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Simultaneously Detecting Subtle and Intensive Human Motions Based on Ag Nanoparticles Bridged Graphene Strain Sensor Zhen Yang, Dan-Yang Wang, Yu Pang, Yu-xing Li, Qian Wang, Tian-yu Zhang, Jia-bin Wang, Xiao Liu, Yi-Yan Yang, Jin-ming Jian, Muqiang Jian, Yingying Zhang, Yi Yang, and Tian-Ling Ren ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.7b16284 • Publication Date (Web): 27 Dec 2017 Downloaded from http://pubs.acs.org on December 28, 2017

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ACS Applied Materials & Interfaces

Simultaneously Detecting Subtle and Intensive Human Motions Based on Ag Nanoparticles Bridged Graphene Strain Sensor †

†

†‡

Zhen Yang, ‡ Dan-Yang Wang, ‡ Yu Pang, Yu-Xing Li,

†‡

Qian Wang,

†‡

Tian-Yu Zhang,

†‡

Jia-Bin Wang,†‡ Xiao Liu,†‡ Yi-Yan Yang,†‡ Jin-Ming Jian,†‡ Mu-Qiang Jian,§ Ying-Ying Zhang,§ Yi Yang *†‡ and Tian-Ling Ren *†‡ †

Institute of Microelectronics, Tsinghua University, Beijing 100084, China

‡

Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua

University, Beijing 100084, China §

Department of Chemistry and Center for Nano and Micro Mechanics (CNMM), Tsinghua

University, Beijing 100084, China

KEYWORDS: strain sensor, Ag nanoparticles, graphene, bridge, human motions

ABSTRACT: There is a growing demand for flexible electronic devices. In particular, strain sensors with high performance have attracted more and more attentions due to its can be attached

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on clothing or on the human skin for applications in the real-time monitoring of human activities. However, monitoring human-body motions that include both subtle and intensive motions, and many strain sensors can’t meet the diverse demands simultaneously. In this work, Ag nanoparticles (NPs) bridged graphene strain sensor is developed for simultaneously detecting subtle and intensive human motions. Ag NPs serve as many bridges to connect the self-overlapping graphene sheets which endows the strain sensor with many excellent performances. The high sensitivity with the large gauge factor (GF) of 475, and strain range over 14.5%, high durability of the sensor has been achieved. Besides, the excellent consistency and repeatability of the fabrication process is verified. Furthermore, the model for explaining the working mechanism of the strain sensor is proposed. Most importantly, the designed wearable strain sensor can be applied in human motions detecting including large-scale motions and small-scale motions.

INTRODUCTION In the past few years, flexible electronics has gradually become a hot research topic. Human-friendly electronic devices have attracted wide attentions around the world, including flexible sensors,1-4 integrated circuits,5,6 flexible display,7,8 and flexible memory.9,10 Among them, flexible strain sensors have been receive the growing attentions for the wide applications in wearable devices.11-16 Wearable strain sensors can be integrated with clothes and electronics in daily life, such as wrist band and watch, to detect human motions. In addition, wearable strain sensors can be also applied in medical-sensing such as rehabilitation assistance after orthopedic surgery.


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Nowadays, researches on nanomaterials promote the development of novel strain sensors. The strain sensors can be developed with carbon nanotube (CNT),17 ZnO nanowires,18 Ag NPs,19 and other fascinating nanomaterials. These nanomaterials have some disadvantages such as high resistance and poor stretch ability. Graphene,20,21 a typical two-dimensional hexagonal honeycomb material, has been applied in high-sensitivity strain sensors due to its extraordinary properties, such as the superior mechanical flexibility, high carrier mobility, good transparency, and high restorability.22,23 Therefore, many works have been done to develop strain sensors with graphene. He Tian et al. fabricated a strain sensor with a low GF of 9.49 by directly reducing graphene oxide film with a light-scribe DVD burner.24 Yi Wang et al. developed a buckling approach to fabricate the graphene ripples strain sensor which exhibited low sensitivity with a GF of 0.55 and large strain deformation.25 Jing Zhao et al. fabricated a new type of strain sensor based on quasi-continuous nanographene films, with a high performance of GF (up to 546), while the strain range was only 1.6%.26 In order to simultaneously achieve a wide measurement range and high sensitivity, a novel flexible Ag NPs bridged graphene strain sensor was fabricated by drop-casting homogenous mixture of Ag NPs and graphene oxide (GO) on polydimethylsiloxane (PDMS) substrate, followed by the laser reduction. After embedding the copper foils as the electrodes, the Ag NPs bridged graphene layer was encapsulated with another PDMS film. This PDMS film provided the environmental protection and induced high sensitivity. Scanning electron microscopy (SEM) and Raman spectroscopy were used to characterize the strain sensor. The SEM image showed that Ag NPs were embedded inside graphene sheet and on the surface of graphene sheet. The strain sensor could be stretched up to 14.5%, which made it suitable for the broad applications. In addition, the sensor showed the high sensibility with the GF value up to 475. The consistent



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resistance response of several separately prepared sensor towards the strain was obtained, which implied the excellent durability of the sensor was found in the repeated stretching/releasing experiments with more than 500 cycles. Also, the promising feasibility of the fabricated sensor for detecting the motions of finger, wrist, leg, finger pulse and elbow were demonstrated. RESULTS AND DISCUSSION Figure 1 shows the schematic diagram of the fabrication process of Ag NPs bridged graphene strain sensor is simple, which does not require expensive equipment and special environment. As shown in Figure 1a, a PDMS film was fabricated as the substrate. Then, the homogeneous mixture of the Ag NPs and GO dispersion (Ag NPs/GO) was drop-coated on the PDMS film. After being dried at room temperature for two days, Ag NPs and GO film was formed (Figure 1b). Figure 1c presents that the GO sheets were reduced to laser-reduced graphene oxide (LRGO) film by laser scribing technique. This method is convenient and quick without expensive equipment. GO is reduced to graphene sheets only by one-step and this graphene sheets is of high quality. After that, two copper foils were pasted on the two ends of the film as the electrodes of the device by silver paste (Figure 1d). Finally, another PDMS film was covered on Ag NPs bridged graphene sheet composite as an encapsulate shell to protect it from environmental factors, such as temperature, humidity, and physical damage (Figure 1e). The photograph of the strain sensor is shown in Figure 1f. The size of Ag NPs bridged graphene strain sensor is shown in Figure S1. In order to optimize the ration of Ag NPs and GO, the Ag NPs bridged graphene strain sensor with different mixing volume ratio of Ag NPs and GO, such as 1:5, 1:10, 1:20, were also fabricated. The Ag NPs bridged graphene strain sensor with 1:10 mixing volume ration of Ag NPs and GO exhibited the highest GF under the same stretch range (see Figure S2).


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Figure 1. Schematic diagram of the fabrication process for Ag NPs bridged graphene strain sensor. a) Preparation of flexible PDMS film. b) Drop-casting of Ag NPs/GO suspension on PDMS film. c) Laser reduction of the GO sheets into LRGO. d) Fabrication of the copper foil electrodes. e) Encapsulation of the composite film with PDMS film. f) The photograph of the strain sensor. Scanning electron microscopy (SEM) and Raman spectroscopy are used to characterize the strain sensor. Figure 2a, 2b, 2c and 2d are the SEM images of the strain sensor with a magnification of 500×, 884×, 15000× and 50000×, respectively. Generally, the graphene layers show the randomly overlapping and stacked structure with numerous interlayer gaps (Figure 2a and 2b). From Figure 2c and 2d, many nanoparticles are randomly embedded within and on the stacked graphene flake. EDX elemental mapping is employed to confirm the composition of the nanoparticles, and the distributions of C, O, Si and Ag in the composite material are shown in Figure S3. This proves the existence of Ag element. The element of Si comes from PDMS which is a kind of silicone-based elastomers.

In addition, the EDX examination shows that the

composite contains 80.87 wt% C and 4.25 wt% Ag, as demonstrated in Table S1. The main diameter range of Ag NPs is from 50 nm to 100 nm measuring by the SEM scale, see Figure S4.



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Thus, a three-dimensional cross-linked structure of the Ag NPs bridged graphene system is formed. It is speculated that the Ag NPs could serve as the conductive bridges between the adjacent graphene flakes, and thus reduce the initial resistance of the strain sensor and yield the layer resistance change. Figure 2e demonstrates the Raman spectrum of the graphene sheet. The D-peak around 1350 cm-1 and the G-peak around 1585 cm-1 are typical graphene sheet characteristic peaks.27 The D-peak reveals that the presence of several structural defects, such as vacancies, stacking faults, and domain boundaries, which could endow the strain sensor with excellent performances. The G-peak and 2D-peak show the graphene sheet film has several layers.28


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Figure 2. Characterization of the Ag NPs bridged graphene strain sensor. a-b) The self-overlapping graphene sheets and stacked structure with numerous interlayer gaps. c-d) The SEM image of Ag NPs bridged graphene. e) The Raman spectrum of the graphene sheet. To evaluate the performance of the Ag NPs bridged graphene strain sensor, the graphene strain sensor without Ag NPs also be fabricated. The measurement results of electrical experiments for the Ag NPs bridged graphene strain sensor are shown in Figure 3. The calculation of GF is based on the formula GF = δR/strain, where δR =△R/R, which refers to the relative resistance change,



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and strain refers to the change of stretching length. The repeatability of the fabrication process is studied using multiple samples prepared under the same conditions. Figure 3a demonstrates the sample-to-sample variation of Ag NPs bridged graphene strain sensor. The result verifies the consistency of the different samples and great repeatability of the fabrication process. Besides, the relationship between strain and the relative resistance change is also demonstrated in Figure 3a, where R0 is the initial resistance and R is the real-time resistance when the strain sensor is stretched. The GF of the Ag NPs bridged graphene sensor is 183 under the strain range of 0-8% while the GF is 475 in the range of 8-14.5%. The strain range is up to 14.5%. From Figure S5, the GF of graphene strain sensor without Ag NPs is 89 under the strain range of 0-9% while the GF is 128 in the range of 9-14.5%. It can be verified that the presence of Ag NPs significantly improves the performance of the strain sensor. The test result of Ag NPs bridged graphene strain sensor consists of two parts; the front part has favorable linearity, and the latter part has little fluctuation. The generation and propagation of inhomogeneous microcracks among the thin films induced by graphene flakes or NPs may lead to nonlinear response of this strain sensor. When the films are formed with graphene and Ag NPs, the microcracks generation will be postponed and the microcracks propagation will be homogeneous, which leads to the high linearity of the strain sensor. In generally, the Ag NPs bridged graphene strain sensor achieves a high sensitivity and large strain range with excellent linearity. Figure 3b shows the responses of the strain sensor under different strains in the studies on the multi-cycle operations. It can be observed that relative resistance changes of the sensor are 520% under 3% strain, 900% under 5% strain, 1300% under 7% strain, and 2500% under 9% strain 3800 11% strain respectively. The inset of Figure 3b is the relative resistance changes of the sensor with 5% strain. The result indicates good linearity of this sensor. A strain sensor must be


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subjected to fatigue testing before really come up to practical applications. Figure 3c presents the dynamic stretching/releasing cycle response of the strain sensor towards the strain within 4% at a rate of 10mm per second. In spite of the response loss at the beginning of the cycle, more than 70% of the original sensor response still remains after 500 stretching-releasing cycles, which confirms the good mechanical durability and stability of the designed strain sensor. When it becomes stable, the sensor exhibits high stability during the repeated cycle testing, as shown in the magnified image (Figure 3d). To further explain the good stability of the Ag NPs bridged graphene strain sensor, the comparison of the morphology before and after the fatigue testing is demonstrated in Figure S6. From these experimental results, we can confirm that our strain sensor has good mechanical durability and stability.



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Figure 3. The electrical experimental results of the Ag NPs bridged graphene strain sensor. a) The sample-to-sample variation of Ag NPs bridged graphene strain sensor. The picture presents the relationship between the strain and the relative resistance change. The response line is favorable linear and the GF is 183 under 8% strain and 475 under 14.5% strain. b) Multi-cycle operation of the strain sensor under 3% strain, 5% strain, 7% strain, 9% strain and 11% strain, respectively. The inset is 5% strain. c) 500 cycles of repeated stretching/releasing test with a maximum strain of 4%, at a rate of 10 mm per second. d) The magnified cycles of stretching test results. In Table 1, the key parameters of several pervious strain sensors are listed. In this work, the strain sensor we fabricated has a larger strain range and a high GF. As can be seen from the table, the strain sensor achieves a good balance between high sensitivity and large strain. Table 1. The comparison of performance parameters for different strain sensors.

Materials

Gauge factor

Strain range

Reference

Silver nanoparticles

2.05

20%

(21)

Graphene

150

1.5%

(18)

Zno nanowires

116

50%

(20)

Laser-scribed graphene

9.49

10%

(24)

Carbon nanotubes

0.82

280%

(19)

Nanographene by CVD

549

1.6%

(26)

RGO/Ag nanoparticles

475

14.5%

This work

The performance of the strain sensor offers a unique opportunity to simultaneously detect subtle and intensive human motions, such as the bending of finger with different degrees, and the


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bending of wrist, leg, finger pulse and elbow. As shown in Figure 4a, we measured the relative resistance change versus the bending of finger with different degrees. During the bending motion of the finger with varying degrees, the relative resistance changes significantly and the strain sensor shows quick response time. The relative resistance change is 300%, 500%, 1000%, and 2200% when the finger is bent at 30 degrees, 45 degrees, 60 degrees and 90 degrees, respectively. This result indicates that the flexible and wearable Ag NPs bridged graphene strain sensor can be integrated in a glove for human finger motion detection. The strain sensor not only can detect intensive motions, but also can detect subtle motions. We used the sensor to measure the finger pulse (Figure 4b) which demonstrated this sensor has high sensitivity. The test result presents 75 pulses per minute, in consistent with heartbeat numbers of a health person. Figure 4c shows finger pulse in 16 seconds. Figure 4d shows a single finger pulse wave. The typical characteristics of finger pulse indicates three typical peaks, which are called percussion wave (P-wave), tidal wave (T-wave) and diastolic wave (D-wave), and doctors can analyze and get much useful diagnosis information from these waves.29 Figure 4e shows that the relative resistance change of wrist bending. The strain sensor is placed on the back of the wrist and used to measure the wrist bending. The relative resistance change increase while the wrist is bent and recover while moving the wrist to the initial state. Also, the sensor demonstrates repeatable sensing performance. Therefore, the sensor can be integrated in wrist band to sensing wrist motion, which can monitor the movement of the wrist during exercising. The motion of leg can also be detected and this sensor can be applied in knee band. Figure 4f demonstrates the relative resistance change with leg bending. Figure 4g shows the elbow bending. Compared with Figure 4e, 4f, and 4g, the relative change in resistance of the sensor vary with different bending motions



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of different amplitude. Therefore, the Ag NPs bridged graphene strain senor can be applied in the real-time sensing simultaneously subtle and intensive human motions.

Figure 4. Detecting simultaneously subtle and intensive human motions using the Ag NPs bridged graphene strain sensor. a) Sensing performance of the strain sensor on the bending of finger. The relative resistance changes are various with different bending degrees. b) Finger pulse can be detected by the strain sensor, and test finger pulse in 60 seconds. Inset: photograph image of finger pulse test. c) Finger pulse detection in 16 seconds. d) Single finger pulse wave. e) The relative resistance changes in bending motion of the wrist. Inset: photograph image of wrist test in original state and bending state. f) The correspond signals of bending leg. Inset:


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photograph of leg test in original state and bending state. g) The relative resistance changes with elbow bending. Inset: photograph of elbow bending test. In order to understand the working mechanism of the Ag NPs bridged graphene strain sensor, we tracked the structure evolution of a sensor during the initial statues and subsequent loading statues. Figure 5 shows the evolution of structure during the different loading. Figure 5a, 5b and 5c are the optical images of the surface and Figure 5d, 5e and 5f are SEM images. The evolution of structure lead to the designed strain sensor in this study shows a high sensitivity and a wide strain range. Here, three theoretical hypotheses are proposed to explain the relationship between the strain and the relative resistance change. First of all, PDMS, a kind of flexible and stretchable silicone-based elastomers, is used as support materials of strain sensors, which can achieve a wide strain range. As shown in Figure 5a and 5d, the numerous gaps between the self-overlapping graphene sheets cause a considerably large initial resistance of the sensor in initial status. The incorporation of Ag NPs serves as a bridge to connect self-overlapping graphene, could convert the layered structure into a three-dimensional network one, and thus reduce the initial resistance and improve the performance of the strain sensor. Secondly, the area of self-overlapping graphene determines the relative resistance change because of the conductivity of graphene is very large. The area of self-overlapping graphene is different for different strain, which results in different relative resistance changes. The decrease of the self-overlapping graphene flakes makes the whole resistance increases when the sensor is stretched. In addition, the edge defects and fracture of the graphene film increase during the stretching process, which further enlarge the whole resistance. Thirdly, as shown in Figure 5b-f, microcracks generate in the network when the pull is applied in the strain sensor, which also leads to the increase of resistance. However, Ag NPs fills the microcracks and connects the



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broken graphene flakes, reducing the increase of the resistance and enhance the uniformly extend of microcracks, contributes to the excellent performance of a wide strain range and good linearity. The three assumptions have been used to explain the excellent performance of the Ag NPs bridged graphene strain sensor.

Figure 5. a-c) the optical images of the surface for strain sensor with different loading. d-e) the corresponding SEM images. To analyze the mechanism concretely, we set a model of randomly positioned Ag NPs bridged self-overlapping graphene film. Figure 6a shows the self-overlapping graphene flakes on original state. Due to the large overlapping area and the presence of Ag NPs, a low initial resistance is achieved. As shown in Figure 6b, the overlapping area decreases, the graphene flakes become loose and generate few microcracks under low strain range, which will increase the resistance. However, the variation of resistance is relatively small induced by the embedded Ag NPs. In the case of small strain range, the relative variation of resistance primarily depends on the decrease of the overlapping area. As demonstrated in Figure 6c, compared with low strain range, the


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graphene flakes are looser, the microcracks aggrandize and the overlapping area continues to decrease under the large strain. Under the circumstance of large strain range, the overlapping area is not the dominant factor for the relative resistance change and the Ag NPs are not large enough to fill the microcracks. Therefore, the microcracks play a decisive role in resistance changes of the sensor. These are the reasons why the strain sensors show a high GF and a wide strain range, and the model is consistent with the experiment results.

Figure 6. The relative resistance change mechanism of the Ag NPs bridged graphene strain sensor. a) The self-overlapping graphene flakes on original state. b) The self-overlapping graphene flakes and little microcracks under small strain. c) The self-overlapping graphene flakes and many microcracks under large strain.

CONCLUSIONS In conclusion, we have fabricated Ag NPs bridged graphene strain sensor with high GF and a wide strain range which can detect simultaneously subtle and intensive human motions. The Ag NPs bridged graphene strain sensor have an excellent strain range (up to 14.5%) with a high GF of 475, which is more excellent than other graphene strain sensors. The strain sensor shows a fast



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response/recovery speed and good linearity. Furthermore, the sensor exhibits good durability and long-term stability again stretch/repeated cycles. Most importantly, the Ag NPs bridged graphene strain sensor has both achieved a high GF and a wide strain range which can be used to detect various human motions. This fabrication method is very simple with a short fabrication period and a low manufacturing cost. According to the theoretical analysis, the Ag NPs bridged self-overlapping graphene flakes contributes to the superior performance of the strain sensor. The strain sensors are applicable for detecting multiple human motions such as finger and wrist bending; the signals of relative resistance change are dependent on the deformation. In addition, some subtle human motions can also be detected such as heartbeat. It is believed that the strain sensor shows significant potentials of applications in wearable electronics for the distinctive features, such as high sensitivity, large strain range, and good durability. Furthermore, the fast, stable and low-cost fabrication method will make them possible and practical to be used for commercial applications in the future. EXPERIMENTAL SECTION Preparation of the strain sensor: The GO dispersion was purchased from Nanjing XFNANO Materials Tech Co., Ltd. The average diameter of the dispersed GO sheet is larger than 500 nm and the concentration is 2 mg mL-1. The Ag NPs dispersion with a concentration of 20 mg mL-1 was purchased from Changsha Weixi New Materials Technology Co., Ltd. First of all, a PDMS film, PDMS liquids and a plasticizer in a ratio of 10:1 mixed, and this ratio could accelerate the liquid curing as well as more easily produce flat films. The PDMS mixed liquid was put on a plastic dish, and then put it into a vacuum pump for half an hour in order to remove the bubbles. To speeding up curing, we placed the plastic dish in an oven at 65°C for 12 h. Second, the Ag NPs and GO were mixed in a volume ratio of 1:10 and the mixture was stirred evenly for 2h to


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produce uniform suspension. After that, we added tetrahydrofuran (THF) to the suspension with a ratio of 1: 5 in order to increase the adhesion of solution and PDMS, and then the mixed suspension was drop-coated on the PDMS in a fume hood. At last, water would evaporate gradually and then an Ag NPs bridged graphene film would be finished. The film was placed under a laser with a wavelength of 450 nm, and the laser could be patterned to reduce GO. In this work, the film was graphically reduced to a square of 6 cm ×1.5 cm. The power of the laser is 90 mW and the spot size is almost 150 µm. Finally, the copper foil was pasted on the both edges of the film as electrode, and silver paste was coated on the junction as a connecting material. And another PDMS was covered on Ag NPs bridged graphene film. Characterization: Scanning electron microscope (Quanta FEG 450) was employed to observe the morphologies of synthesized materials. The accelerate voltage of the SEM microscope is 5000 volts. The Raman spectrum was obtained by utilizing a Lab RAM HR Evolution (JY-HR800) with a wavelength of 532 nm and power of 50 mW at room temperature. The electromechanical properties of the strain sensor were measured with a testing machine (SHIMADZU AGS-X) and digital electrometer (RIGOL DM 3068). ASSOCIATED CONTENT Supporting Information The supporting information is available free of charge on the ACS Publications website. The size of sensor, the GF of sensor with different mixing volume ration of Ag NPs and GO, the EDX mapping, SEM images of Ag NPs, the comparison of the graphene sensor and Ag NPs bridged graphene sensor, the comparison of the morphology before and after fatigue testing, the EDX composition results.



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AUTHOR INFORMATION Corresponding Author *

E-mail: [email protected], [email protected]

Notes The authors declare no competing financial interest. ACKNOWLEDGMENTS This work was supported by National Key R&D Program (2016YFA0200400), National Natural Science Foundation (61574083, 61434001), National Basic Research Program (2015CB352101), Special Fund for Agroscientific Research in the Public Interest of China (201303107), and Research Fund from Beijing Innovation Center for Future Chip. The authors are also thankful for the support of the Independent Research Program of Tsinghua University (2014Z01006) and Shenzhen Science and Technology Program (JCsYJ20150831192224146). REFERENCES (1) Mannsfeld, S. C. B.; Tee, B. C.-K.; Stoltenberg, R. M.; Chen, C. V. H.-H.; Barman, S.; Muir, B. V. O.; Sokolov, A. N.; Reese, C.; Bao, Z. Highly Sensitive Flexible Pressure Sensors with Microstructured Rubber Dielectric Layers. Nat. Mater. 2010, 9 (10), 859–864. (2) Someya, T.; Sekitani, T.; Iba, S.; Kato, Y.; Kawaguchi, H.; Sakurai, T. A Large-Area, Flexible Pressure Sensor Matrix with Organic Field-Effect Transistors for Artificial Skin Applications. Proc. Natl. Acad. Sci. U. S. A. 2004, 101 (27), 9966–9970.


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