Comparative study on the Preparation and Gas sensing properties of

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Comparative study on the Preparation and Gas sensing properties of Reduced Graphene oxide/SnO2 Binary nanocomposite for Detection of Acetone in Exhaled Breath Ramji Kalidoss, Snekhalatha Umapathy, Rohini Anandan, Ganesh Vattikondala, and Yuvaraj Sivalingam Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.8b05670 • Publication Date (Web): 14 Mar 2019 Downloaded from http://pubs.acs.org on March 14, 2019

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Analytical Chemistry

Comparative study on the Preparation and Gas sensing properties of Reduced Graphene oxide/SnO2 Binary nanocomposite for Detection of Acetone in Exhaled Breath Ramji Kalidossa, Snekhalatha Umapathya,*, A. Rohinib, V.Ganeshb, Yuvaraj Sivalingamb,c aDepartment

of Biomedical Engineering, SRM Institute of Science & Technology,

Tamilnadu-603203, India.

bDepartment

of Physics and Nanotechnology, SRM Institute of Science & Technology,

Tamilnadu-603203, India.

cLaboratory

for Sensors, Energy and Electronic Devices (Lab SEED), SRM Research

Institute, SRM Institute of Science & Technology, Tamilnadu-603203, India.

ACS Paragon Plus Environment

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Analytical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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KEYWORDS: Reduced Gaphene Oxide; Binary Nanocomposites; Diabetes Mellitus; Breath Analysis; Gas Sensors.

ABSTRACT

Reduced graphene oxide/Tin dioxide (RGO/SnO2) binary nanocomposite for acetone sensing performance was successfully studied and applied in exhaled breath detection. The influence of structural characteristics was explored by synthesizing the composite (RGO/SnO2) using solvothermal method (GS-I) and hydrothermal method (GS-II) by chemical route and mechanical mixing, respectively. The nanocomposites characterized by X-ray diffraction (XRD), High resolution transmission electron microscope (HRTEM), Fourier transform infrared spectroscopy (FTIR) and Brunauer-Emmett-Teller (BET) revealed that GS-I exhibited better surface area, surface energy and showed enhanced


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gas response than GS-II at an operating temperature of 200 oC. These sensors exhibited comparable response in humid environment as well, suitable for acetone sensing in exhaled breath that clearly distinguishes between healthy and diabetes subjects. The enhanced response at lower concentrations was attributed to the synergistic effect at the RGO/SnO2 interface. These results indicate that modification in the structural characteristics of RGO/SnO2 nanocomposite enhances the sensing property. Furthermore, it proved to be a promising material for potential application for point-of care, non- invasive diabetes detection.

1. INTRODUCTION

Diabetes Mellitus (DM) is a metabolic disease characterized by hyperglycemia resulting from the lack of insulin secretion (Type I DM), insulin action (Type II DM) or both. Long term effects of DM include potential loss of vision, renal failure, risk of foot


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ulcers, cardiovascular complications and osteoporosis, leading to increased risk in fracture.1 As a result of hyperglycemic condition (high blood glucose level), the biochemical reactions involve decarboxylation of acetoacetate and dehydrogenation of isopropanol which is an abundantly available source in liver for acetone production.2 The produced acetone in blood gets diffused to the airways through lungs, as the blood/air partition coefficient of acetone at normal human body temperature is 341 and diffused through urine.3 Numerous literatures had reported the diagnosis of diabetes through acetone concentration in breath.4,5 These studies had established the mean acetone concentration in a healthy human breath to be 300-900 ppb and in diabetic breath an anomalous concentration exceeding 1800 ppb.6,7 Some of the analytical techniques to qualitatively asses the breath compounds are gas chromatographic technique combined with mass spectrometry, laser spectroscopy and photo ionization detectors.8-10 However, these methods are inadequate for routine blood glucose monitoring as they rely on sophisticated laboratory equipments and lack of real time quantitative data. In contrast, chemi-electrical gas sensor had drawn an interest to the scientific community


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for their low cost facile fabrication, reliable measuring electronics and miniaturization potential.

Recently,

graphene

based

binary

nanocomposites

with

n-type

metal

oxide

semiconductors are reported as an efficient acetone gas sensor.11-14 A heterojunction at the interface of graphene and n-type metal oxide semiconductor develops an intimate electrical contact responsible for sensitive detection. Commonly, SnO2 with wide bandgap energy tend to equalize the fermi levels across the interface and effective band bending occurs. Therefore, even a ppb concentration level of acetone vapor near the vicinity of RGO/SnO2 nanocomposite causes a significant change in its electrical parameter. The RGO/SnO2 nanocomposite with precisely modified sensing area and oxygen vacant facets are expected to influence the sensing behavior.15 Accordingly, a number of synthesis procedures had been developed such as electrospinning, mini arc reactor, complex microwave argon environment, surfactant based self-assembly.16-18 Compared with all other synthesize procedures, the chemical routes (Hydrothermal and solvothermal methods) used to synthesize RGO/SnO2 gas sensor material tend to alter


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the structural characteristics with ease. These methods involve working at harsh environments and hence the material is stable for a longer time. Further, chemical routes are simple, economic and therefore suitable for mass production. To investigate the role of structural properties, we have pointed out two different synthesis procedures. The first method involves a one-pot solvothermal route and the second consists of mechanical mixing of reduced graphene oxide sheet and SnO2 nanoparticles prepared by hydrothermal method.

In our work, acetone sensors for glucose monitoring were fabricated with Reduced graphene oxide/Tin dioxide (RGO/SnO2) binary nanocomposites synthesized by solvothermal (GS-I) and hydrothermal methods (GS-II). The sensing performance was investigated with different acetone exposures in humid environment at an operating temperature of 200

oC

and the stability parameter of the prepared sensors was

calculated over a period of 1 month. The responses to the interfering disease biomarker were studied and applied to exhaled breath analysis. The RGO/SnO2 binary nanocomposite sensors exhibited unprecedented sensitivity, selectivity, aging stability


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and a minimal uncertainty in discrimination of diabetes and healthy breath. However, subtle difference in the sensing performance is observed as a consequence of different preparation procedures. These investigation results highlight the possibility of acetone detection in breath by RGO/SnO2 nanocomposite for diabetes detection. Moreover, the sensitive and selective acetone sensing mechanism was discussed in detail.

2. EXPERIMENTAL SECTION

2.1. Materials

All the reagents and solvents (Southern India Scientific Co. Ltd., India) used in this study were of analytical grade and used as received. Graphene oxide (GO) was prepared from natural graphite flakes through modified Hummers method

19

and a

portion was later reduced via modified hydrothermal method as reported.20

The RGO/SnO2 nanocomposites have been prepared by two different routes schematically illustrated in Figure 1. The first procedure includes a one pot solvothermal method as reported in the previous literature.21 In a typical synthesis, 20 mg of SnCl2


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and 100 mg of GO were added in 30 ml of isopropanol, followed by sonication for 1 h to obtain a completely dispersed solution. Subsequently, 1 ml of deionized water was added dropwise, and stirred for 30 min. Then, the dispersion was transferred into a 100 mL Teflon-lined stainless-steel autoclave and heated at 180 oC for 16 h. After cooled down to room temperature, the solution is washed with deionized water and absolute ethanol several times. The residue was dried at 60 oC overnight to obtain a black precipitate.

In the second method, SnO2 nanoparticles were prepared as reported in the previous literature by hydrothermal method.22 In brief, 50 mg of SnCl2 was added to 10 ml of deionized water, and then sonicated for 30 min to obtain a completely dispersed solution. The dispersion was then transferred to 100 mL Teflon lined autoclave and heated at 180 °C for 14 h. The obtained white precipitates were collected by centrifugation using ethanol several times. Required amount of the prepared SnO2 was dispersed in deionized water and mixed with GO sheets (1:5). The mixed solution was


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then sonicated for 30 min and washed with deionized water and dried at 60 °C overnight.

Figure 1. Schematic illustration of one pot solvothermal and two step hydrothermal synthesis procedures of reduced graphene oxide/Tin dioxide nanocomposite. Color schemes: grey –carbon, red – oxygen, white – hydrogen, blue – SnO2 nanoparticle.

2.2 Characterization


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The morphologies of binary nanocomposites were characterized by Field Emission scanning electron microscope (FESEM) FEI Quanta FEG 200 HR-SEM. The samples was dispersed by ultrasonication and drop-coated on carbon coated copper grids to study the microstructures using JEOL JEM 2000 high resolution transmission electron microscopy (HRTEM) and selected area electron diffraction (SAED) at an accelerating voltage of 200 kV. Powdered X-ray diffraction intensities were characterized by X-ray diffractometer X’pert PRO (PANalytical) using Cu Kα (λ=1.5418 Å) radiation at a scanning rate of 3 o/min. Fourier Transform Infrared Spectra (FT-IR) were recorded on Cary 660 FT-IR,(Agilent Technologies Pvt. Ltd.) in the infrared spectrum between 4000 cm-1 to 400 cm-1. The BET surface area, pore diameter and pore volume distribution of the GO/SnO2 composite were measured by N2 degassed at 150 oC using autosorb (Quantachrome Instruments, USA). The work function changes of the binary nanocomposites in the presence of ambient air and acetone were characterized by Scanning Kelvin Probe (SKP) with 2 mm diameter vibrational gold tip at the frequency of 78.3 Hz (SKP5050 model, KP Technologies Ltd, UK).


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2.3 Sensor fabrication

The binary nanocomposites (GS-I and GS-II) and bare RGO were dispersed in isopropanol in the ratio of 1:4 to form slurry for spin coating on a 1 cm × 1 cm squared alumina substrate. Gold electrodes were thermally evaporated on the either end of the substrate with the metal contacts established using platinum leads. The Ni-Cr heater fixed at the backside of the substrate to radiate uniform heat in the operating temperature range of 150 °C – 350 °C. Finally, GO/SnO2 nanocomposite sensors were thermally reduced by annealing at 100 °C for 2 h. During the process, the free radicals containing oxygen in solvent develops radical reaction with the carbon dangling bonds at defective sites or with the negatively charged oxide functional group of GO films, eventually leading to reduction of GO (RGO).23-25 The fabricated sensors were then thermally aged in baseline gas (humid atmosphere) for 5 days at 350 oC to improve the mechanical strength of electrical contact and placed in a 250 mL vacuum chamber. The desired concentration of acetone vapor was realized by taking required amount of gas (Table S1) from the obtained precalibrated cylinder (500 ppm acetone, 500 mL gas cylinder, Chemtron Science Laboratories) in a gas tight syringe and then injected it into the


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chamber. The vapor sensing properties such as sensor response and sensitivity were measured via Keysight 34465A data logger, allowing the resistance measurements in the range from 100 Ω to 1000 MΩ. To achieve better signal to noise ratio at baseline coaxial cables were used.26 The relative gas response (S) to acetone is defined as:

S=(Ra/Rg)-1 (1)

where Ra and Rg are the electric resistances of the sensing film in air and acetone gas, respectively. Sensitivity is defined as the derivative of sensor’s relative response with respect to gas concentration.27 Response time and recovery time were the time taken by the sensor to reach 90% resistance change of the final equilibrium value.

Furthermore to measure the work function changes in air and acetone environment, bare RGO, GS-I and GS-II were sonicated with isopropanol in 1:4 ratio and spin coated on the ITO substrate.

2.4 Clinical studies


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Breath samples of diabetic subjects and healthy subjects were collected before breakfast in a Tedlar bag (1 litre) at SRM hospital and research center under administration by the doctor. Each breath collection bag equipped with a mouthpiece is filled with calcium chloride desiccants to selectively adsorb humidity from breath.28 After three tidal volume ventilations and a deep inspiration, subjects exhaled for 7 sec at ~200mL/sec to minimize the flow rate variation. The first 3 sec (~600 mL) of exhaled breath was vented out to clear anatomic dead space volume and the remaining breath sample (alveolar breath) was then transferred to occupy the whole volume (250 ml) of the sensor chamber using a gas tight syringe as shown in Figure 2. The blood and urine samples were collected before breakfast to obtain glucose levels in blood and ketone levels in urine by the gold standard methods at the biochemical examination facility. The medical sample collection and acetone detection procedures were approved by institutional ethical committee along with signed consent from all the sample donors. Finally, the obtained signals were digitized and transmitted through a data acquisition card.


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Figure 2. Schematic illustration of acetone sensor and the gas testing process in clinical study.

3. RESULTS AND DISCUSSION

3.1 Material characterization


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Figure 3 displays the X-ray diffraction patterns of GO, GS-I, GS-II and RGO samples, respectively. The XRD pattern of GO delineated an intense sharp peak at 2θ = 11.6o attributed to (002) plane. The deoxygenation of exfoliated GO calcined at alkaline medium exhibited a broad diffraction peak at 24.21o (Figure. 3d), indicating a fully reduced GO with the removal of most of the oxygen functional group from the surface. 29, 30

For the binary composites, the peaks centered at 26.56o, 33.82o and 51.50o can be

assigned with (1 1 0), (1 0 1), and (3 0 1) planes, which corresponds to tetragonal rutile SnO2 (JCPDS Card No. 41-1445). Due to exfoliation of graphene into single layer 2D sheet and loading of 5:1 weight ratio leads to suppression of the strong (0 0 2) peak of graphene oxide.31 As shown in the Figure 3, GS-I is more crystalline than GS-II as it exhibits a narrow diffraction peak with high intensity.32 As the solvent (Isopropanol) allows slower nucleation, the growth of the high crystalline nanoparticle was more favorable.33


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Figure 3. X-ray diffraction patterns of (a) GO, (b) GS-I, (c) GS-II binary nanocomposite and (d) RGO. Figure 4a-c presents the FE-SEM images of the GO, GS-I and GS-II samples. In Figure 4a, the graphene oxide exhibits a monolayer homogeneous wrinkled structure. The SEM images of GS-I & II (Figure 4b-c) clearly shows the coverage and stacking of SnO2 nanoparticles between reduced graphene sheets. This inference is further supported by TEM images. The uniform coverage of SnO2 nanoparticles on reduced graphene oxide sheets in GS-I were revealed in Figure 4d, whereas in GS-II (Figure 4e) agglomeration and random distribution was observed with the spherical morphology. Their particle size ranged between 12 - 48 nm and 34 - 50 nm for GS-I and GS-II, respectively. The nanocomposite prepared by the solvothermal method allows slower nucleation leading


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to lower particle size.33 The HR-TEM image of RGO/SnO2 nanocomposites (Figure 4f) confirms the presence of SnO2 nanoparticles with the fringes spacing 0.35 nm which agreed well with the spacing of dominant peak (1 1 0) lattice plane.34

Figure 4. SEM images of (a) GO, (b) GS-I, (c) GS-II and TEM images of (d) GS-I, (e) GS-II sensor. (f) HRTEM image of RGO/SnO2 binary nanocomposite.

Fourier Transform infrared spectroscopy reveals the presence of various surface bound chemical species depicted in Figure 5. Absorption band in the range of 600 - 650 cm-1 is attributed to antisymmetric vibrations of O-Sn-O and stretching vibrations of Sn-O.35 The lower intensity of these vibrations in GS-II may be attributed to the low crystallinity of SnO2 in accordance with the results obtained from XRD. 36 The broad peak near 3440 cm-1 indicates the presence of sharp and stretching hydroxyl groups (O-H) which is


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relatively stronger in GS-I. The peak around 1620 cm-1 indicates mono substituted alkene groups (C=C) and the peak centered at 1380 cm-1 implies bending alkane bonds (C-H). The peak at 1180 cm-1 is associated with the presence of strong C-O stretching bond.37 GS-II also showed all of these peaks but with lower intensity and slightly different frequencies. FT-IR spectrum discloses the modification in absorbance peaks between the prepared nanocomposites, indicating a small variation of bending and stretching

vibrations

of

surface

functional

groups.

Although

the

absorption

characteristics of RGO/SnO2 nanocomposites were almost identical, the Sn-O bonds of GS-I on the surface region were much influenced by surface bound chemical groups. Hence there is a difference of 7 cm-1 due to the fact that functional groups in GS-I tend to vibrate at higher frequencies. This leads to more unsaturated surface bonds and further better vander waals force of attraction between the sensor material and acetone molecules.38


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Figure 5. FTIR Spectra of (a) GS-I and (b) GS-II.

The surface area and pore diameter influences the gas sensing performance based on the interactions between target gas molecule and active sensing surface. The N2 adsorption/desorption isotherm in Figure 6, showed type-II hysteresis loop, exhibiting meso-porosity. In comparison with the high BET surface area (101.35 m2/g) and pore diameter (3.72 nm) of GS-I, the BET surface area and pore diameter for GS-II is as low as 43.51 m2/g and 1.56 nm. Their respective pore size distribution curves are shown in inset of Figure 6. The pore size distributions of GS-I are well centered at 3.7 nm, but not well concentrated for GS-II with multiple peaks at 1.5 nm, 6.1 nm and 11.7 nm. Both the sensor material possesses a good porous structure and was considerably retained in


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GS-I even after sonication and heat treatment, indicating good mechanical stability, an important property for gas sensor. These results illustrate that the binary nanocomposite prepared via solvothermal method has a numerous active sites for surface contact reactions and enhances gas adsorption-desorption ability.

Figure 6. N2 adsorption-desorption isotherms of (a) GS-I and (b) GS-II. The inset image shows the pore size distributions of the fabricated sensors.

3.2 Electrical transport and vapor sensing behavior

Figure 7a shows the relative response of GS-I & II for 5 ppm acetone vapor at varying operating temperatures (100 oC to 300 oC). The relative responses of GS-I and GS-II for


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5 ppm acetone vapor were 31.92 and 17.98, respectively. The higher response of the sensor synthesized by solvothermal method (GS-I) may be attributed to the oxygen functional group, vibrating at higher energy. This shows a capability of effectively adsorbing target gas on the surface.38 Similarly, the influence on gas sensing properties of RGO/SnO2 by different preparation methodologies is compared with the reported literature as shown in table S2. However both the sensor exhibits volcano shaped behavior at varying operating temperatures because of the alteration in thermodynamics of gas adsorption and desorption on the sensor material.39-41

Figure 7b shows the Arrhenius plot of resistance change with temperature at ambient atmosphere. The activation energy evaluated from slope of Arrhenius plot which is a linear fitting of resistance rate with temperature. The activation energy at ambient air is lesser (4.037 kJ/mol) for GS-I sensor compared to GS-II sensor (16.702 kJ/mol). A shift in the activation energy of GS-II indicated the inhomogeneous distribution of SnO2 on RGO sheets. Hence the different activation energies correspond to the RGO sheets and SnO2 nanoparticles. Whereas, the uniform slope and lower activation energy of GS-I


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indicates the reaction between the target vapor and GS-I sensor to be sensitive and faster.42 The sensor resistances at optimized temperature (200 oC) were found to be 444 MΩ and 256 kΩ for GS-I and GS-II as depicted in Figure S1. This significant difference in baseline resistance between the sensors was attributed to the uniform distribution of SnO2 in GS-I as evident from the TEM images (Figure 4d & 4e).

Figure 7. (a) The relative response of the fabricated sensors to 5 ppm acetone at various operating temperatures, (b) Arrhenius plot of rate of resistance change of the sensors with temperature at ambient atmosphere. The transient response of the binary nanocomposites to acetone pulses with different concentrations from 0.5 to 30 ppm at 200 oC is displayed in Figure 8 a&b. Further, the response of bare RGO to acetone pulses with concentrations ranging from 5 to 50 ppm at 200 oC were studied and depicted in Figure S2. They exhibited an n-type behavior as


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the resistance of the sensors decreases from the baseline resistance after gas input.38 This can be attributed to the fact that the majority carriers in SnO2 and RGO are electrons when annealed at 350 oC.43 Moreover the scanning kelvin probe studies has suggested the sensing materials to exhibit n-type behavior based on the work function change (Figure S3) and Fermi level shift (Figure S4) between air and acetone environment.

Figure 8c plots the relative responses of the sensor to varying acetone vapor concentration. It can be seen that the relative response of the prepared sensors were found to increase in the concentration range 0.25 ppm to 5 ppm and negligible beyond 5 ppm. The negligible response at higher vapor concentration was ascribed to the declination in active vapor adsorption and desorption sites.44 Hence the sensors showed higher sensitivity at lower concentration and the slope is due to the availability of free surface for physisorption process. While the slope at higher concentration indicates poor electrical response because of the chemisorption process that affects the sensor performance due to the unavailability of active sites.45 The linear correlation of


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GS-I (R2=0.9939) and GS-II (R2=0.9852) at lower acetone concentration (inset image of Figure 8c) indicates that the binary metallic hybrid RGO/SnO2 is a suitable candidate for potential application of diabetes detection from breath.

To further investigate the gas selectivity, the responses of the sensor to 20 ppm of disease biomarkers (Acetone, Hydrogen Sulfide, Ammonia and Methanol) were experimented. The relative response of GS-I to acetone is high compare to other interfering gases. In contrast, GS-II exhibited poor cross selectivity as seen in Figure 8d. This is due to the lower intensity exposure of oxygen vacancies of SnO2 (1 1 0) that is responsible for selective adsorption of acetone.46


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Figure 8. Transient response curves of (a) GS-I, (b) GS-II sensor, (c) relative responses exposed to acetone with concentration ranging from 0.5 to 30 ppm operating at 200 oC and (d) selectivity characteristics of the sensors to acetone at 200 oC with respect to Methanol, Ammonia, and Hydrogen Sulfide.

Humidity characteristics of the fabricated sensors revealed negligible humidity interfering effect as shown in Figure S5 due to the chemical inertness and hydrophobic surface of RGO in both the sensors

47, 48.

The relative responses of the sensors for 30


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days at 3 days regular interval are displayed in Figure S6. It can be seen that the decline in response between the initial and final day was calculated to be 1.33% for GSI and 3.11% for GS-II. The response (recovery time) of GS-I and GS-II to 5 ppm acetone vapor depicted in Figure S8 were 24s (64s) and 30s (72s) with stable repeatability (Figure S7).

Further, clinic test was conducted to estimate acetone concentration in human breath with 5 diabetic and 5 healthy volunteers with the validated sensors. The relative response to the exhaled breath with respect to the subjects was plotted (Figure 9). The results show that there is a prominent discrimination between healthy and diabetic volunteer for GS-I sensor. However, even with the same dilution ratio and experimental protocol, GS-II showed a minimal uncertainty. This difference in responses between GS-I and GS-II sensor probably depends on their structural property and it progresses according to the surface area, surface energy and the nature of dispersion of oxygen vacant facets.


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Figure 9. Relative responses of (a) GS-I and (b) GS-II at 200 ̊C for clinical test data to diabetic and healthy subjects.

3.3 Sensing mechanism

The vapor sensing mechanism of SnO2 usually involves redox reactions between the adsorbed oxygen species from the atmosphere and the acetone vapor. The (1 1 0) facet in SnO2 has a number of uncoordinated oxygen vacancies that donates electrons to the conduction band.49 The atmospheric oxygen captures the electrons from the conduction band that causes a reduction in carrier concentration. Hence increase in the resistance of the material (Oxidation).43 Electron capture leads to the ionization of adsorbed oxygen into molecular (O2-) and atomic (O-, O2-) forms. The dominating species depends on the working temperature and the composite doped with SnO2.38 Further


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upon infusion of reductive gas (acetone) into the test chamber, the target gas reacts with the surface ionized oxygen, resulting in a decrease in surface O2- and O-, O2-, leading to an increase in concentration of electrons in the conduction band.50

The enhanced response of RGO/SnO2 nanocomposite to acetone can be attributed to the following reasons. Firstly, SnO2 functionalization into RGO matrix leads to more active sites that support acetone adsorption. Further, SnO2 functionalization leads to increased resistance of the nanocomposite hindering the effective charge transfer at the heterojunction leading to higher baseline resistance and higher sensor response. 17, 51-53 Secondly, as reported by the previous studies the large surface area benefitted from reduced graphene oxide facilitates gas adsorption and diffusion through active sites.54, 55

Thirdly, as the work function of reduced graphene sheets (Ф1 = 5.3 eV) is higher than

that of SnO2 nanoparticles (Ф2 = 4.9 eV) forming n-n heterojunction. Hence an energy barrier height (ΔE) exists due to the differences in Fermi levels.

56, 57

This leads to the

formation of accumulation region at the interface of n-type semiconducting oxides. Further, depletion of accumulation region is achieved by larger oxygen adsorption from


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air leading to high baseline resistances (Figure S9). These high baseline resistances and the contribution of n-n heterojunction between RGO and SnO2 may be responsible for improved acetone sensitivity.58, 59 The interactions of volatile acetone vapor with the graphene bimetallic hybrid are driven by electrical polarization and acts as an electron donor (Reduction).15 The electron transfer can occur from low work function material (SnO2) to the higher work function (RGO) until the equalization of fermi level and results in the band bending of bandgap energies (Figure S9).60 Hence there is a specific capture and migration of electrons from SnO2 nanoparticles to reduced graphene oxide sheets and results in decrease in resistance. Therefore, effective sensitivity of RGO/SnO2 nanocomposite is due to the effects of high conductive graphene sheets, formation of n-n hetero junction and high surface area.

The formation of electron cloud by the asymmetric arrangement of O atoms in SnO249 and high dipole moment of acetone (Table S3) causes highly selective sensing. Hence, the selectivity of the composite to acetone was primarily ascribed to the exposure of oxygen vacant facets.15 Exposure of (110) plane of SnO2 has numerous unsaturated


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coordinated O atoms leaving more oxygen vacancies.45 The asymmetric arrangement of oxygen atoms causes a distribution of electron cloud and leads to electrical polarization. As the dipole moment of acetone compared to other vapors (Table S3) is significantly large, strong interactions takes place and leads to selective adsorption, even though with lesser kinetic diameter. Thus, due to the presence of oxygen vacant facets and high vander waals force of attraction easier adsorption of acetone molecules happens, hence could be operated at lower temperature. Based on the factors mentioned above for sensitivity and selectivity, GS-I dominates GS-II on surface area, surface energy and distribution of oxygen vacant facets. Hence both the sensors possess similar sensing characteristics, with GS-I exhibiting high sensing performance.

4. CONCLUSION

Finely dispersed SnO2 nanoparticles supported on graphene sheets have been prepared by one step solvothermal and mechanically mixed hydrothermal method for highly sensitive and selective acetone vapor sensor. A systematic comparison of


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sustainable synthesis procedures has been carried out to understand the influence of structural properties in terms of distribution, surface area and surface energy. Comparatively one pot synthesized GS-I exhibited effective structural properties and better acetone sensing performance. The nanocomposite sensors achieved a linear response at lower concentration (0.25 ppm – 3 ppm), high selectivity and aging stability. Further, clinical tests were also performed, indicating that the binary nanocomposite sensors proved to discriminate healthy and diabetic breath.

ASSOCIATED CONTENT

Supporting Information

Dilution ratio of acetone vapor from gas tight syringe to sensor chamber; I-V characteristics of the fabricated sensors; Transient response curve of RGO exposed to acetone with concentration ranging from 5 to 50 ppm operating at 200 ̊C; Comparison of


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synthesis procedures of RGO/SnO2 hybrids and its gas responses; Fermi level and work function changes of the fabricated sensors in air and acetone environment; Humidity characteristics of the fabricated sensors; Stability characteristics of the fabricated sensors; Response and recovery time of the fabricated sensors; Dipole moment and kinetic diameter of different biomarkers; Proposed energy band structure diagram for n-type RGO/n-type SnO2 and schematic model for the RGO/SnO2 nanocomposite sensors exposed to acetone. AUTHOR INFORMATION

Corresponding Author

*Email: [email protected] (Snekhalatha Umapathy)

Notes

The authors declare no competing financial interest.

ACKNOWLEDGEMENT The authors are thankful to Prof. Kantha D Arunachalam, Dean, Center for Environmental Nuclear Research and Prof. M.Sasidharan, HOD, SRM Research Institute for encouraging the research and providing the necessary facility. The authors


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are thankful for extending the facility of Scanning Kelvin Probe system funded by the Department of Science & Technology (ECR/2017/001218) – Science and Engineering Research Board (SERB), Government of India.

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Comparative study on the Preparation and Gas sensing properties of

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