Smartphone-Based VOC Sensor Using Colorimetric Polydiacetylenes

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A Smartphone-Based VOC Sensor Using Colorimetric Polydiacetylenes Dong-Hoon Park, Jung-Moo Heo, Woomin Jeong, Young Hyuk Yoo, Bum Jun Park, and Jong-Man Kim ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.7b18121 • Publication Date (Web): 17 Jan 2018 Downloaded from http://pubs.acs.org on January 17, 2018

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A Smartphone-Based VOC Sensor Using Colorimetric Polydiacetylenes Dong-Hoon Park§1, Jung-Moo Heo§1, Woomin Jeong1, Young Hyuk Yoo2, Bum Jun Park3*, and JongMan Kim1,4* 1

Department of Chemical Engineering, Hanyang University, Seoul 04763, Korea

2

Department of Computer Software, Kwangwoon University, Seoul 01897, Korea

3

Department of Chemical Engineering, Kyung Hee University, Yongin 17104, Korea

4

Institute of Nano Science and Technology, Hanyang University, Seoul 04763, Korea

KEYWORDS: polydiacetylene, conjugated polymer, VOC sensor, solvatochromism, smartphone-based detection ABSTRACT Owing to a unique colorimetric (typically blue-to-red) feature upon environmental stimulation, polydiacetylene (PDAs) have been actively employed in chemosensor systems. We developed a highly accurate and simple volatile organic compound (VOC) sensor system that can be operated using a conventional smartphone. The procedure begins with forming an array of four different PDAs on conventional paper using inkjet printing of four corresponding diacetylenes (DAs) followed by photopolymerization. A database of color changes (i.e., Red and Hue values) is then constructed based on different solvatochromic responses of the four PDAs to eleven organic solvents. Exposure of the PDA array to an unknown solvent promotes color changes, which are imaged using a smartphone camera and analyzed using the app. A comparison of the color changes to the database promoted by the eleven solvents enables the smartphone app to identify the unknown solvent with 100% accuracy. Additionally, it was demonstrated that the PDA array sensor was sufficiently sensitive to accurately detect the eleven VOC gases. ACS Paragon Plus Environment

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INTRODUCTION Efficient and accurate methods for detection of volatile organic compounds (VOCs) are an important goal.1 Solvatochromism-based detection of VOCs takes advantage of color changes of materials (e.g., molecular dyes, π-conjugated polymers, etc.) in response to solubilities and polarities of solvents.2-14 Although a variety of solvatochromic based sensor technologies have been developed to date, the majority of them requires complicated fabrication procedures as well as additional equipment for color detection. These two limitations need to be overcome in order to create economic and practical sensors for detection of VOCs. As the number of worldwide smartphone users has increased dramatically, technological features as well as the data processing power of these devises have also grown. In addition, smartphone application software (“apps”) has been developed at an increasing rate using web-based app-making tools that can be utilized to create tailored mobile applications by people that do not have prior knowledge of computer programming.15-20 In the context of new strategies to design VOC detection systems, we envisioned that smartphones could replace heavy and expensive instrumentation by serving as a high-performance built-in digital camera and a mobile app for image analysis. Polydiacetylenes (PDAs) are intriguing π-conjugated supramolecules that possess unique colorimetric properties.21-40 In general, diacetylene monomers (DAs) form highly assembled aggregates when present on diverse substrates. Subsequent UV-irradiation of the aggregates leads to photopolymerization of laterally stacked diacetylene groups to form an extended π-conjugated main chain backbone. When PDAs, which intrinsically absorb visible light and often have a blue color, are exposed to various chemical and/or physical stimuli, they undergo blue-to-red color transitions. As a result, PDAs serve as efficient colorimetric sensors.

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One of the most important features of PDAs is that their DA building blocks can be chemically modified and locally functionalized. Consequently, it is possible to generate PDAs that have readily tunable sensitivities to stimuli that promote color changes and controllable solubilities in solvents. In addition, owing to strong intermolecular interactions that exist between the DA molecules in aggregates, fabrication of PDA films on various substrates is extremely simple, involving only two steps including deposition of a solution of the DA on a substrate and UV-irradiation to promote polymerization. Moreover, it was recently demonstrated that PDAs can be coated on paper by using conventional inkjet printing.29 Adaptation of inkjet printing to PDAs is advantageous because it can be used to generate flexible, inexpensive and lightweight PDA-based paper sensor systems possessing tailored designs or patterns. PDAs have been observed to undergo color changes when treated with various organic solvents.30-35 However, determining the identity of a solvent based on the color change of a single PDA sensor is challenging. In the study described below, we devised a new “combinatorial” strategy to simplify and improve the flexibility and accuracy of PDAs for sensing VOCs in both liquid and vapor phases by integrating the PDA-based hydrochromic sensors with a conventional smartphone system. The approach uses a library of PDA sensors, which display different colorimetric responses to different solvents. The PDAs are prepared by polymerization of an array of DAs (Scheme 1), each bearing an appropriate functional group and alkyl chain length that give the respective PDA a specific colorimetric response to solvents. Upon exposure of the sensor array to a solvent, color changes of the four PDAs take place simultaneously. Finally, a smartphone camera and smartphone “app” are then used to identify the solvent. Notably, the criteria for DA monomers selection is that the monomers should be inkjetprintable on conventional paper and the polymerized PDA regions should undergo distintive color changes upon solvent exposure.

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Scheme 1. Chemical structures of DA monomers for the smart VOC sensor system.

EXPERIMENTAL SECTION Materials and Instruments. 10,12-Pentacosadiynoic acid (PCDA) was obtained from GFS Chemicals (Powell, OH, USA). 1-(3-Aminopropyl)imidazole, bromoethanol, iodomethane, 4vinylaniline were purchased from Sigma Aldrich (Korea). Amino functional silicone (DMS-A11, M.W. 850-900) was purchased from Gelest (Morrisville, PA, USA). All chemicals were used as received. The N-hydroxysuccinic ester form of PCDA, 2,5-dioxopyrrolidin-1-yl pentacosa-10,12-diynoate (PCDANHS) was synthesized via the previously reported method.27 1H NMR spectra were recorded on a Varian UnityInova (300 MHz) spectrometer. Synthesis of [3-(2-hydroxyethyl)-1-(3-(pentacosa-10, 12-diynamido)propyl)-1H-imidazol-3ium] (DA1). The DA1 monomer was synthesized via the literature procedure (Scheme S1).40 A solution mixture of 0.40 g of [N-(3-(1H-imidazol-1-yl)propyl)pentacosa-10,12-diynamide] and 0.23 g of 2bromoethanol dissolved in 20 mL acetonitrile was vigorously stirred under reflux overnight. The solution was aged at room temperature overnight and concentrated in vacuo. The residue was then ACS Paragon Plus Environment

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subjected to a silica gel column chromatography (methylene chloride/methanol, 96/4) to give the product as white solid (0.40 g, 80%). 1H NMR and 13C NMR spectra of DA1 are available in Figure S1. IR (ATR) vcm-1: 3322, 3138, 3078, 2920, 2848, 1648, 1543, 1462, 1422, 1363, 1319, 1251, 1234, 1220, 1174, 1073, 1061, 1025, 957, 866, 782, 722. Synthesis

of

[3-methyl-1-(3-(pentacosa-10,12-diynamido)propyl)-1H-imidazol-3-ium

iodide] (DA2). The DA2 monomer was synthesized via the literature procedure (Scheme S1).40 A solution of 0.4 g of [N-(3-(1H-imidazol-1-yl)propyl)pentacosa-10,12-diynamide] and 0.18 g of iodomethane in 20 mL acetonitrile was vigorously stirred under reflux overnight. The solution was aged at room temperature overnight and concentrated in vacuo. The residue was then subjected to a silica gel column chromatography (methylene chloride/methanol, 96/4) and the product was obtained as white solid (0.42 g, 81%). 1H NMR and 13C NMR spectra of DA2 are available in Figure S2. IR (ATR) vcm1: 3320, 3138, 3070, 2916, 2850, 1666, 1636, 1550, 1465, 1423, 1337, 1333, 1302, 1282, 1256, 1234, 1166, 1124, 1055, 1022, 911, 837, 762, 725. Synthesis of DA3: A solution of 10,12-pentacosadiynoic acid (0.94 g, 2.50 mmol) in dichloromethane (50 mL) was added to a solution of N-terminated oligomeric dimethyl siloxane (DMSA11, 1.09 g, 1.25 mmol), propylphosphonic anhydride (T3P, 0.88 g, 2.75 mmol) and triethylamine (TEA, 0.28 g, 2.75 mmol) in 30 mL dichloromethane (Scheme S2). The solution was stirred at room temperature overnight. The reaction solution was washed with a sufficient amount of saturated NaHCO3 aqueous solution. The organic phase solution was concentrated in vacuo. The residue was subjected to a silica gel column chromatography (ethyl acetate/hexane, 1/3) to give DA3 as yellowish liquid (2.89 g, 72%). 1H NMR (300 MHz, CDCl3, δ): 3.23 (q, J = 6.6 Hz, 4H), 2.23 (t, J = 6.9 Hz, 8H), 2.14 (t, J = 7.5 Hz, 4H), 1.65-1.45 (m, 16H), 1.42-1.20 (m, 52H), 0.87 (t, J = 6.6 Hz, 3H), 0.55-0.50 (m, 4H), 0.13-0.01 (m, 60H). 13C NMR (75 MHz, CDCl3, δ) 178.4, 77.5, 77.3, 65.3, 65.2, 42.3, 36.8, 34.0, 31.9, 29.6, 29.5, 29.4, 29.3, 29.2, 29.1, 29.0, 28.9, 28.87, 28.84, 28.81, 28.7, 28.3, 28.2, 25.7, 24.7, 23.5, 22.6, 19.1, 15.3, 14.1, 1.1, 1.0, 0.1. 1H NMR and 13C NMR spectra of DA3 are available in Figure S3. IR (ATR) vcm-1: 2960, 2919, 2847, 1692, 1644, 1555, 1468, 1443, 1419, 1360, 1258, 1079, 1019, 930, 863. HRMS (ESI, ACS Paragon Plus Environment

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m/z): calcd. for C78H162N2O12Si11 [M+Na]+ 1649.9487, found 1649.9180. calcd. for C80H168N2O13Si12 [M+Na]+ 1723.9675, found 1723.9241. Synthesis of [N-(4-vinylphenyl)pentacosa-10,12-diynamide] (DA4): A solution of 10,12pentacosadiynoic acid (1.87 g, 5.00 mmol) in 50 mL dichloromethane was added to a solution of 4vinylaniline (0.63 g, 5.25 mmol), propylphosphonic anhydride (T3P, 2.07 g, 6.5 mmol) and triethylamine (TEA, 0.61 g, 6 mmol) in 30 mL dichloromethane (Scheme S2). The solution was stirred overnight at room temperature. The reaction solution was washed with saturated NaHCO3 aqueous solution. The organic phase solution was concentrated in vacuo and the resulting solid was washed with isopropanol, diethyl ether, hexane three times to give DA4 as a white powder (1.99 g, 84%). 1H NMR (300 MHz, CDCl3, δ): 7.50 (d, J = 8.1 Hz, 2H), 7.37 (d, J = 8.7 Hz, 2H), 7.22 (s, 1H), 6.68 (dd, J = 11.1 Hz, 6.6 Hz, 1H), 5.65 (d, J = 17.7 Hz, 1H), 5.17 (d, J = 10.5 Hz, 1H), 2.34(t, J = 7.8 Hz, 2H), 2.24 (t, J = 7.2 Hz, 4H), 1.72 (quint, J = 7.2 Hz, 2H), 1.51 (quint, J = 7.2 Hz, 4H), 1.42-1.25 (m, 26H), 0.88 (t, J = 6.6 Hz, 3H).

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C NMR (75 MHz, CDCl3, δ) 171.5, 137.6, 136.1, 133.5, 126.7, 119.7, 112.8, 77.6, 65.3,

65.2, 37.7, 31.9, 29.6, 29.4, 29.3, 29.1, 29.0, 28.8, 28.7, 28.3, 28.2, 25.5, 22.6, 19.2, 19.1, 14.1. 1H NMR and

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C NMR spectra of DA4 are available in Figure S4. IR (ATR) vcm-1: 3282, 2920, 2848, 1660,

1629, 1589, 1530, 1460, 1423, 1401, 1381, 1321, 1302, 1254, 1209, 1181, 1116, 1095, 1050, 1028, 994, 964, 940, 907, 856, 837. HRMS (ESI, m/z): calcd. for C33H49NO [M+Na]+ 498.3712, found 498.3712. Fabrication of PDAs Array: Black ink was removed from four cartridges (HP 703) of a commercial inkjet printer (HP Deskjet Ink Advantage K209g). After washing with sufficient amounts of ethanol and water, the cartridges were dried with nitrogen purging. The aqueous DA1 and DA2 solutions with 100 mM concentration were diluted by adding 30% volume of ethanol. The DA3 and DA4 were dissolved in tetrahydrofuran and the concentration of the solutions were 80 mM and 40 mM, respectively. The DA solutions were loaded into the washed cartridges, separately. The square array composed of four circular spots with a diameter of 0.4 cm was computer-designed using Microsoft PowerPoint, and each DA solution was inkjet-printed on a conventional Kent paper consecutively replacing the cartridges containing the four different DA solutions. After 1 min drying, the blue colored ACS Paragon Plus Environment

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PDAs array on the printed regions appeared upon exposure to UV irradiation (254 nm, 1 mW/cm2) for 1 min. Solvatochromic and Vapochromic Tests: The fabricated PDA array senor was used to detect common volatile organic solvents in both liquid and vapor phases. To demonstrate the solvatochromic responses of the PDAs, ~80 µL of a solvent was added directly onto the center region of the four arrayed spots. For testing vapochromism, 2 mL of each solvent in a glass vial was sealed by screwing the cap and incubated for ~30 min at ambient conditions. Upon opening the cap, the PDA sensor was inserted immediately into the vial, allowing exposure to the saturated solvent vapor. After closing the cap, the time evolution of the color change in the PDA array was recorded by taking photographs over 30 min. Typically, after 25 min exposure, further color changes were not observed significantly for all cases of eleven solvents. Therefore, the snapshots at 30 min were used to analyze the vapochromic responses of the PDA array. Notably, the solvatochromic and vapochromic tests were performed at room temperature (i.e., 20 – 30°C) because the temperature condition could affect the solubility of unpolymerized DA molecules and thus color changes. Solubility Measurement of DA Monomers: To measure solubility of the DA monomers in organic solvents, 1 mg of a DA monomer was repeatedly added to 1 mL of a solvent until the solution was saturated and precipitation occurred. The saturated solution was completely dried and the weight of the dried powder was measured.

RESULTS AND DISCUSSION In the first step of studies aimed at demonstrating the feasibility of this strategy, an information database was generated for color changes (i.e., RGB and hue values) of four different PDA sensors occurring upon exposure to eleven solvents in both liquid and vapor phases. Next, individual solutions of the DA precursors of the PDA sensors were inkjet-printed on separated regions on a paper substrate, and then subjected to UV-irradiation. The color changes of the four spots, induced by exposing the array to an ACS Paragon Plus Environment

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unknown solvent, were imaged by using a smartphone camera. Analysis of the image using a smartphone application was used to extract color information (i.e., RGB and hue values) from the image and identify the unknown solvent upon comparison with a preloaded color change database for eleven solvents.

Figure 1. (a) Schematic for fabricating and operating the smart sensor system. (b) Different color patterns when the PDA sensors were exposed to various solvents.

As shown schematically in Figure 1a, solutions of the four DAs (DA1-4) were separately loaded into four inkjet cartridges and then printed in an array pattern on Kent paper. The printed DA array is invisible because the DA monomers do not absorb visible light. UV irradiation (254 nm, 1 mW/cm2) led to photopolymerization of the four DAs resulting in production of the corresponding PDAs (PDA1-4) and the corresponding appearance of blue colors in the four printed regions (first image in Figure 1b). Each set of four arrayed spots was individually treated (~80 µL) with eleven common organic solvents

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in liquid phases, including tetrahydrofuran (THF), chloroform (CHCl3), dichloromethane (DCM), acetone, ethyl acetate (EA), isopropyl alcohol (IPA), ethyl alcohol (EtOH), methyl alcohol (MeOH), diethyl ether (Ether), acetonitrile (AcN) and n-hexane. In response to the respective solvents, each array generated a unique color pattern (Figure 1b), which can be distinguished by using naked eyes. For example, in spite of their similar polarities, CHCl3 and DCM promoted distinguishable color patterns on the PDAs array, with the color transitions of PDA1 and PDA4 caused by CHCl3 being more distinguishable than those promoted by DCM. Likewise, a noticeable difference existed in the color patterns produced on the PDA array by three different alcohols (IPA, EtOH and MeOH). Note that the similar colorimetric responses were found upon exposure of saturated vapor phase solvents to the PDA array sensor (Figure S5).

Figure 2. UV-vis absorbance spectra for solvatochromic responses of (a) PDA1, (b) PDA2, (c) PDA3 and (d) PDA4. ACS Paragon Plus Environment

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The solvatochromic responses of the four PDAs were also evaluated using visible absorption spectroscopy (Figure 2). Exposure of the blue colored PDAs to organic solvents in liquid phases (e.g., THF, CHCl3, DCM, alcohols) causes shifts to take place in their absorption wavelength maxima from initial values of ~638 nm to ~543 nm (Figures 2a-2d), associated with color changes from blue to red (Figure 1b). When the vapor phase solvents were exposed to the four PDAs, the vapochromic responses led to the similar absorbance spectra, as seen in Figure S6. We previously proposed that the solventinduced changes in the absorption maxima are a consequence of local stress on the backbone structure and partial deformation of the π−conjugated backbone in the PDAs caused by dissolution of unpolymerized monomers present in the polymer matrix film.32 To demonstrate this mechanism operating in the current system, the ratio of absorbance intensities at ~638 nm (blue phase) and ~543 nm (red phase) for the PDA4 was determined as a function of the solvent (Figure 3a). The absorbance ratios (Ired/Iblue) for responses to THF, CHCl3 and DCM are relatively high compared to those for other solvents. The solubilities of DA4 monomer in the organic solvents also display a similar trend (Figure 3b). Specifically, DA4 is highly soluble in THF, CHCl3 and DCM, only moderately soluble in acetone and EA, and nearly insoluble in IPA, MeOH, EtOH, Ether and hexane. In short, the solvatochromic responses of PDA4 are greater for solvents in which the corresponding monomer DA4 is highly soluble, but much lower for solvents in which the monomer is barely soluble.

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Figure 3. (a) Absorbance ratio and (b) solubility of the PDA4 sensor for various solvents. The inset is the magnified histogram for the indicated region.

Although the PDA sensor array enables visual distinction between the eleven solvents, the intensities of the colorimetric transitions are small, thus, making it difficult to use naked eyes for the determination. In addition, as the number of solvents increases, the identification process would become exceptionally challenging. Thus, a simple, convenient and automatic mobile platform based protocol for this purpose was explored in the final phase of this investigation. To quantify the solvent promoted changes occurring in the PDA arrays, the values of red color (R value) were extracted using photoshop software or a smartphone app. The higher R values correspond to deeper red colors, indicating that the PDA is more strongly responsive to a solvent. The R values corresponding to the solvatochromic and vapochromic responses of the PDA for multiple tests (≥ 10) were tabulated in Table 1a and Table S1a, ACS Paragon Plus Environment

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respectively. To minimize image process errors, the hue (H) value, a color appearance parameter, was also

employed

(

(Table

1b

and

Table

S1b).

Hue,

is

calculated

by the

RGB

values,

)

H = atan 3 (G − B ) /( 2 R − G − B ) . The database of R and H values for the solvents was uploaded to a VOC sensor smartphone app that was made using an Android Studio app. The beginning screen of the app is composed of a camera button and four circles (Figure 4a), which are guidelines for positioning the four components of the PDA array. After the sensor array is exposed to an unknown solvent, the PDA regions are aligned with the four circles on the smartphone screen (Figure 4b) and a snapshot is taken by pressing the camera button. The smartphone app then extracts the R and H values of the respective circle areas and carries out an identification process by calculating and comparing the R and H values of the PDA array to those in the preloaded database (Figure 4c) to give the identity of the unknown solvent (Figure 4d). To reduce image analysis errors that can arise from varying environmental conditions (e.g., weather and ambient lighting) and the performance of a built-in camera, the R and H values were normalized by using calibration factors corresponding to RGB values obtained from the center spot with a white background among the four PDA regions, as indicated by the dotted circle in Figure 4b. For instance, when the RGB values of the calibration spot with the white background were extracted as (215, 211, 208), the calibration factors were calculated to be (−25, −21, −18), based on the standard RGB values of (190, 190, 190), as seen at the bottom in Figure 4c. Using the obtained calibration factors, the R and H values of the four PDA regions were normalized and appeared at the top in Figure 4c. Then, the normalized R and H values were compared to the preloaded database and the matching result appeared on the smartphone screen, as seen in Figure 4d. Note that the values in Table 1 and Table S1 were normalized using the identical calibration process. By utilizing this sensing protocol, it is possible to identify the eleven solvents with 100% accuracy in both liquid and vapor phases (see Move S1).

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Table 1. Database of the normalized R (a) and H (b) values for solvatochromic responses of PDAs.

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Figure 4. Smartphone-based VOC sensing procedure. Each panel indicates the consecutive smartphone screen shot to show (a) start-up screen, (b) image capture, (c) analysis process, and (d) result screen.

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CONCLUSIONS In the effort described above we developed a highly accurate and simple VOC sensor system that can be operated using a conventional smartphone. The procedure begins with forming an array of four different PDAs on conventional paper using inkjet printing of four corresponding DAs followed by photopolymzerization. A database of color changes (i.e., R and H values) is then constructed based on different solvatochromic and vapochromic responses of the four PDAs to eleven organic solvents. Exposure of the PDA array to an unknown solvent promotes color changes, which are imaged using a smartphone camera and analyzed using the app. A comparison of the color changes to the database promoted by the eleven solvents enables the smartphone app to identify the unknown solvent. It is important to note that the developed VOC sensor strategy can be extended to creating systems for detecting numerous other VOCs, their mixtures with different concentrations, gases and ligand-receptor interactions using continuously and accumulatively updated databases derived from newly synthesized DA molecules and PDAs. Furthermore, integration of the PDA-based sensing protocol with a conventional smartphone system can offer extremely convenient and simple methodology for various VOC sensing applications.

ASSOCIATED CONTENT

Supporting Information Additional schemes for synthesizing the DA monomers (Schemes S1 and S2), NMR spectra of the monomers (Figures S1, S2, S3 and S4), and a movie for smartphone-based VOC sensing (Movie S1). Vapochromic responses of PDAs sensor are also provided (Figures S5, S6 and Table S1).

AUTHOR INFORMATION ACS Paragon Plus Environment

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Corresponding Author *E-mail: [email protected] (J.-M. Kim), [email protected] (B. J. Park)

Author Contributions §

These authors contributed equally.

Notes The authors declare no competing financial interest.

ACKNOWLEDGMENTS This investigation was supported financially by the National Research Foundation of Korea (NRF) grant funded by a Korea government (MSIP) (NRF-2017R1A2A1A05000752) and the Engineering Research Centre of Excellence Program of MSIP/NRF (NRF-2014R1A5A1009799).

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