Journal of Sensors

Journal of Sensors / 2019 / Article

Research Article | Open Access

Volume 2019 |Article ID 5786105 | https://doi.org/10.1155/2019/5786105

Fahad Usman, John Ojur Dennis, Khe Cheng Seong, Abdelaziz Yousif Ahmed, Thomas L. Ferrell, Yap Wing Fen, Amir Reza Sadrolhosseini, Olumide Bolarinwa Ayodele, Fabrice Meriaudeau, Aminu Saidu, "Enhanced Sensitivity of Surface Plasmon Resonance Biosensor Functionalized with Doped Polyaniline Composites for the Detection of Low-Concentration Acetone Vapour", Journal of Sensors, vol. 2019, Article ID 5786105, 13 pages, 2019. https://doi.org/10.1155/2019/5786105

Enhanced Sensitivity of Surface Plasmon Resonance Biosensor Functionalized with Doped Polyaniline Composites for the Detection of Low-Concentration Acetone Vapour

Academic Editor: Sachin K. Srivastava
Received05 Aug 2019
Accepted16 Oct 2019
Published20 Nov 2019

Abstract

PANI/chitosan composite and a ternary composite comprising of PANI, chitosan, and reduced graphene oxide have been successfully synthesised and characterised using FTIR and UV-VIS spectroscopy. Optical constants of the composites were extracted from the UV-VIS spectra. The extracted parameters were applied in the simulation of a surface plasmon resonance (SPR) biosensor functionalised with PANI/chitosan and ternary composites. The aim was to explore the applicability of the composite-based SPR sensor in the detection of low-concentration acetone vapour within the range of 1.8 ppm–5.0 ppm for diabetes monitoring and screening. The functionalization of the SPR sensor with the PANI/chitosan and the ternary composites shows promising application of the sensor in the detection of acetone vapour at a low concentration down to less than 0.5 ppm. The maximum sensitivity values of about 60 and 180 degree/refractive index change were observed for PANI/chitosan and ternary composite sensing layers, respectively, in comparison with the bare gold-based SPR which shows no response up to 10 ppm concentration of acetone vapour in air. In addition, the two sensing layers show good selectivity to acetone vapour compared to ethanol, methanol, and ammonia. The response in the case of ternary composite shows better linearity with a correlation coefficient of 1.0 compared to PANI/chitosan- and gold-based SPR layers with 0.9999 and 0.9997, respectively.

1. Introduction

The interaction between light waves and conduction electrons at the interface of metal and dielectric media produces quanta of longitudinal surface waves. The waves are called surface plasmons and are confined at a smaller wavelength along the surface of the metal (plasmonic material) in contact with the dielectric interface [13]. Surface plasmon resonance (SPR) happens when energy is exchanged between the light waves and surface plasmons. The incident angle of the light at which nearly complete attenuation of the reflected light occurs is called the SPR angle, and it is a function of the optical properties of the metal, dielectric medium, and any adsorbate on the metal. This dependency is exploited in SPR biosensing [3, 4]. SPR-based sensors feature high sensitivity, real-time noninvasive measurement, label-free measurement, and nonrequirement of electrodes [1, 4].

Gold is widely used as the plasmonic material in SPR biosensors due to its high SPR shift feature (allowing high sensitivity) and chemical stability [1]. However, despite these important features, detection of volatile compounds and other gases (few hundreds of Daltons) in low concentrations is difficult to achieve. This is due to their poor interaction with gold surface [5, 6]. But detection and monitoring of the molecules of such volatile compounds are required in many aspects such as the environmental monitoring of toxic gases that are released through unintended processes as well as the quality control and industrial monitoring of many chemical products [79]. In addition, some of these molecules can serve as disease biomarkers. An example is the use ammonia in monitoring kidney complications and acetone as a diabetes biomarker [1014].

Exhaled breath acetone can be used as a diabetes biomarker because of its high correlation with blood glucose (conventional diabetes biomarker) [15]. The concentration of acetone in the human body is generally very low (0.1 ppm–0.8 ppm), although it can be higher in the case of metabolism disorders, including diabetes mellitus (DM) (1.8 ppm–5.0 ppm) [1618]. Detection of such very low concentration has been achieved by chemiresistor-based sensors that mostly employ metal oxide semiconductors [19, 20]. However, the contact resistance of the sensors’ electrodes also contributes to the overall resistance of the device. This leads to unreliable detection and poor selectivity, as little information other than resistance can be obtained [21]. Furthermore, metal oxide semiconductor sensors operate at a high temperature [19, 2225] resulting to an increased energy consumption and unfavourable detection. SPR sensors are not subject to these effects.

SPR-based sensors have been successfully applied in the detection of some volatile compounds and gases like benzene, ammonia, chloroform, ethanol, methanol, ethyl benzene, 2-propanol, toluene, and acetone vapours [8, 2632]. The performance of the sensors has been improved through various design modifications which include the incorporation of nanoparticles of different morphologies [3335], bimetallic layers [2, 3639], porous gold [4043], graphene layer on gold [5, 44], conducting and insulating polymer coatings [26, 45, 46], and metal oxide coatings [47, 48]. However, SPR detection of acetone vapour has not been optimized for suitable applicability in diabetes monitoring and screening [32].

Conducting polymers, particularly, polyaniline, have been used as an active layer in gas sensors since early 1980s [49]. In contrast to metal oxide-based sensors, polyaniline-based sensors are operated at room temperature [21]. Polyaniline is also widely researched for its easy synthesis, high sensitivity even at room temperature, short response time, good mechanical properties enabling facile fabrication, high surface area to volume ratio, and high surface tension. Furthermore, chitosan has demonstrated ppm-level detection of acetone vapour based on a different means of detection [50]. Graphene-based SPR sensors are also well known at improving sensitivity and selectivity due to graphene’s unique physical, optical, and electrical properties [5153]. Additionally, adsorption of gas molecule onto the surface of an organic material (active sensing layer) can alter its structural, electrical, or optical properties. Better sensitivity and selectivity are normally expected with possible solvation effect/and potential of hydrogen bond formation. Fortunately, Hildebrand and Hansen solubility parameters of polyaniline and acetone are closer than many other similar vapours [54]. In addition, both polyaniline and chitosan can form a hydrogen bond with the CO group from acetone [54, 55]. Furthermore, graphene has been described as among the best adsorbent material for carbon-based biomolecules [56].

In this work, we have synthesised p-toluene sulfonic-doped polyaniline (PANI)/chitosan composite and a ternary composite comprising of PANI, chitosan, and reduced graphene oxide (RGO). The composites were characterised by ultra violet-visible spectroscopy (UV-VIS) and Fourier transform infrared spectroscopy (FTIR). Furthermore, the optical properties of the composites were extracted from their respective optical spectra (UV-VIS). The applicability of the PANI/chitosan and the ternary composites in SPR sensing was then investigated and compared with conventional gold-based SPR sensor using mathematical modeling and simulation. Our aim was to investigate the potential of the PANI/chitosan and the ternary composite-based SPR biosensors for utilization in the detection of low concentration of acetone vapour for diabetes monitoring and screening.

2. Materials and Methods

2.1. Materials

Aniline monomer (Aniline 99%), p-toluene sulfonic acid (PTSA), ammonium peroxodisulfate (APS) (98%), graphene oxide (GO), acetic acid, hydrazine monohydrate (>99%), and chitosan were all supplied by Avanti chemicals supply from Merck and Sigma-Aldrich. All the chemicals were analytical grade. RGO was obtained by hydrazine reduction.

2.2. Synthesis of PANI Composites and Characterisation
2.2.1. PANI/Chitosan Composites

The synthesis of PANI/chitosan composites is in accordance with some previous works [57, 58]. In a typical synthesis, 0.5 g of chitosan was dissolved in 50 ml of aqueous acetic acid (), and the solution was stirred for 24 hours at room temperature. To this mixture, about 30 ml of 0.1 M of aniline (dissolved in 0.4 M PTSA) was added and stirred for 15 min to form a homogenous solution. The resultant mixture was cooled to less than 5°C. In order to initialised the polymerisation process, 10 ml of 0.15 M solution of APS was prepared in 0.1 M PTSA and added to the above homogenous solution drop by drop with constant stirring at 0°C-5°C. After that, the reaction mixture was kept under constant stirring for 6 hours. A greenish-black precipitate was obtained. The precipitate was filtered and washed (with water and ethanol) until the filtrate becomes colourless. The final composite was dried at 60°C for 24 hours.

2.2.2. Ternary Composites

Based on the previous literatures [59, 60], a ternary composite was synthesised. In a typical synthesis, 1 g of chitosan was dissolved in 100 ml of aqueous acetic acid (), and the solution was stirred for 24 hours at room temperature. A separate homogeneous dispersion of 100 mg RGO in 45 ml of 0.4 M solution of PTSA was prepared by ultrasonication for 2 hours. The two components were mixed under continuous stirring. To the resulting mixture, about 50 ml of 0.1 M of aniline (dissolved in 0.4 M PTSA) was added and stirred for 15 minutes to form a homogenous dispersion. 0.15 M APS solution was then added to the dispersion drop by drop with constant stirring at 0°C-5°C. The reaction mixture was kept under constant stirring for an additional 6 hours. A greenish-black precipitate was obtained. It was then filtered and washed with water and ethanol until the filtrate becomes colourless. The final composite was dried at 60°C for 24 hours.

2.2.3. Characterisation

The successful synthesis of the PANI composites was confirmed by FTIR spectroscopy (PerkinElmer, Spectrum One) in the 4000–400 cm-1 range. UV-VIS spectroscopy of the composites’ thin films was also carried out in order to further confirm the synthesis and for optical constant measurements. The thickness measurement was conducted using surface roughness tester, SV-mutitoyo-3000.

2.3. Optical Constants and SPR Studies of the PANI Composites
2.3.1. Optical Constant of the PANI/Chitosan and the Ternary Composites

The optical constants of the composites were extracted from the UV-VIS spectra of the thin film of the respective composites. The thin films were deposited from the dispersion concentration of 0.015 g/ml. Deionised water was used as solvent in the case of the PANI/chitosan and the ternary composites while 1-Methyl-2-pyrrolidinone (NMP) was used in the case of PANI and PANI/RGO. The process was complemented by constant magnetic stirring for 3 hours at a 350 rpm test. Later, the resulting dispersions were spin coated using POLOS™ spin coater at 1500 rpm.

The extraction of the optical constants was based on the well-known relationship between the reflectance (), transmittance (), and absorbance () spectral data [61]. This is shown in equation (1). The optical absorption based on Beer’s law, transmittance, and absorption coefficient () of the composites were also calculated using equations (2), (3), and (4), respectively [61, 62]. where is the intensity at depth of thickness , is intensity at zero thickness, and is absorption coefficient.

However, the extinction coefficient, (imaginary part refractive index) is related to by equation where is the wavelength of the light waves (633 nm in this case).

Based on all these above equations ((1)–(5)), the real part of refractive indices, of the composites were evaluated from the Fresnel equation (equation (6))-based reflectivity measurement of the composites using equation (7) [61, 62]

Furthermore, the complex dielectric constant values of the composites were evaluated from the and values using the ff. equations [61] where and are real part and imaginary part dielectric constants, respectively.

2.3.2. SPR Studies of the Composites

The design of a surface plasmon-based sensors is guided by the knowledge of the penetration depth of a surface plasmon wave. It is defined as the distance from the interface of metal-dielectric at which the amplitude of the field becomes of the value at the interface [1]. The penetration depth in the dielectric gives us a measure of the length over which the surface plasmon is sensitive to the changes in the refractive index of the dielectric medium, while the penetration depth into metal gives us an idea of the thickness of the metal film required for the coupling of light incident from the other interface of the metal film [1]. In this study, the dielectric constant value of gold from literature and that of the composites was substituted in equations (10) and (11) in order to find the penetration depth through the gold () and the composite materials adjacent to the gold film, respectively [26]. where is the free space wavelength and and εd are the real part dielectric constant of gold and the material adjacent to the gold, respectively.

The design was further optimized using 5 different light sources, namely red light at 633 nm, yellow light at 589 nm, green light at 546 nm, violet light at 441 nm, and blue light at 436 nm (G-Line). The sketch diagram of the sensing device is shown in Figure 1.

The system is comprised of He-Ne laser light (), SF11 prism ( at 633 nm), Au (, ) [63, 64], PANI/chitosan composite or ternary composites (), and dry air environment. Using equations (5) and (7), the complex refractive indices () of PANI/chitosan and ternary composites at 633 nm were found to be and , respectively. The refractive index of dry air () at temperature and pressure was found to be 1.000263719 using the ff. equation [65, 66] where is the refractive of standard air at 633 nm, 15°C, and 101325 with 0.045% by volume of carbon dioxide (1.000272874).

To explore the response linearity of the proposed sensor, the transfer matrix method (TMM) was applied in MATLAB environment to generate SPR curves. The system was considered to be composed of layers with dielectric constants and thicknesses and , respectively, placed between SF11 prism with dielectric constant and air medium with dielectric constant . The system also assumed a fixed thickness refractive index change of 0.005 units due to the presence of analyte of certain concentration. The complex reflection coefficient () for the p-polarised incident light was therefore described using equation [3] where represents the transfer matrix: where is the wave vector perpendicular to the interface.

The angular dependence of is contained in the , and the reflectance was obtained from equation

For the SPR simulation of the detection of low concentration of acetone vapour in dry air for diabetes monitoring, the Arago–Biot mixing formula (equation (17)) was applied for the estimation of the refractive index of 0.5 ppm, 2 ppm, 4 ppm, 6 ppm, 8 ppm, and 10 ppm concentration of acetone vapour in dry air [67]. where is the -millionth fraction by volume of acetone vapour, , 2, 4, 6, 8, and 10 for 0.5 ppm, 2 ppm, 4 ppm, 6 ppm, 8 ppm, and 10 ppm of acetone, respectively. Also, . and are the refractive index of dry air and acetone vapour, respectively.

Furthermore, the detection of such low concentration of acetone vapour was simulated based on the following assumptions. The thickness of gold was considered to be constant during the detection process due to its lack of good adsorption capability for gases [6]. However, the thicknesses and the refractive indices of PANI/chitosan and ternary composites were increased by 0.0005 and 0.1 nm units, respectively. This is due to potential adsorption, solvation, and swelling effect of PANI and chitosan [26, 30, 54, 6870]. Equation (18) was applied in comparing the sensitivity of the SPR sensors based on gold, PANI/chitosan, and ternary composite [3]. The refractive index change, , of the sensing layer was considered in the case of PANI/chitosan and ternary composites because the contributions from the gas-phase atop the polymer are not anticipated to substantially influence the sensor response [26]. For gold-based SPR sensor, the refractive index change of the gas phase was considered. where is the shift in the SPR angle (SPR shift) and is the refractive index change.

3. Results and Discussion

The successful synthesis of the composites was confirmed by FTIR and UV-VIS characterisations as shown in Figures 2 and 3, respectively. All the characteristics peaks for PANI, chitosan, and RGO were observed as summarised in Tables 1 and 2 for FTIR and UV-VIS, respectively. FTIR confirmed the presence of two important PANI peaks due to quinoid and benzoid vibration, respectively (Table 1) [71, 72].


Absorption frequencies (cm-1)
PANI/chitosanTernary

NH stretching34333433
OH group34333433
CH stretching2853, 29162853, 2919
C-N stretching16951584
C=C quinoid ring14871491
C=C benzoid ring16331589
Protonation of imine nitrogen12741295
CH bending799805
SO3- group10791088
C-S vibration mode559560


Wavelength (nm)Assignment

259-508π-π transition+localised Polaron
>750Delocalised polaron
<259Electronic conjugation due RGO
<259Chitosan absorption band

Assignment of UV-VIS peaks in PANI/chitosan and ternary composites for UV-VIS, both composites, shows PANI characteristics’ peaks attributable to transition of the benzenoid rings, localised polarons, and delocalised polarons at 325, 433, and above 900 nm, respectively (Table 2). The broad peaks before 259 nm were all attributed to the presence of chitosan and RGO [73].

3.1. Optical Constants of the Sensing Layers and SPR Studies

The optical constants of the PANI composites, particularly the complex refractive index and the dielectric constants, were all evaluated through the application of equations ((1)–(12)) at 633 nm. Their values together with other materials used are illustrated in Table 3. It is observed that the values of the optical constant in the ternary composites are greater compared to those of PANI/chitosan. This is due to the presence of reduced graphene oxide (RGO) which features many unique optical features [7476].


MaterialRefractive index ()
(633 nm)
Extinction coefficient ()
(633 nm)
Real part dielectric constant
(633 nm)
Ref.

Dry air1.0026[65]
PANI/chitosan1.89570.09103.5853Equations ((1)–(12))
Ternary2.69730.12497.2599Equations ((1)–(12))
Acetone vapour1.0011[65]
SF11 glass prism1.77863.8652E-083.1633[77]

Prior to the commencement of the SPR studies, different light sources were assessed for the applicability in SPR sensors based on the optical properties of the PANI composites. The assessment was conducted through the evaluation of penetration depth through the PANI composites (dielectric in this case) and the gold film. Table 4 shows the optical constant of gold thin film at different wavelengths of light [63].


Wavelength (nm)Refractive index ()Extinction coefficient ()Real part dielectric constant

6330.194043.5934-12.875
5890.261463.1019-9.5532
5460.396312.5581-6.3871
4411.554101.9847-1.5239
4361.570501.9933-1.5067

For a better SPR sensing capability, the penetration depth through metal is required to be as low as possible while the penetration depth through the dielectric is required to be as high as possible. Figure 4 shows a comparison between () and the composite materials at different light source wavelengths of red light (633 nm), yellow light (589 nm), green light (546 nm), violet light (441 nm), and blue light (436 nm, G-Line). Based on the above criterion, 633 nm was selected as the best light source for the subsequent SPR sensing studies based on PANI/chitosan and ternary composites. It can be observed that blue and violet light sources are not feasible as far as this study is concern. However, apart from the red light source which is the best, yellow light could also be applicable.

In order to obtain maximum sensitivity in our studies, we optimized the reflectance minimum () and minimized the width of the resulting resonance curve. As shown in Figures 5(a) and 5(b), this was achieved by selecting the appropriate thickness of the gold layer. We selected 10 different thicknesses of gold, from 42 nm to 51 nm in dry air. The narrowest width of SPR curve is observed in 51 nm thickness. However, its reflectance minimum is the shallowest. But as shown in the inset of Figures 5(a) and 5(b), the greatest depth is observed when the thickness of the gold is decreased to 46 nm (Figure 5(b)). In addition, its full width at half maximum is not the worst. As such, we selected the appropriate thickness of the gold layer throughout this study as 46 nm.

For the selection of appropriate thickness of the PANI layers, it is well-known that reflectance minimum and FWHM of SPR curves deteriorate with increasing thickness of over layer coatings [26, 74] and Figure 6 proves that for Figure 6(a), PANI/chitosan, and Figure 6(b), ternary composites films. However, in this study, thickness that could be achieved in reality has been considered [77, 78]. As shown in the figures (Figures 6(a) and 6(b)), as the thickness increases from 10 nm to 16 nm in dry air, the properties tend to be affected significantly. But we assumed the attainment of 15 nm thickness of the PANI composites as something closer to reality. As such, all our evaluations were based on that thickness except otherwise described.

The response linearity of the proposed sensor to change in the refractive index is illustrated in Figure 7. The values were generated by increasing the refractive index of dry air at interval of 0.005 due to the presence of analyte. It is shown that the SPR shift is completely linear over the wide range of refractive index change for both the bare gold-based SPR sensor and the composite-based SPR sensors. This shows the potential application of the PANI composite materials in SPR sensors.

Figure 8 shows the SPR curves generated from the detection of low concentration of acetone vapour in air from 0.5 ppm to 10 ppm using gold-based (Figure 8(a)), PANI/chitosan composite-based (Figure 8(b)), and ternary composite-based (Figure 8(c)) SPR sensors. Using equation (17), the refractive indices of acetone vapour at different concentrations were calculated. The values of refractive index change with respect to air are illustrated in Table 5. It is observed from Figure 8(a) that bare gold surface could not show any significant SPR shift for acetone vapour in 0.5 ppm to 10 ppm concentration range. This is the diabetes range of interest. However, the PANI/chitosan and the ternary composites show maximum sensitivity of about 60 and 180 degree per refractive index change, respectively. The performance of the gold-based SPR sensor in the detection of the acetone vapour is due to its lack of adsorption capability to gases at a low concentration.


Concentration (ppm)Refractive index change ()

0.5
2
4
6
8
10

The selectivity of the PANI/chitosan- and the ternary composite-based SPR biosensors to acetone vapour was also investigated by examining the sensor response (SPR shift) to the common interfering vapours such as ethanol, methanol, and ammonia [79, 80]. Figure 8(d) shows the selectivity of the two sensing layers to 10 ppm concentrations of acetone, ethanol, methanol, and ammonia vapours with their refractive index values estimated based on Arago–Biot mixing formula (equation (17)). The increment in refractive index for the vapours with respect to that of air (1.000263719) was found to be , , , and for acetone, ethanol, methanol, and ammonia vapours, respectively. Both the PANI/chitosan- and the ternary-based SPR sensors show higher response for acetone vapour compared to other three vapours. Furthermore, PANI/chitosan-based SPR sensors show no response to 10 ppm concentrations of methanol and ammonia. In addition, the ternary composite-based SPR sensor still maintained the highest response compared to the PANI/chitosan-based sensor.

The improved sensitivity and selectivity of PANI/chitosan- and the ternary composite-based SPR biosensors are due to the abundance of functional groups in the PANI composites, their possible solvation, and unique optical and electronic properties. In addition, the better performance of the ternary composites could also be attributed to the unique properties of reduced graphene oxide. Furthermore, graphene-based materials are known to adsorb carbon-based materials strongly and stably. Hence, our PANI composite-based SPR sensors, especially the ternary based, could open a way to achieve a reliable gas-phase SPR sensor with potential applications in health and environmental monitoring.

Usually, gas sensing mechanisms are explained based on the change in the index of refraction in the analyte volume, the formation of an adsorbed layer, the diffusion of the analyte gas into the sensor layer, and the solvation of the analyte gas in the sensor layer [81]. Interestingly, in addition to low temperatures (below 100 °C), operation capability, and inexpensiveness in PANI-based sensors, PANI optical properties can be tailored (through doping or composites formation) to attract a specific gas (based on mechanisms stated in the introduction part) and thus can have high selectivity [54]. As such, we investigated the possible improvement in SPR shift with an increased value of refractive index in PANI/chitosan (Figure 9(a)) and ternary composites (Figure 9(b)). The imaginary value of the refractive index was kept constant. The result shows the 0.1 unit refractive increment to produce almost no improvement in SPR shift (also sensitivity) for both PANI/chitosan (Figure 9(a)) and ternary composites (Figure 9(b)). However, as the refractive index is increased by 0.5 units, the SPR shift increased significantly before dropping after adding about 1.5 unit of refractive index. Therefore, it could be concluded that the two composites need no further improvement. This is because the increment in refractive index that is normally achieved experimentally is within 0.1 unit increment range.

4. Conclusions

This work presents the application of PANI/chitosan composite and a ternary composite comprising of PANI, chitosan, and reduced graphene oxide in the SPR sensing of acetone vapour for the monitoring and screening of diabetes using mathematical modeling and simulation. The synthesis of the composites was based on oxidative polymerisation of aniline using ammonium peroxydisulfate (APS) and characterised using FTIR and UV-visible spectroscopy. Optical constants of the composites were extracted from the absorption spectra of the UV-VIS spectroscopy and applied in the simulation of a surface plasmon resonance- (SPR-) based acetone vapour sensor functionalised with PANI/chitosan and ternary composites for diabetes interest, 1.8 ppm–5.0 ppm. The response in the case of ternary composite shows best linearity with correlation coefficient values of 1.0 compared to PANI/chitosan- and gold-based SPR layers with 0.9999 and 0.9997, respectively. The result indicates promising application of the composite-based sensor in the detection of acetone vapour at a low concentration down to less than 0.5 ppm. The maximum sensitivity values of about 60 and 180 degree per refractive index change were observed for PANI/chitosan and ternary composite sensing layers, respectively, in comparison with the bare gold-based SPR which shows zero response up to 10 ppm concentration of acetone vapour in air. The sensing layers also show better selectivity to acetone vapour compared to ethanol, methanol, and ammonia vapours. Hence, the PANI/chitosan and ternary composite sensing layers, especially the ternary composite, would have a great potential in realising a gas-phase SPR biosensor for health and environmental monitoring.

Data Availability

Data would be made available upon request.

Conflicts of Interest

The authors declare no conflict of interests.

Acknowledgments

This work is supported by the Fundamental Research Grant Scheme, under Grant 015MA0-018 of the Ministry of Higher Education Malaysia and the Yayasan Universiti Teknologi PETRONAS-Fundamental Research Grant, under Grant 0153AA-E40.

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