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Abstract

Smart wearable electronic devices with superb sensing performance have aroused superb attention in recent years. However, designing an admirable strain sensor with the excellent balance between superior sensitivity and excellent stretchability remains a major challenge. Herein, we developed a conductive polydopamine-coated poly (ethylene terephthalate)/polyurethane fabric as the wearable strain sensor with the layered generating structure and the cooperative effect of carboxylated carbon nanotubes and reduced graphene oxide via self-assembly intercalation process. Obviously, the cooperative conductive effect of conductive fillers endowed the fabric with a superb integration of tunable strain sensitivity (0–265.48), outstanding electromechanical performance, great stretchability (0–220%), excellent heating performance, and long-term stability and repeatability under different strains over 2500 cycles. Especially, the as-prepared sensor was used for the detection of tiny body movements and vigorous human motions, indicating its further impressive prospect in wearable smart electronics. Therefore, such the proposed sensor with the layered generating structure exhibited remarkable potential for developing the flexible wearable electronic device of integrated sensing property and excellent electromechanical performance.

Keywords

Polydopamine wearable electronic devices carboxylated carbon nanotubes reduced graphene oxide poly (ethylene terephthalate)/ polyurethane fabric human movement detection

Introduction

Smart wearable electronic devices with superb sensing performance and excellent electromechanical stability. They have aroused considerable attention on account of their promising prospects in smart robots,¹ electronic skin,² sensors,³ and human movement monitoring recently.⁴ Among them, flexible strain sensors have extensively been investigated to detect diverse activities while healthcare problems and the preparation of these desirable strain sensors are of substantive importance in meeting various requirements containing tunable sensitivity, excellent stretchability, superb electrical heating performance.⁵ The currently fabricated methods of flexible strain sensors are mainly by coating conductive fillers containing carbon nanotubes (CNTs),⁶ reduced graphene oxide (rGO)⁷ onto the surface of elastomeric substrates^8–10 including textile, thermoplastic polyurethane (TPU) via chemical/physical treatment techniques. As an example, a facial fabrication¹¹ of the thermoplastic polyurethane (TPU) coated with rGO, which possessed excellent electrical property but the comparatively inferior GF (gauge factor) 11 and 79 in a sensing range of 0–10%, 10–100% respectively by the ultrasonication technique. Likewise, Yang et al. reported a wearable sensor¹² with a low sensitivity of 26 at a strain of 0–14% fabricated by growing rGO onto polyester knitted textile to monitor body motions. Additionally, Ren et al. developed a conductive rGO-anchored polyester fabric¹³ with negative resistance variation and a strain range of 0–8 % via the thermal reduction process. But the developed strain sensor did not present a substantial promising application owing to the high thermal reduction temperature and the inferior stretchability in wearable electronic devices. Other sensors, especially developed elastic substrates with CNTs sheets,¹⁴ displayed poor sensitivity and low stretchability. Thus, designing an admirable strain sensor remains a major challenge by structure design.

In recent years, researchers have effectively solved the above problems by designing the microstructure of the sensing layer of flexible strain sensor. One of the excellent approaches to solve this problem is incorporating some conductive fillers to construct a more stable and cooperative conductive network structure on the elastomeric substrate surface and to improve the sensing performance, such as carboxylated carbon nanotubes (CNTs-COOH), rGO. The reasonable design of the conductive layer presents a new opportunity for gaining tunable sensitivity while retaining excellent stretchability in such cooperative layered strain sensors with CNTs and rGO. Recently, some flexible strain sensors based on the flexible substrate with the synergistic laminated conductive network structure have attracted tremendous attention from researchers. For instance, Shi et al. designed a flexible strain sensor with graphene-bridged CNTs via the drop-casting process, which achieved high sensitivity but comparatively low stretchability.¹⁵ Liu et al.¹⁶ developed successively the thermoplastic polyurethane (TPU) decorated with CNTs and rGO for wearable strain sensors through a dip-coating approach, but the proposed strain sensor with the narrow strain range of 0–30% exhibited poor conductivity because of the low deposition of fillers on the TPU surface. Some other strain sensors with the cooperative effect of CNTs and rGO have been prepared via some microstructure design techniques containing blending,¹⁷ surface generating,¹⁸ or other approaches.^19,20 While they could hardly obtain both outstanding stretchability and tunable sensitivity. Therefore, it is still a challenge to prepare high-performance flexible sensors with microstructure design by simple processes. In addition, the superb adhesion between flexible substrates and conductive fillers was vital prospect in the development of flexible wearable electronic devices. Polydopamine (PDA)^21–24 with many functional groups including catechol, amine, and imine largely enhances the adhesion of conductive layer on the flexible matrix surface. Meanwhile, the interaction between CNTs-COOH and rGO improves the dispersion of entangled rGO and CNTs-COOH themselves, thus forming synergistic conductive network structure, which leads to the improvement of mechanical and electrical performances.^25,26

Herein, we proposed the combination of facile layered generating structure and collaborative effect of CNTs-COOH and rGO on the strain sensor surface via self-assembly intercalation technique. The inherent performance of poly (ethylene terephthalate)/polyurethane (PET/PU) fabric endowed outstanding physical property, and the PDA, as a versatile platform, demonstrated the superior adhesion on the PET/PU fabric surface. Subsequently, CNTs-COOH and rGO were evenly and constantly generated on the PDA-grown PET/PU fabric surface through the strong bonding. Finally, Strain sensing properties, human motion characteristics, workable strain response mechanism, electromechanical and electrothermal performances of the sensor were studied. Impressively, the obtained sensor revealed tunable strain sensitivity (0–265.48), great stretchability (0–220%), and outstanding stability and repeatability over 2500 cycles, superb stability under various strain ranges, fascinating electromechanical and electrothermal performances. More importantly, such the as-prepared strain sensor with excellent stretchability and tunable sensitivity by a feasible method, which enables it to detect tiny body movements and robust human motions as wearable strain sensors integrating multifunction.

Experimental

Materials

PET/PU fabrics were supplied from Wujiang Shuntai Textile Co., Ltd., Suzhou, China. Dopamine hydrochloride was Sinopharm Chemical Reagent Co., Ltd, China. Carbon nanotubes and GO were obtained from Suzhou Tanfeng Graphene Technology Co., Ltd, China. L-ascorbic acid (LAA) was purchased from Shanghai Titan Technology Co., Ltd.

Preparation of PDA-templated PPFs

PET/PU fabrics (PPFs) were added into the mixed solution with dopamine solution (1.5 mg/mL) and a tris buffer solution (0.5 M) stirring (75 r/min) for 12 h. Subsequently, these fabrics were washed with water and dried at 80°C.

Fabrication of GCPPPFs

PPPFs (1 × 6 cm²) were soaked in a Teflon container with GO dispersions (20 mM) and CNTs-COOH (25 mM) (GCPPPFs) with ultrasonic treatment for 15 min at 55°C. Subsequently, the obtained sample with GO was soaked in L-ascorbic acid solution (35 mM) for 20 min at 85°C to reduce the GO on the sample surface. Finally, PPPFs containing CNTs-COOH and rGO (GCPPPFs) were washed with water and dried at 60°C. The preparation process of GCPPPFs is depicted in Figure 1.

Figure 1.

Schematics for the preparation of GCPPPF.

Characterization and measurements

Scanning electron microscopy (SEM, FE-SEM, JEOL JSM-7500F) was conducted to observe the surface morphology. The Swiss TEXTEST FX 3150 fabric moisture permeability tester was used to measure the moisture permeability of PET/PU fabric before and after modification, which was determined in accordance with the GB/T 12704. 1-2009 Moisture Permeability of Textile Fabrics standards. YG461Z full-automatic air permeability tester is used to perform the air permeability of PET/PU fabric before and after modification. It was determined in accordance with the GB/T 5453-1997 Determination of Air Permeability of Textile Fabrics. X-ray photoelectron spectroscopy was performed to investigate the surface chemical states. The thermal performances of GCPPPFs were demonstrated by thermal gravimetric analysis (TGA) (TGA-Q500, TA Instruments Corporation, USA), dynamic mechanical analyzer (TA: DMA Q 800, TA Instruments, New Castle, DE, USA), and DSC analyzer (Mettler Toledo, Mettler Toledo, Columbus, OH, USA). The relative change in electrical resistance was measured by the formula

\frac{∆ R}{R_{0}} = \frac{(R - R_{0})}{R_{0}}

(1-1)

Where R₀ and R were the primary resistance and the testing resistance.

Results and discussion

Material preparation

We developed a sensor with a facile layered generating conductive network structure (Figure 2(a) and Figure S1). The incorporation of PDA with many functional groups including catechol, amine, and imine endowed the flexible matrix with exceptional interface adhesion effect via self-assembly. CNTs-COOH and rGO were subsequently grown on the PPPF surface via the dip-coating process (Figure S2). Thus, the deposition of the PDA served as a superb nanocarrier for the generating of CNTs-COOH and rGO, and acted as plenty of cross-linking points to improve the uniform distribution of conductive fillers. As the strain was applied, rGO served as a hub via point-line mode, which formed numerous connection points²⁷ and led to more effective stress transfer (Figures 2(b) and (c) and Figure S3). This thus improved the uniformity of sensitive materials on the PPPF surface and constructed the more stable synergistic conductive network.

Figure 2.

(a) The preparation process of GCPPPFs, (b) The generating process of CNTs-COOH, (c) The growing process of rGO@CNTs-COOH on the sensor surface.

Electro-mechanical property

The incorporation of rGO and CNTs-COOH in PPFs with PDA endowed the electrical conductivity. Notably, the mechanical property of PPFs evidenced from the stress-strain curves revealed in Figure S11a. Interestingly, the tensile strength tremendously increased from 45.07 ± 0.5 MPa for PPFs to 62.12 ± 1.2 MPa for GCPPPFs. These results implied the mechanical performance of GCPPPFs was immensely improved. It also was possible that the addition of PDA molecules greatly improved the adhesion between rGO/CNTs-COOH and the elastomer substrate as numerous mortars. CNTs-COOH and rGO due to their outstanding tensile strength²⁸ diffused into the PDA largely increased as plenty of bricks the interfacial interaction, thereby further facilitating the improvement of mechanical properties of GCPPPFs. Moreover, the strain-sensing performance of GCPPPFs as strain sensors was investigated in Figure S11b. The sensor also presented great sensitivity and stretchability of 40.25 and 0–50%, 85.72 and 50–100%, 182.21 and 150–230%, and 265.48 and 230–270% respectively. Notably, the GCPPPF remarkably exhibited the superior sensitivity in composition with that of reported strain sensors,^11,12 which was ascribed to the facile layered generating structure and cooperative effect of CNTs-COOH and rGO on the strain sensor surface. As a strain sensor, the resistance of GCPPPFs generally increased after performing some repetitive stretching-releasing tests. Figure S11c depicts excellent current-voltage (I−V) curves of the sensor under different strain ranges. The sensor revealed wonderful linear I-V performance at different strains implying the outstanding construction of conductive pathways on the PPPFs surface. Furthermore, the bending tests were confirmed (Figure S11d). The resistance of GCPPPFs did not illustrate an obvious change after bending tests, implying that the sensor possessed excellent sensing property. In addition, the sensor wired to a LED lamp at a 1.5 V voltage exhibited some distinct variations in light intensity under various strain ranges (Figure S12a-h). Interestingly, it still showed an apparent brightness when the sensor was stretched to 200%. This indicated that the sensor presented excellent conductivity.

Strain sensing property

The response time of the sensor was critical to evaluate the performance of sensor. Obviously, the response time and relaxation time of the sensor were 30 and 50 ms respectively at the strain of 5%, indicating that the sensor was capable of monitoring complicated muscle movements (Figure 3(a)). Moreover, the sensing stability of the sensor corresponding to various frequencies under a strain of 5% is demonstrated in Figure 3(b). Remarkably, the resistance response signal was stable and consecutive, suggesting superb sensing property and fast response. To furthermore demonstrate the stability and reproducibility of proposed strain sensors, Figures 3(c)–(f) and Figure S13 exhibit the relative resistance change of GCPPF strain sensors in different strain ranges over 2500 stretching-releasing tests. As expected, the resistance response signal of the sensor was stable after performing some repeated stretching-releasing process. Meanwhile, the relative resistance change demonstrated almost periodic variation over 2500 cycles, suggesting that the sensor exhibited remarkable stability and reproducibility, as well as excellent mechanical durability under various strain situations. This was ascribed to the remarkable binding between conductive fillers and PPFs. Additionally, the strain mechanism of the sensor was verified (Figure 4). The initial resistance model included three conductive pathways comprised of R₁-R_a1-R₂-R_a1, R_a1-R₂-R_a1-R_1, and R_a1-R₂-R_a2-R_a1, respectively (Figures 4(a) and (c)). R₁ and R₂ were the resistances of the sensor in the horizontal and vertical direction, respectively. R_a1 was the contact resistance between horizontal and vertical loops. R_a2 was the contact resistance of adjacent loops in the vertical direction. And the resistance of each path was defined as R_m, R_n, and R_p, respectively. Thus, the resistance of each path was obtained using the formula^29–32

R_{m} = R_{1} + R_{2} + 2 R_{a 1}

(1-2)

R_{n} = R_{1} + R_{2} + 2 R_{a 1}

(1-3)

R_{p} = R_{2} + 2 R_{a 1} + R_{a 2}

(1-4)

Figure 3.

(a) Fast response of the GCPPPF at a strain of 5%, (b) The ΔR/R₀ response of the GCPPPF at three diverse frequencies at a strain of 5%, (c–f) Excellent stability of the sensor over 2500 cycles at different strains (5,50, 100, and 200%).

Figure 4.

(a) and (c) Demonstration of the resistance model of the GCPPF, (b) Resistance model under the applied strain.

R_m is equal to R_n. Thus, the total initial resistance (R) could be evaluated as

R = 1 / (\frac{1}{R_{m}} + \frac{1}{R_{n}} + \frac{1}{R_{p}}) = (R_{m} * R_{p}) / (R_{m} + 2 R_{p})

(1-5)

In the original status, the intermeshing of the horizontal and vertical loops and the adjacent vertical loops imparted the higher contact resistance R_a1 and R_a2 to the sensor in comparison with the resistances R₁ and R₂. And the resistances R₁ and R₂ could be omitted. Therefore, the resistance of each pathway was gained using the formula

R_{m} = R_{n} = 2 R_{a 1}

(1-6)

R_{p} = 2 R_{a 1} + R_{a 2}

(1-7)

The total resistance (R) could be evaluated as

R = (2 R_{a 1}^{2} + R_{a 1} * R_{a 2}) / (3 R_{a 1} + R_{a 2})

(1-8)

The R_a1 and R_a2 increased remarkably when a strain was applied (Figure 4(b)). When a strain was further applied, the permanent deformation of many conductive network on the GCPPPF surface because of severe irretrievable effects on the PET/PU molecular structure endowed the larger contact resistance R_a1 and R_a2 to the sensor. Thus, it caused the increase of the total resistance (R). These presented the resistance variation obtained from the GCPPPF. Thus, this resistance model illustrated a reasonable demonstration for the working strain mechanism of the sensor.

Table 1 presents the critical property parameters of different sensors demonstrated previously. The as-prepared strain sensor exhibited comparatively a superb sensing performance superior to that of reported strain sensors, implying the superiority of GCPPPFs as the wearable sensor.

Table 1.

Comparison of the gauge factor and strain range under various strain sensors.

Material	Gauge factor	Strain range (%)	Ref
Graphene/polyester	34	0–20	³³
Graphene/polyester	5	20–50	³³
Graphene/polyester fabric	26	0–14	¹²
Graphene/CNTs/TPU	35.78	0–30	¹⁶
RGO/nylon/PU	12.1	10–18	³⁴
GCPPPF	40.25	0–50	This work
	85.72	50–100
	182.21	150–230
	265.48	230–270

Wearable application as strain sensors

To demonstrated the practical application of the sensor, the as-prepared sensor was expected to monitor precisely wide range physiological motions (Figure 5). The sensor was affixed onto the wrist to investigate the bending-relaxing movements (Figure 6(a)). The ΔR/R₀ value revealed a periodic variation through bending-unbending process. Notably, the resistance signal showed an apparent deviation under the primary cycles, but it kept stable after implementing some stretching-relaxing movements. Meanwhile, the appearance of the residual resistance was produced by the permanent deformation of the sensitive materials on the PPPF surface. Likely, the sensor was affixed onto the finger to monitor the joint movement at various bending angles (Figures 6(b)–(d)). The relative change in resistance increased obviously with the increase of the finger bending deformation, proving its stability and making a precise identification based on the different bending degrees. Meanwhile, it was affixed onto the elbow to conduct its bending motion (Figure 6(e)). The sensor provided superb resistance signal response without distinct deviation. The knee bending motion was further investigated because of the complex deformation of human movements (Figure 6(f)). The corresponding resistance signals exhibited excellent stability, suggesting that the sensor was capable of recognizing the knee joint movement. Except for the monitor of robust joint movements, it was qualified for performing tiny body motions. The sensor was mounted on the cheek to detect resistance signals (Figure 6(g)). The corresponding resistance signal remained consistent and stable, implying its good reliability. Similarly, the sensor detected tiny body movements related to the forehead via frowning-relaxing tests (Figure 6(h)). The resistance signal presented remarkable repeatability. This indicated that the sensor had great sensitivity. In addition, the moisture permeability of PET/PU fabric before and after modification was 5837 and 5634 g/(m²·24 h) respectively. Likely, the air permeability of PET/PU fabric before and after modification was 517 and 505 (mm·s⁻¹). This illustrated that the sensor had great comfort. Therefore, these results demonstrated that the fabricated sensor reveals a potential candidate for the monitor of real-time human movements as flexible electronic devices.

Figure 5.

Schematic illustration of the as-prepared sensor acts as the body joint detector.

Figure 6.

Application of GCPPPF strain sensor to detecting (a) the wrist bending, (b–d) the finger bending, (e) the elbow bending, (f) the keen bending, (g) cheek and (h) forehead.

Conclusion

A wearable strain sensor was developed via a self-assembly intercalation technique. Due to the facile layered generating structure of the conductive fabric and the synergy effect of conductive fillers, the sensor presented a superb strain range of up to 290%, excellent sensitivity, long-term electrothermal stability, along with remarkable durability as the wearable sensor. As expected, the as-prepared sensor with superior layered generating structure was used to detect precisely wide range physiological motions. Importantly, the sensor presented remarkable heating performance. Therefore, the fabricated sensor provided a superb perspective for further promising prospect in flexible electronic devices.

Supplemental Material

Supplemental Material - Large-scale assembly of highly stretchable and conductive polydopamine-generated poly (ethylene terephthalate)/ polyurethane fabric through the self-assembly intercalation strategy for superior sensing

Supplemental Material for Large-scale assembly of highly stretchable and conductive polydopamine-generated poly (ethylene terephthalate)/ polyurethane fabric through the self-assembly intercalation strategy for superior sensing by Shuqiang Zhao, Peixiao Zheng, Honglian Cong and Ailan Wan in Journal of Industrial Textiles

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Science Foundation of China (11972172), the Fundamental Research Funds for the Central Universities (JUSRP22026).

ORCID iDs

Peixiao Zheng

Honglian Cong

Supplemental Material

Supplemental material for this article is available online.

References

Wang

Tian

, et al. Customizable textile sensors based on helical core-spun yarns for seamless smart garments. Langmuir 2021; 37: 3122–3129.

Guo

Zhong

Fang

, et al. A wearable transient pressure sensor made with mxene nanosheets for sensitive broad-range human-machine interfacing. Nano Lett 2019; 19: 1143–1150.

Duan

Jiang

Wang

, et al. Inspiration from daily goods: a low-cost, facilely fabricated, and environment-friendly strain sensor based on common carbon ink and elastic core-spun yarn. ACS Sustain Chem Eng 2019; 7: 17474–17481.

Wang

Xiao

, et al. Flexible TPU strain sensors with tunable sensitivity and stretchability by coupling AgNWs with rGO. J Mater Chem C 2020; 8: 4040–4048.

Lee

Park

Cho

, et al. Flexible ferroelectric sensors with ultrahigh pressure sensitivity and linear response over exceptionally broad pressure range. ACS Nano 2018; 12: 4045–4054.

Wang

Xiang

Zhu

, et al. Multistimulus responsive actuator with GO and carbon nanotube/PDMS bilayer structure for flexible and smart devices. ACS Appl Mater Inter 2018; 10: 27215–27223.

Min

S-H

Lee

G-Y

Ahn

S-H

. Direct printing of highly sensitive, stretchable, and durable strain sensor based on silver nanoparticles/multi-walled carbon nanotubes composites. Compos B-Eng 2019; 161: 395–401.

Wang

Zhang

, et al. High-sensitivity wearable and flexible humidity sensor based on graphene oxide/non-woven fabric for respiration onitoring. Langmuir 2020; 36: 9443–9448.

Jia

Yue

Wang

, et al. Multifunctional stretchable strain sensor based on polydopamine/reduced graphene oxide/electrospun thermoplastic polyurethane fibrous mats for human motion detection and environment monitoring. Compos B-Eng 2020; 183: 107696.

10.

Gao

Huang

, et al. Electrically conductive and fluorine free superhydrophobic strain sensors based on SiO2/graphene-decorated electrospun nanofibers for human motion monitoring. Chem Eng J 2019; 373: 298–306.

11.

Wang

Hao

Huang

, et al. Flexible electrically resistive-type strain sensors based on reduced graphene oxide-decorated electrospun polymer fibrous mats for human motion monitoring. Carbon 2018; 126: 360–371.

12.

Huang

Yang

, et al. Phase-separation-induced PVDF/graphene coating on fabrics toward flexible piezoelectric sensors. ACS Appl Mater Inter 2018; 10: 30732–30740.

13.

Yang

Pang

Han

X-L

, et al. Graphene textile strain sensor with negative resistance variation for human motion detection. ACS Nano 2018; 12: 9134–9141.

14.

Wang

Jiang

, et al. A bi-sheath fiber sensor for giant tensile and torsional displacements. Adv Funct Mater 2017; 27: 1702134.

15.

Shi

Cheng

, et al. Graphene reinforced carbon nanotube networks for wearable strain sensors. Adv Funct Mater 2016; 26: 2078–2084.

16.

Liu

Gao

Huang

, et al. Electrically conductive strain sensing polyurethane nanocomposites with synergistic carbon nanotubes and graphene bifillers. Nanoscale 2016; 8: 12977–12989.

17.

Zheng

Dai

, et al. A highly stretchable and stable strain sensor based on hybrid carbon nanofillers/polydimethylsiloxane conductive composites for large human motions monitoring. Compos Sci Technol 2018; 156: 276–286.

18.

Kim

S J

Song

, et al. High durability and waterproofing rGO/SWCNT-fabric-based multifunctional sensors for human-motion detection. ACS Appl Mater Inter 2018; 10: 3921–3928.

19.

Shi

Dai

, et al. Graphene welded carbon nanotube crossbars for biaxial strain sensors. Carbon 2017; 123: 786–793.

20.

Huang

Her

S-C

Yang

, et al. Synthesis and characterization of multi-walled carbon nanotube/graphene nanoplatelet hybrid film for flexible strain sensors. Nanomaterials 2018; 8: 786.

21.

Cheng

, et al. Hydrothermal growing of cluster-like ZnO nanoparticles without crystal seeding on PET films via dopamine anchor. Appl Surf Sci 2019; 467: 534–542.

22.

Yan

Xiang

, et al. Polydopamine nanotubes: bio-inspired synthesis, formaldehyde sensing properties and thermodynamic investigation. J Mater Chem A 2016; 4: 3487–3493.

23.

Jia

Sheng

, et al. Adhesive polydopamine coated avermectin microcapsules for prolonging foliar pesticide retention. ACS Appl Mater Inter 2014; 6: 19552–19558.

24.

Liu

. Polydopamine and its derivative materials: synthesis and promising applications in energy, environmental, and biomedical fields. Chem Rev 2014; 114: 5057–5115.

25.

Shin

M K

Lee

Kim

S H

, et al. Synergistic toughening of composite fibres by self-alignment of reduced graphene oxide and carbon nanotubes. Nat Comm 2012; 3: 650.

26.

Ding

, et al. Molecular-engineered hybrid carbon nanofillers for thermoplastic polyurethane nanocomposites with high mechanical strength and toughness. Compos B 2019; 177: 107381.

27.

Zhao

Bai

. Highly sensitive piezo-resistive graphite nanoplatelet-carbon nanotube hybrids/polydimethylsilicone composites with improved conductive network construction. ACS Appl Mater Inter 2015; 7: 9652–9659.

28.

Yoo

Mahapatra

Cho

. High-speed actuation and mechanical properties of graphene-incorporated shape memory polyurethane nanofibers. J Phys Chem C 2014; 118: 10408–10415.

29.

Zheng

Huang

, et al. Multifunctional and highly sensitive piezoresistive sensing textile based on a hierarchical architecture. Compos Sci Technol 2020; 197: 108255.

30.

Luo

Gao

Luo

, et al. Superhydrophobic and breathable smart MXene-based textile for multifunctional wearable sensing electronics. Chem Eng J 2021; 406: 126898.

31.

Shi

Liu

, et al. Wearable superhydrophobic PPy/MXene pressure sensor based on cotton fabric with superior sensitivity for human detection and information transmission. Colloid Surf A 2022; 642: 128676.

32.

Barman

Tirkey

Batra

, et al. The role of nanotechnology based wearable electronic textiles in biomedical and healthcare applications. Mater Today Commun 2022; 32: 104055.

33.

Reddy

Gandla

Gupta

. Highly sensitive, rugged, and wearable fabric strain sensor based on graphene clad polyester knitted elastic band for human motion monitoring. Adv Mater Inter 2019; 6: 1900409.

34.

Cai

Yang

, et al. Flexible and wearable strain sensing fabrics. Chem Eng J 2017; 325: 396–403.

Supplementary Material

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