive PU multifilament coated uniformly AgNPs by an in situ reduction method, with low initial resistance (0.16 Ω/cm) (Figure 4a,b) [45]. AgNPs are uniformly distributed inside the multifilament and form a dense shell on the outer layer. The GF of the strain sensor reaches about 9.3 <sup>×</sup> <sup>10</sup><sup>5</sup> (under 450% strain) when the strain sensor is first stretched, while the GF decreases to 659 (under 450% strain) after subsequent stretching. Although the strain sensor has high sensitivity and wide strain range, its sensitivity is unstable and its linearity is poor. Generally speaking, the microcrack structure constructed by the strain sensor in tension is an effective method to achieve a sensing response and high sensitivity of sensors. However, the microcrack structure is usually limited by strain range. Compared with monofilament, the increase in the number of multifilament structures greatly widens its working strain range according to the theory (Figure 4c,d) [45]. Eom et al. first polymerized conductive PEDOT on polyester (PS) fibers by in situ polymerization to prepare conductive coated fibers, and then embedded this conductive fiber into fabrics to manufacture textile-based strain/touch/pressure sensors and user interface (UI) equipment [36]. Due to the multifilament structure of its PEDOT/PS fiber, the resistance of the sensor tends to fall with the increase in strain, which is contrary to the common trend. During stretching, the overall conductivity of the PEDOT/PS multifilament increases, and the PEDOT/PS monofilament exhibits the opposite behavior. Liu et al. designed a monofilament strain sensor with a beaded structure using the Plateau– Rayleigh instability principle. The way to control the strain distribution along the fiber axis is by adjusting the size of the microbeads and the distance between the microbeads (Figure 5) [88]. This design effectively causes strain concentration and amplifies the local strain. Compared with a single uniform monofilament, the sensitivity of the sensor with a beaded structure is significantly improved. Overall, the sensitivity of the sensor with the crack effect usually increases significantly and then decreases, which is a characteristic of nonlinear sensing [45]. Due to the destruction and shedding of the conductive layer, the sensor also exhibits a certain amount of hysteresis and poor cycle stability.

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axis is by adjusting the size of the microbeads and the distance between the microbeads (Figure 5) [88]. This design effectively causes strain concentration and amplifies the local strain. Compared with a single uniform monofilament, the sensitivity of the sensor with a beaded structure is significantly improved. Overall, the sensitivity of the sensor with the crack effect usually increases significantly and then decreases, which is a characteristic of nonlinear sensing [45]. Due to the destruction and shedding of the conductive layer, the

axis is by adjusting the size of the microbeads and the distance between the microbeads (Figure 5) [88]. This design effectively causes strain concentration and amplifies the local strain. Compared with a single uniform monofilament, the sensitivity of the sensor with a beaded structure is significantly improved. Overall, the sensitivity of the sensor with the crack effect usually increases significantly and then decreases, which is a characteristic of nonlinear sensing [45]. Due to the destruction and shedding of the conductive layer, the

sensor also exhibits a certain amount of hysteresis and poor cycle stability.

sensor also exhibits a certain amount of hysteresis and poor cycle stability.

**Figure 4.** (**a**) The electrical conductivity of the sensor under different strains; (**b**) SEM images of the fiber strain sensor at ε = 20%; (**c**) the resistance model of the double-filament strain sensor and the corresponding equivalent circuit; (**d**) the relationship between the electrical conductivity of the single-filament/multifilament fiber strain sensor and the tensile strain; *n* is the number of multiple filaments in the fiber strain sensor [45]. **Figure 4.** (**a**) The electrical conductivity of the sensor under different strains; (**b**) SEM images of the fiber strain sensor at ε = 20%; (**c**) the resistance model of the double-filament strain sensor and the corresponding equivalent circuit; (**d**) the relationship between the electrical conductivity of the single-filament/multifilament fiber strain sensor and the tensile strain; *n* is the number of multiple filaments in the fiber strain sensor [45]. fiber strain sensor at ε = 20%; (**c**) the resistance model of the double-filament strain sensor and the corresponding equivalent circuit; (**d**) the relationship between the electrical conductivity of the single-filament/multifilament fiber strain sensor and the tensile strain; *n* is the number of multiple filaments in the fiber strain sensor [45].

**Figure 4.** (**a**) The electrical conductivity of the sensor under different strains; (**b**) SEM images of the

[88]. **Figure 5.** (**a**) Finite element simulation to study the strain adjustment effect of microstructured fibers compared with flat fibers; (**b**) the strain distribution of different structures along the fiber surface **Figure 5.** (**a**) Finite element simulation to study the strain adjustment effect of microstructured fibers compared with flat fibers; (**b**) the strain distribution of different structures along the fiber surface [88].

compared with flat fibers; (**b**) the strain distribution of different structures along the fiber surface

#### 3.2.2. Wrinkle Structure

[88].

In order to improve the workable strain range, a conductive coating with a wrinkle structure was added to the fiber surface to design a flexible strain sensor. Wang et al. designed a highly stretchable NTSm@rubber@fiber strain sensor with a dual-sheath buckling structure by the pre-stretching method, in which NTS is the carbon nanotube sheets and m represents the number of NTS layers (Figure 6a) [89]. The elastic support fiber coaxially coated a curved rubber intermediate layer and a curved NTS conductive layer. At the same time, the GF of the sensor was controlled by changing the manufacturing

parameters to adjust the buckling structure, but its overall sensitivity values were very low, only 0.5 (0–200%) and 0.14 (200–600%). The design of a wrinkle structure makes the strain sensor bear high tensile deformation without destroying the conductivity of the material, thereby increasing its sensing range. However, it also causes a small resistance change in the stretched state, showing lower sensitivity. As shown in Figure 6b, CNT ink/PU yarns with a wrinkle-assisted crack microstructure were created by Sun et al. [90]. The yarn sensors have an ultralow detection limit and excellent repeat stability. As mentioned above, the complex and multistep manufacturing process poses challenges to realize a large-scale production of strain sensors. same time, the GF of the sensor was controlled by changing the manufacturing parameters to adjust the buckling structure, but its overall sensitivity values were very low, only 0.5 (0–200%) and 0.14 (200–600%). The design of a wrinkle structure makes the strain sensor bear high tensile deformation without destroying the conductivity of the material, thereby increasing its sensing range. However, it also causes a small resistance change in the stretched state, showing lower sensitivity. As shown in Figure 6b, CNT ink/PU yarns with a wrinkle-assisted crack microstructure were created by Sun et al. [90]. The yarn sensors have an ultralow detection limit and excellent repeat stability. As mentioned above, the complex and multistep manufacturing process poses challenges to realize a large-scale production of strain sensors.

In order to improve the workable strain range, a conductive coating with a wrinkle structure was added to the fiber surface to design a flexible strain sensor. Wang et al. designed a highly stretchable NTSm@rubber@fiber strain sensor with a dual-sheath buckling structure by the pre-stretching method, in which NTS is the carbon nanotube sheets and m represents the number of NTS layers (Figure 6a) [89]. The elastic support fiber coaxially coated a curved rubber intermediate layer and a curved NTS conductive layer. At the

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3.2.2. Wrinkle Structure

**Figure 6.** (**a**) The manufacturing steps of NTS m @rubber@fiber, the longitudinal cross-sections of the fibers of different manufacturing steps are shown below the rubber fiber. Yellow, red and gray are used for SEBS core, SGE layer and NTS sheath, respectively [89]. (**b**) Schematic diagram of preparation of WCMYSS [90]. **Figure 6.** (**a**) The manufacturing steps of NTS m @rubber@fiber, the longitudinal cross-sections of the fibers of different manufacturing steps are shown below the rubber fiber. Yellow, red and gray are used for SEBS core, SGE layer and NTS sheath, respectively [89]. (**b**) Schematic diagram of preparation of WCMYSS [90].

#### Building a multilayered structure at the fiber scale is another way to design flexible 3.2.3. Multilayer Structure

3.2.3. Multilayer Structure

strain sensors. Cao et al. introduced a AgNW/PU fiber with a composite multilayer structure by using an adhesive layer with adjustable adhesion to adjust the interface adhesion and fiber microstructure (Figure 7a) [91]. The GF and stretchability of the strain sensor were adjusted by changing the interface layer combination (Figure 7b). However, its sensitivity was weak and the resistance response was nonlinear. After 100 and 1000 cycles of stretching at 10% strain, the drift rate values of the relative resistance of the sensor were 29.4 and 53.1%, respectively, showing poor repeatability. Liu et al. reported the silver plating polyurethane filaments (SPPF) with good electrical resistivity (4.5 ± 0.1 Ω/cm) [92]. These AgNPs are bound to the surface of the filament by polydopamine, which remarkably improves the bonding between the conductive material and the fiber interface, but the nonlinear error and hysteresis of the SPPF strain sensor are up to 29.3 and 34.3%, respectively. The layer-by-layer (LBL) assembly method has been used to develop strain sensors Building a multilayered structure at the fiber scale is another way to design flexible strain sensors. Cao et al. introduced a AgNW/PU fiber with a composite multilayer structure by using an adhesive layer with adjustable adhesion to adjust the interface adhesion and fiber microstructure (Figure 7a) [91]. The GF and stretchability of the strain sensor were adjusted by changing the interface layer combination (Figure 7b). However, its sensitivity was weak and the resistance response was nonlinear. After 100 and 1000 cycles of stretching at 10% strain, the drift rate values of the relative resistance of the sensor were 29.4 and 53.1%, respectively, showing poor repeatability. Liu et al. reported the silver plating polyurethane filaments (SPPF) with good electrical resistivity (4.5 ± 0.1 Ω/cm) [92]. These AgNPs are bound to the surface of the filament by polydopamine, which remarkably improves the bonding between the conductive material and the fiber interface, but the nonlinear error and hysteresis of the SPPF strain sensor are up to 29.3 and 34.3%, respectively.

with multilayer structures. The LBL assembly method has been reported as an effective method for manufacturing carbon-based films. Instead of simple deposition, this process includes repeated immersion and evaporation, and various reactions such as electrostatic The layer-by-layer (LBL) assembly method has been used to develop strain sensors with multilayer structures. The LBL assembly method has been reported as an effective method for manufacturing carbon-based films. Instead of simple deposition, this process includes repeated immersion and evaporation, and various reactions such as electrostatic interactions, hydrogen bonding, or covalent bonding to enhance the adhesion of the interface [93]. Li et al. prepared a strain sensor using graphene/polyvinyl alcohol (Gr/PVA) composite material as the outer layer conductive sheath and polyurethane as the elastic core fiber [94]. When the Gr concentration is 1wt% and the number of coatings is nine, the composite coated fiber has the maximum GF (86.9) and a wide strain range (50%) and good linearity (R<sup>2</sup> = 0.97). However, the GF of the strain sensor only reaches more than 40 in the 50% strain extension–release cycles, and the repeatability is 1.81% and the hysteresis error is 9.08% over 100 cycles. A CPC@PU yarn strain sensor was prepared by Wu et al. (Figure 7c) [34], in which the ultrathin conductive CPC layer consists of positively charged chitosan (CS) and negatively charged carbon black (CB)/cellulose nanocrystal (CNC)/natural rubber (NR) nanohybrid. Although this fiber sensor based on CPC coating detects strains as low as 0.1% and shows a GF of approximately 38.9 at 1% strain, it is not reliable for detecting strains larger than 5%. Li et al. proposed a core–sheath structure strain sensor, which is composed of PU core yarn, a highly conductive multilayer sheath material, namely graphene nanosheets/thin gold film/graphene nanosheets (GNSs/Au/GNSs), and PDMS coating. This multilayer structure combination can simultaneously achieve high sensitivity, wide strain-sensing range and good waterproof performance. In 10,000 stretch–release cycles at 50% strain, its stability is excellent [42]. Although the LBL method improves the adhesion of the coating, it takes multiple cycles of treatment to achieve a high conductivity due to the introduction of the insulating polymer. ural rubber (NR) nanohybrid. Although this fiber sensor based on CPC coating detects strains as low as 0.1% and shows a GF of approximately 38.9 at 1% strain, it is not reliable for detecting strains larger than 5%. Li et al. proposed a core–sheath structure strain sensor, which is composed of PU core yarn, a highly conductive multilayer sheath material, namely graphene nanosheets/thin gold film/graphene nanosheets (GNSs/Au/GNSs), and PDMS coating. This multilayer structure combination can simultaneously achieve high sensitivity, wide strain-sensing range and good waterproof performance. In 10,000 stretch–release cycles at 50% strain, its stability is excellent [42]. Although the LBL method improves the adhesion of the coating, it takes multiple cycles of treatment to achieve a high conductivity due to the introduction of the insulating polymer.

interactions, hydrogen bonding, or covalent bonding to enhance the adhesion of the interface [93]. Li et al. prepared a strain sensor using graphene/polyvinyl alcohol (Gr/PVA) composite material as the outer layer conductive sheath and polyurethane as the elastic core fiber [94]. When the Gr concentration is 1wt% and the number of coatings is nine, the composite coated fiber has the maximum GF (86.9) and a wide strain range (50%) and good linearity (R2 = 0.97). However, the GF of the strain sensor only reaches more than 40 in the 50% strain extension–release cycles, and the repeatability is 1.81% and the hysteresis error is 9.08% over 100 cycles. A CPC@PU yarn strain sensor was prepared by Wu et al. (Figure 7c) [34], in which the ultrathin conductive CPC layer consists of positively charged chitosan (CS) and negatively charged carbon black (CB)/cellulose nanocrystal (CNC)/nat-

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**Figure 7.** (**a**) Schematic diagram of the longitudinal section of Ag NW/PU fiber (**b**) Modeling of the resistance change and strain of Ag NW/PU fiber with different interface bonding strengths [91] (**c**) Schematic of the preparation of CPC@PU yarn by the LBL assembly process [34]. **Figure 7.** (**a**) Schematic diagram of the longitudinal section of Ag NW/PU fiber (**b**) Modeling of the resistance change and strain of Ag NW/PU fiber with different interface bonding strengths [91] (**c**) Schematic of the preparation of CPC@PU yarn by the LBL assembly process [34].

The characteristics of fiber strain sensors prepared by coating technology are summarized in Table 5. In general, the coating method is easy to implement and the 1D strain sensors produce via this method show good sensing performance. As the mechanical The characteristics of fiber strain sensors prepared by coating technology are summarized in Table 5. In general, the coating method is easy to implement and the 1D strain sensors produce via this method show good sensing performance. As the mechanical properties of conductive coatings and elastic substrates are inconsistent, conductive coatings propagate small and dense microcracks, which destroys conductive networks and causes the changes of resistance. However, the poor adhesion and the mechanical mismatch between the elastic substrate and the conductive coating often leads to degradation of the sensor response. Therefore, it is still a big challenge to achieve high linearity and cycle stability by a simple coating. Due to the irreversible fracture and shedding of the conductive layer, it is very necessary to explore the stress distribution and interface strength between the conductive coating and the substrate. Although the added adhesive (like the LBL method) has improved adhesion, the fatigue durability of the strain sensor is still a challenge. Additionally, there is a lack of systematic studies on how to control the crack propagation and stability, and on how it affects the sensing performance of strain sensors.


**Table 5.** Characteristics of fiber strain sensors prepared by coating technology.
