Recent advances in carbon material-based NO2 gas sensors

Accepted Manuscript Title: Recent Advances in Carbon Material-Based NO2 Gas Sensors Authors: Sang Won Lee, Wonseok Lee, Yoochan Hong, Gyudo Lee, Dae Sung Yoon PII: DOI: Reference:

S0925-4005(17)31640-4 http://dx.doi.org/10.1016/j.snb.2017.08.203 SNB 23070

To appear in:

Sensors and Actuators B

Received date: Revised date: Accepted date:

21-4-2017 2-8-2017 29-8-2017

Please cite this article as: Sang Won Lee, Wonseok Lee, Yoochan Hong, Gyudo Lee, Dae Sung Yoon, Recent Advances in Carbon Material-Based NO2 Gas Sensors, Sensors and Actuators B: Chemicalhttp://dx.doi.org/10.1016/j.snb.2017.08.203 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Recent Advances in Carbon Material-Based NO2 Gas Sensors Sang Won Leea, Wonseok Leeb, Yoochan Hongc, Gyudo Leea*, Dae Sung Yoona*

a

School of Biomedical Engineering, Korea University, Seoul 02841, Korea

b

Department of Biomedical Engineering, Yonsei University, Wonju 26493, Korea

c

Department of Medical Device, Korea Institute of Machinery and Materials (KIMM), Daegu Research Center for Medical Devices and Green Energy, Daegu 42994, Korea

*Corresponding author. E-mail address: [email protected] (D.S. Yoon); [email protected] (G. Lee)

Contents Abstract 1.

Introduction

2.

One-dimensional (1D) material: Carbon nanotube (CNT)

3.

2.1

Configuration and mechanism of CNT-based gas sensors

2.2

Doping the dopant on CNT

2.3

CNT-based nanocomposite materials

Two-dimensional (2D) material: Reduced graphene oxide (rGO)

3.1

Configuration and mechanism of rGO as a NO2 gas sensors

3.2

Doping the dopant on rGO

3.3

Chemical functionalization of rGO

3.4

rGO-based nanocomposite materials

3.5

Three-dimensional (3D)-like material: Stacked layers of rGO

4.

Other carbon nanomaterials

5.

Perspective and conclusions

ABSTRACT: Nitrogen dioxide (NO2) detection is critical because NO2 is a typical toxic gas that is harmful to humans as well as the environment. Over the last few decades, various nanomaterials such as nanowires, nanoparticles, carbon nanotubes, and graphene have been widely utilized to construct the platform (i.e., supporting material) of NO2 gas sensors. Among these materials, carbon nanomaterials (e.g., graphene and carbon nanotubes) have received increasing attention owing to their outstanding physical and electrical properties required for NO2 detection. Recently, many attempts have been made to blend the carbon nanomaterials with other materials, resulting in the creation of composite materials with enhanced electrical conductivity and physical properties for highly sensitive and selective detection of NO 2 gas. As such, blended or stacked carbon composite materials offer higher

efficiency (i.e., improved sensitivity and response/recovery time) for detecting NO2 gas in comparison with pristine carbon nanomaterials. In this review, we consider state-of-the-art amperometric NO2 gas sensors based on carbon nanomaterials with respect to their dimensionalities, and we discuss the enhanced gas-sensing performance achieved by using composite materials.

Keywords: nitrogen dioxide (NO2) electrical gas sensor response/recovery time carbon nanotube reduced graphene oxide nanomaterial

Introduction

1

Nitrogen dioxide (NO2), which is volatile and has a pungent smell, is a toxic gas that can be deadly to humans and is harmful to the environment [1-7]. NO2 is formed via many pathways, such as car exhaust, burning of fossil fuels, and emissions from industrial complexes. Recently, diesel vehicle emission that

contains a high amount of NO2 is becoming an increasingly serious issue [8, 9]. Moreover, NO2 as a volatile gas can undergo photochemical reactions with other pollutants or water, generating ozone or acid rain [10-13]. NO2 can also be formed as a secondary pollutant, increasing its hazardous effects on the environment [14-16]. Further, the gas causes nose and throat discomfort, transient coughs, eye irritation, fatigue, and nausea in extremely low concentrations (<10 ppm) or affects debilitating pulmonary system diseases, often with no symptoms [17-20]. In these regards, detecting the harmful NO2 gas has emerged as one of the most important sensing techniques. Over the past few decades, NO2 gas detection using electronic signal has been reported with sensors based on a wide variety of materials, such as polymers [16, 21-26], metal oxide/metallic nanoparticles (NPs) [27-31], nanowires [32-36], nanobelt [37], molybdenum disulfide (MoS2) [38, 39] and carbon nanomaterials [40-43]. Especially, owing to their remarkable physical and electrical properties, carbon nanomaterials (e.g., carbon black (CB) [44, 45], fullerene [46], carbon fiber (CF) [47, 48], carbon nanotubes (CNTs) [20, 49-54] and graphene [55-60] ) have received a great deal of attention as materials for gas sensors. With their inherent physical/electrical properties, such as high surface-to-volume ratios, high electrical or heat conductivities, chemical inactivity, and high tensile strength, carbon nanomaterials are optimal for NO2 gas sensing via changes in electronic signals [61]. As well known, many chemicals which are used in fabricating metal electrodes can cause denaturation of the non-carbon materials of sensors [62-65]. Moreover, physical processes such as etching, baking, and ultra violet (UV)-light irradiation often corrupt the material structure. These external factors can change the inherent properties of the non-carbon materials, resulting in adverse effects on sensor performance. However, carbon materials such as CNT, graphene, and graphene derivate (i.e., graphene oxide and reduced graphene oxide) are chemically/physically stable, which is sufficient to endure harsh environments (e.g., strong acidic/alkali condition, very high temperature, high-pressure, high-energy light, etc.) during the fabrication process [51, 66, 67]. Moreover, carbon materials have a number of advantages for detecting NO2 gas. Theoretically, oxygen compound molecule species adsorb on p-type carbon nanomaterials such as CNT and reduced graphene oxide (rGO), and attract electrons from the conduction band [68, 69]. In terms of NO2 molecules, it acts as an electron-accepter that induces an increase in the

electrical conductance [70, 71]. On the other hand, electron-donors such as NH3, CO, H2S, acetone, ethanol, etc. cause the electrical conductance on the ptype semiconductor to decrease. Therefore, the p-type semiconducting carbon nanomaterial-based electronic gas sensor can distinguish the NO2 gas (i.e., electron-acceptor) from other gases (i.e., electron-donor). Also, it is well known that the p-type semiconducting carbon nanomaterial can capture the NO2 gas molecules better than other electron-acceptor gases (e.g., NO, O2, H2O, CO2). Accordingly, carbon nanomaterials are very suitable for detecting the NO2 gas by measuring the changes in the electrical conductance. Specifically, carbon nanomaterials have a high carrier mobility and low signal-to-noise ratio owing to their semiconductor properties, and they can be extremely sensitive toward changes in their local environment [72-74]. In accordance with the operating mechanism for the detection of NO2 molecules by a sensing platform, many techniques have been advanced to improve the efficiencies of gas sensors, such as improvements of the response/recovery time, sensitivity, selectivity, reproducibility, and even the flexibility and robustness of sensing devices. In this review, we address the advanced techniques for gas sensors based on carbon nanomaterials (i.e., CNT and rGO). Prior to discussing carbon nanomaterial-based NO2 gas sensors in detail, we examine the configuration and mechanistic principles of gas sensors based on changes in electrical signals. We then scrutinize advanced techniques for doping nanomaterials, such as the introduction of metal or metallic NPs to CNTs or rGO. These techniques contribute to improving the response/recovery time, sensitivity, or selectivity of such materials to NO2 gas. To further enhance the efficiencies of a sensing device, including response time, recovery time, sensitivity, selectivity, repeatability, robustness, and flexibility, the dimensions of the nanomaterial composite used to adsorb the target gas can be changed from a wired structure (i.e., one-dimensional (1D)) or a flat (i.e., two-dimensional (2D)) structure to a threedimensional (3D) structure. In other words, devices are constructed using carbon nanomaterials composited with other nanomaterials, with repeated stacking of the same unit structure. The carbon nanomaterial-based NO2 gas sensors with various sensing efficiencies are summarized in Table 1. The following section reviews the configuration and mechanism of CNT-based gas sensors.

2

One-dimensional (1D) material: Carbon nanotube (CNT)

CNT is cylindrical carbon nanomaterial that can be classified as single-walled CNTs (SWCNTs) or multi-walled CNTs (MWCNTs) according to the number of layers in the tube wall. CNT has unique mechanical stiffness, strength, electrical properties, and high thermal conductivity [75, 76]. In particular, CNT exhibits high conductivity owing to an asymmetrical distribution of electron clouds, which provides rich π-electron conjugation along the CNT walls [77, 78]. Because of these outstanding electrical properties, CNT has been used to detect NO2 gas [79-83].

2.1

Configuration and mechanism of CNT-based gas sensors

Kong et al. reported NO2 gas sensing using SWCNTs at room temperature [20]. A single SWCNT is laid on a SiO2/Si substrate, and two metal (Au) electrodes are connected at each end of a SWCNT (Fig. 1a). As shown by the I-V curves, the conductance of the p-type SWCNT is increased after NO2 gas exposure (Fig. 1b). NO2 is a strong oxidizer with an unpaired electron, which acts as an electron-acceptor during electron transfer to the p-type SWCNT. Therefore, the conductance of the SWCNT increases sharply by about three orders of magnitude after exposure to 200 ppm of NO2 for 10 min (Fig. 1c). As a concentration test, the SWCNT was exposed to 2-20 ppm of NO2 gas. At the lowest concentration of NO2 gas, the lowest conductance is measured for the SWCNT (Fig. 1d). Interestingly, the SWCNT has a longer response time at this low concentration of NO2 gas than that at 200 ppm. This difference may be attributed to the time required for adsorption of NO2 gas molecules on the SWCNT. In this work, the limit of detection (LOD) of the SWCNT for NO2 gas is 2 ppm.

Li et al. reported that a nanomesh or network of SWCNTs on interdigitated electrodes (IDEs) provides a large enough density of sites for the adsorption of NO2 gas molecules (Fig. 2a) [84]. The SEM image shows that SWCNTs form a nanomesh or network on the interdigitated electrodes (IDEs (Fig. 2b). The IDE configuration enables effective electric contact between SWCNTs and the electrodes over large areas, which can provide good accessibility for gas molecules to all SWCNTs. Indeed, the nanomesh SWCNT-based gas sensor detects 6-100 ppm of NO2 gas with a LOD of 44 ppb. Despite the high sensitivity, the recovery time of this sensor is very long (10 h) owing to the strong binding affinity of NO2 gas molecules with SWCNTs. Conductance recovery is an important factor that should be considered in addition to the sensitivity of the NO2 gas sensor. To reduce the recovery time, a high operating temperature or UV light is required. Kong et al. used purging gas to observe the conductance recovery after exposure to NO2 gas. The conductance of the SWCNT recovered slowly, taking approximately 12 h, which is attributed to the strong binding affinity between the SWCNT and adsorbed NO2 molecules. In contrast, the recovery time of the SWCNT is reduced to 1 h at a high operating temperature (200°C). The reduced recovery time is due to a thermal energy-driven faster desorption for removal of NO2 gas molecules from the sensing platform [20]. Li et al. attempted another method for promoting the recovery rate using UV illumination of the sensing platform under purging gas, which results in the signal returning to the initial level within a short period of time (~10 min) [84]. Moreover, the recovery efficiency is greater under UV light than without UV light. This improvement is attributed to a decrease of the desorption-energy barrier by UV-light illumination, enabling the NO2 molecules to be easily desorbed from the SWCNT (sensing platform). Although the recovery rate improves, the recovery of the conductance signal to the initial state is not achieved by either a high operating temperature or UV-light illumination. Above all, recovery is the most problematic process for such gas sensors. Therefore, dopants or nanomaterials have been introduced to CNTs to improve the recovery efficiency.

2.2

Doping the dopant on CNT

A pristine CNT exhibits low sensitivity or response signals for many pollutant gases such as NO2, CO or NH3 [85]. Therefore, dopants or many metal nanoparticles have been introduced to CNTs to enhance their sensing performance such as response signal, recovery time and operation temperature [86]. Adjizian et al. showed the sensing performances with a dopant (i.e., boron and nitrogen) doped MWCNT to NO2 gas at room temperature [87]. Boron (B) or nitrogen (N) doped MWCNTs has improved electrical and physical properties. As results, N-doped MWCNT shows significantly enhanced response that enables the detection of low concentration NO2 (50 ppb) with complete recovery to initial state at room temperature. Moreover, the response signals linearly increase as the concentration of the gas was increased (0.05-1 ppm). This is attributed to the high binding energy which causes rapid charge transfer between NO2 gas molecules and N-doped MWCNT. Adjizian et al. also reported that NO2 molecules can aggressively bind to B-doped MWCNT rather than to pristine MWCNT. However, B-doped MWCNT has poor sensing efficiency to the NO2 gas. Compared to the N-doped MWCNT, B-doped MWCNT showed low sensitivity in detecting NO2 gas and insufficient signal recovery. This is because of the oxidation of boron dopants during the doping process, which often inhibits the adsorption of NO2 gas molecules to the B-doped MWCNT [88].

2.3

CNT-based nanocomposite materials

To improve the recovery efficiency of CNT-based gas sensors, metal NPs such as AuNPs [82, 89-91], PdNPs [90, 92] and PtNPs [50, 91, 92] have been introduced to CNTs to form composite materials. Dilonardo et al. reported the use of AuNP- or PdNP-decorated MWCNT composite materials for recovering the response signal at an optimized operating temperature [90]. AuNPs (12 nm) and PdNPs (5 nm) are well dispersed on MWCNTs through an electrophoretic process. The SEM image of the AuNP-MWCNT composite material shows that the AuNPs are loaded on the MWCNTs with an appropriate Au content (0.3

at%) (Fig. 3a). The bar graph in Fig. 3b shows that the response signal is best recovered by the AuNP-MWCNT composite at an operating temperature of 150°C, which is consistent with a previous work in which the surface of CNT was cleaned at 150°C [89]. A high operating temperature (>400°C) reduces the catalytic properties of metal NPs, which tend to aggregate on a large sized of agglomerate. Accordingly, the catalytic properties of the metal NP-decorated MWCNT can also be denatured at the high temperature. The reduced catalytic properties are involved in the reduction of active sites where NO2 gas molecules can be adsorbed. As a result, the sensitivity becomes lower. At a low operating temperature (i.e., room temperature), although the catalytic properties of the metal nanoparticle-decorated MWCNT are retained, the recovery efficiency could become worse. At room temperature, the desorption of the NO2 gas molecules from the metal nanoparticle-decorated MWCNT is difficult without UV-light; the response signal does not recover to the initial state. This situation results in poor reproducibility [93]. Dilonardo et al. found that a temperature range of 100-150°C is suitable for desorbing the NO2 gas molecules from the active sites, whereby the response signal is perfectly recovered to the initial state within an hour. At an operating temperature of 150°C, the AuNP-MWCNT composite shows better reproducibility at 10 ppm and fast response/recovery at all concentrations. Owing to its good recovery to the initial state, the conductance of this sensor changed rapidly with different concentrations of the NO2 gas. The composite material offers higher sensitivity and signal response to NO2 gas than pristine MWCNTs. Resistance curves (ΔR/R0) indicate that MWCNTs decorated with 0.3 at% of AuNPs exhibit the highest response signals toward the various concentrations of NO2 gas with high sensitivity (0.2 ppm). In the case of MWCNTs decorated with PdNPs (1.5 at%) (Fig. 3c), NO2 gas detection was achieved with high efficiencies at a lower operating temperature than the AuNP-MWCNT composite. The bar graph shows that the best recovery efficiency of the PdNP-MWCNT composite occurs at an operating temperature of 100°C (Fig. 3d). Moreover, the best sensing performance of PdNP-MWCNT was in the range of 0.2-1 ppm, showing high response signals with using 1.5 at% of PdNPs rather than 0.3 at% of PdNPs. As such, pristine CNT or CNT composites exhibit excellent performance for NO2 gas detection. However, CNT often suffers from small active areas for molecular interactions, and graphene is considered a promising candidate to address this issue.

3

Two-dimensional (2D) material: Reduced graphene oxide (rGO)

Pristine graphene is a well-known 2D carbon nanomaterial consisting of a single-atom-thick layer. It is composed of a honeycomb network structure of sp2hybridized carbon atoms [94, 95]. This structure offers unique optical, mechanical, and electrical properties, including high strength, thermal conductivity, flexibility, and biocompatibility [96-100]. Among these properties, its high electron mobility at room temperature (2.5 × 105 cm2 V-1 s-1) [101], high thermal conductivity (>3,000 W mK-1) [102], complete impermeability to gas molecules, and ability to sustain extremely high densities of electric current (1 million times higher than the ability of copper) make graphene a strong candidate for electrical gas sensors [72, 103, 104]. Despite the outstanding electrical properties of graphene, it is difficult to construct a large-area graphene sheet for detecting NO2 gas. Thus, reduced graphene oxide (rGO), which has the same sp2-structure as pristine graphene, has been introduced to obtain large-area sheets with a single layer. RGO is produced by reducing graphene oxide (GO), a derivative of graphene with sp3-hybridized carbon atoms, which causes GO to have different properties from pristine graphene or rGO [56]. This structure leads to some difficulties in the large-quantity production of GO sheets, low sensing efficiencies, and poor adsorption and desorption of target gas molecules [105]. Above all, GO is electrically insulating, which makes it unsuitable as a gas sensor. Therefore, additional thermal or chemical reactions of GO sheets using various reduction agents are required to produce rGO [106-108]. Owing to its excellent properties, rGO has been developed for NO2 gas detection [109, 110].

3.1

Configuration and mechanism of rGO as a NO2 gas sensors

NO2 gas molecules are adsorbed on rGO, which induces electron transfer between the rGO sheet and the gas molecules [70, 111]. Typically, NO2 gas

molecules act as electron acceptors (electron-withdrawing) on p-type semiconducting rGO [69]. Therefore, the adsorption of NO2 leads to an increase of the hole concentration of rGO, which increases conductance [42, 66]. Through this mechanism, NO2 gas detection can be achieved by measuring the conductance change of rGO (sensing platform). Lu et al. reported that GO sheets partially reduced by low-temperature annealing exhibit high sensitivity for NO2 gas detection [106]. To prepare the rGO sheets, the following process was used. First, GO sheets were laid between Au IDEs (Fig. 4a). GO sheets appear to be electrically insulating at room temperature, as indicated by curve A (Fig. 4b), which means that the presence of epoxide groups, hydroxyl groups, and carboxylic groups leads to the existence of extensive sp3-hybridized carbon atoms. Then, GO is reduced by annealing in Ar gas at atmospheric pressure at a low temperature to produce a semiconducting material (i.e., rGO) for detecting NO2 gas molecules. As shown in Fig. 4b, annealing in Ar gas (curve B, 100°C and 200°C, each for an hour; and curve C, 300°C for an hour) results in partially rGO sheets that are more conductive than GO. In addition, the conductance shown in curve C corresponds to that of a p-type semiconductor (inset, Fig. 4b). Partially rGO shows a high response to NO2 gas that can be explained by its many sp2-hybridized carbon atoms that act as active sites for the adsorption of NO2 gas molecules. NO2 gas molecules are electron-acceptors and strong oxidizers that enrich the hole concentration of rGO, thus increasing the conductance of the rGO. Partially rGO shows a dynamic response with exposure to NO2. The electrical signal increases on exposure to NO2 gas and stops increasing when the gas is removed. On exposure to 100 ppm NO2, the partially rGO annealed at 300°C shows higher sensitivity than partially rGOs produced under other conditions (i.e., annealed at 200°C) because more rGO regions are produced at 300°C (Fig. 4c). Although partially annealed rGO can capture NO2 gas molecules, these sheets often suffer from poor sensitivity, selectivity, and recovery efficiency. Accordingly, the rGO sheets have been modified by doping the dopants.

3.2

Doping the dopant on rGO

The sensitivity and selectivity can be enhanced by doping the dopant on pristine rGO sheets. Boron (B), nitrogen (N) or sulfur (S) doped rGO sheets alter the electrical properties and chemical reactivity of the sheets by disturbing the SP2-hybridized structure [112]. The dopants (e.g., B, N, and S) function as active sites for gas molecules. Boron atoms induce pristine graphene to have a p-type semiconducting behavior or enhance the electrical conductance to rGO. Therefore, NO2 gas molecules can strongly react with B-doped rGO sheets, and B-doped rGO sheets adsorb more NO2 gas molecules than pristine rGO sheets. Boron atoms augment the electrical properties of rGO. Lv et al. applied B-doped rGO sheets for detecting NO2 and NH3 gas molecules. It is noted that the numerous gas molecules on the sheets enhanced the sensitivity and response signals; B-doped rGO could detect even 1 ppb of NO2 gas, while the rGO sensor measured over 8 ppb of the gas. Moreover, the response signal intensity of B-doped rGO is 27 times more enhanced than that of rGO. However, the recovery efficiency is reduced. Because of the strong binding interactions between the NO2 molecules and B-doped rGO sheet, the desorption of gas molecules is difficult without UV-light or high operating temperature. N-doped rGO sheet also provides advanced efficiencies for the gas sensor regarding sensitivity, response time and selectivity in comparison to rGO sheet. Nitrogen atoms have been doped on rGO sheets (i.e., N-doped rGO) to improve the sensitivity and response time at room temperature. Shaik et al. exposed 5 ppm of NO2 gas to N-doped rGO for 10 min, and compared the sensing performance with rGO at room temperature [113]. The N-doped rGO exhibits 41.85% higher response signal than rGO, which is attributed to the greater number of active sites for the gas molecules adsorption in N-doped rGO than rGO. However, due to the high binding energy between the gas molecules and N-doped rGO, the response signals are not recovered to initial state. To accelerate the recovery time, Shaik et al. irradiated UV-light which renders the binding energy weak. The N-doped rGO detects NO2 gas in a wide range of NO2 concentration (2.5-100 ppm), and the limit of detection (LOD) is 0.12 ppm (Fig. 5a). Moreover, N-doped rGO shows superior selectivity to the NO2 gas (Fig. 5b). Interestingly, Wang et al. attempted to introduce a dopant (i.e., nitrogen) on a metallic oxide nanomaterial (i.e., SnO2NP) composite based on rGO [114]. SnO2NP was fabricated with N-doped rGO, resulting in the formation of a SnO2NP/N-rGO composite. The SnO2NP/N-rGO composite exhibited a faster

response/recovery time than the SnO2NP-rGO composite or rGO sheet at room temperature. The SnO2NP-rGO composite based sensing performance is discussed in more detail in Part 3.4. Briefly, compared to SnO2NP-rGO composite or rGO sheet, the SnO2NP/N-rGO response to 5 ppm of the NO2 gas in 45 s, which is recovered within 168 s at room temperature (without UV-light or high operating temperature) (Fig. 5c). This short time is due to the metallic oxide material (i.e., SnO2NP) that offers more active sites for the adsorption of NO2 gas molecules. For the SnO2NP/N-rGO composite-based sensor, the response signal is recovered to its initial state after the NO2 gas is switched off, and it could perform perfectly with different gas concentrations (1-10 ppm) (Fig. 5d). Moreover, the SnO2NP/N-rGO composite obviously detects NO2 gas among various gases with high selectivity. In summary, the SnO2NP/N-rGO composite shows an advanced detection of NO2 gas with fast response and recovery rate at room temperature. Guo et al. developed the S-doped rGO and exposed 10 ppm of the NO2 gas to the composite at different operating temperatures (70-150°C) [115]. The results showed that, while the response (ΔR/R0) of S-doped rGO is the most improved at 70°C, the sensor needs a long time to recover the signal to the base line at that temperature. Interestingly, while the response signal is recovered to the base line regardless of the gas concentration (1-10 ppm) within 20 min at 150°C, the response signal is weaker becomes worse than at 70°C. Taken together, the N-doped rGO is the most advanced NO2 gas sensor among the three gas sensors in terms of the response/recovery rate, sensitivity, and selectivity. Moreover, N-doped rGO displayed a perfect recovery performance regardless of the gas concentration at room temperature. Besides of dopants, chemical groups or metal/metallic oxide NPs have also been introduced to rGO sheet for fabricating sensors that can show improved sensing efficiency at room temperature [116].

3.3

Chemical functionalization of rGO

Various chemical groups, such as sulfonic group (–SO3H) [117, 118], ethylenediamine (EDA) [119], caesium [120] and ozone [121], have been introduced to graphene sheets to act as electrochemical sensors, biological sensors, chemiresistors, etc. [122, 123]. Chemical functionalization is one of the most advanced methods for improving the properties of gas sensors, such as response/recovery time, recovery efficiency, selectivity, and sensitivity. Yuan et al. showed that the sensitivity of chemically modified rGO sheets to NO2 with sulfonate functional groups (-S) and ethylenediamine groups (-EDA) is 4-16 times greater than that of pristine rGO sheet [119]. Moreover, both functional groups exhibit improved reversibility and selectivity. Atomic force microscopy (AFM) images indicate that rGO sheet and chemically functioned rGO sheets (i.e., S-rGO and EDA-rGO) are not only tangled but also well dispersed in water. These samples have thicknesses of 0.9-1.1 nm, similar to the atomic thickness of single-layer graphene. The conductance of rGO, S-rGO, and EDArGO samples before exposure to NO2, measured using an I-V meter, are shown in Fig. 6a. The I-V curves of these three samples exhibit linear ohmic behavior, which shows that the electrical contact plays a negligible role in the sensing process. The response curves of the three samples to NO2 gas (50 ppm) are compared by recording the dynamic response signal for 10 min at a bias of 1 V. The conductances of S-rGO sheet (24.7) and EDA-rGO sheet (6.5) are 16.4 and 4.3 times higher than that of rGO sheet (1.5), respectively. Moreover, although the recovery rate is slow, chemically modified rGO sheets (i.e., SrGO and EDA-rGO) show good recovery efficiency after stopping exposure to the NO2 gas. It should be noted that the response signals of rGO sheet and EDA-rGO sheet are perfectly recovered within 10 min. However, the response of the S-rGO sheet was not saturated during the same period. The conductance of the S-rGO sheet increases about 70 times after exposure to 50 ppm NO2 for 2.4 h. This result indicates that S-rGO sheet has strong ability to adsorb NO2 molecules, thus enhancing the response signal. The thickness of the sheets can strongly influence the performance of the gas sensor. Yuan et al. utilized S-rGO sheet to confirm the effect of the thickness

of the S-rGO sheet on the response signal. The response signals of S-rGO sheet with a thickness of 1–6 nm is 4.3 times higher than that with a thickness of 50 nm, and 2.3 times higher than that with a thickness of 10 nm. This result shows that thinner sheets have more active sites where NO2 gas molecules can be adsorbed. Further, in concentration and selectivity tests, S-rGO sheet and EDA-rGO sheet show linear responses to the NO2 gas concentrations, with higher concentrations of NO2 gas corresponding to higher response signals. The sensing signal of S-rGO sheets increases linearly with an NO2 concentration in the range of 5 to 45 ppm (Fig. 6b), while the EDA-rGO sheets display a linear response in the range of various concentrations (1-10 ppm) (Fig. 6c). Interestingly, the LOD of the EDA-rGO sheet is lower (0.07 ppm) than that of the S-rGO sheet (3.6 ppm). However, the response signal of the S-rGO sheet is much higher than that of the EDA-rGO sheet at the same concentration of gas. Among the various gases, NO2 can be adsorbed selectively by S-rGO sheet (Fig. 6d). Although a slight response signal is detected on exposure to NH3 gas, the signals can be distinguished owing to the molecular mechanisms of NO2 (acceptor) and NH3 (donor). S-rGO sheet can detect the NO2 gas molecules selectively with a strong response and good recovery.

3.4

rGO-based nanocomposite materials

To improve the sensing efficiency of rGO-based gas sensors, composite materials have been fabricated using rGO and various nanomaterials such as metal or metal oxide NPs [124-126], peptides, and polymers [16, 127]. In this review, we focus on rGO sheets modified with metal NPs (i.e., Al, Au, and SnO2). In general, the combination of metal NPs and rGO increases the active sites for gas molecule adsorption and improves the properties of the gas sensors, such as response/recovery rate, recovery efficiency, sensitivity, robustness, and flexibility. For example, aluminum NPs (AlNPs) have been introduced onto rGO sheet to enhance the sensitivity, selectivity, robustness, and flexibility of gas-sensing devices [67]. The rGO sheet decorated with AlNPs detects NO2 gas selectively, exhibiting higher sensitivity than rGO. The sensing mechanism of the AlNP-modified rGO sensor involves depletion of the hole carriers in the

rGO sheet by the AlNPs, which improves the adsorption of the NO2 gas molecule on the sheet. Hole depletion at the interface facilitates electron transfer from a graphene sheet to NO2 gas molecules. AlNPs are arrayed between Au/Ti IDEs on a hard Si/SiO2 substrate. While the rGO sheet has some wrinkles, the nanoscale morphology depends on the presence of AlNPs. The response of AlNP-rGO to 1.2 ppm of NO2 gas improves by about 200% (1.44 to 2.89) compared with that of rGO. Surprisingly, the response of AlNP-rGO to 100 ppm of NH3 is only about 96% of that of the rGO sheet (1.94 to 1.87). This behavior is attributed to the properties of NH3 molecules, which act as electron donors on p-type semiconducting materials [128, 129]. Therefore, the selectivity for NO2 gas over NH3 gas is effectively improved by the introduction of AlNPs. Moreover, when rGO and AlNP-rGO are introduced to a flexible substrate (e.g., polyimide), the sensors acquire high flexibility. The sensing performance remains consistent for 104 bending cycles, after which AlNP-rGO and rGO undergo irrevocable deformation with cracks formed in the grain boundaries between the graphene domains. The stress-induced permanent deformation at the grain boundaries and macroscopic cracks might increase the resistance of the flexible graphene device. Although the response signals for NO2 gas exposure decrease slightly after the bending cycles, the response signal of AlNP-rGO is enhanced relative to that of rGO, similar to the response behavior before the bending cycles. Thus, the highly sensitive and reliable flexible device based on AlNP-rGO represents a simple route toward practical gassensing applications. As mentioned above, to accelerate the recovery time for NO2 desorption from the gas-sensing platform, UV-light irradiation or a high operating temperature can be introduced. Recently, various metal NPs have been introduced to rGO sheets at low temperatures (at least 50°C). Zhang et al. reported a NO2 gas sensor that can be operated at low temperatures [130]. The gold NP (AuNP)-rGO composite material showed high sensitivity, a rapid response/recovery time, and reproducibility. They introduced a RuO2 layer to the gas-sensing platform for heating at 50°C to decrease the recovery time. The TEM image of AuNPrGO reveals that the AuNPs (10 nm) are uniformly distributed on the rGO sheets (Fig. 7a). Compared with rGO, AuNP-rGO exhibits a reduced response time (from 798 to 132 s) and a reduced recovery time (from 7312 to 386 s) when heated at 50°C (Fig. 7b). The main problem with rGO is that an operating

temperature higher than 50 °C is required to accelerate the response/recovery time. At 50°C, AuNP-rGO shows a linear response to NO2 gas concentration (0.5, 1, 2, and 5 ppm) (Fig. 7c). Moreover, the curve in Fig. 7c shows that AuNPrGO recovers to the initial state in a short period of time after the target gas is removed. Further, AuNP-rGO can detect low concentrations of NO2 gas with high sensitivity (0.5 ppm). The effects of AuNPs are as follows. First, AuNPs contribute significantly to improving the conductivity of rGO, leading to better sensing behavior. Second, the NO2 gas was distributed over the rGO sheets by AuNPs acting as a catalyst, with improved adsorption and desorption of NO2 gas molecules on AuNP surfaces owing to the highly catalytic or conductive nature of Au. Thus, the number of electrons attracted to NO2 (electron acceptor) increases. Third, electron transfer from the defect states (sp3-hybridized carbons) to AuNPs not only increases the resonant electron density but also creates energetic electrons in high-energy states. The role of AuNPs as electron mediators further facilitates electron transfer from rGO to NO2 molecules, as given in equations (1) and (2). NO2 + e− → NO− 2

(1)

− NO2 + O− 2 → NO + O2

(2)

Therefore, the AuNPs significantly decrease the electron density of the rGO sheet. As an important property of gas-sensing devices, the AuNP-rGO device shows selectivity for NO2 gas detection (Fig. 7d). Zhang et al. reported that tin dioxide NPs (SnO2NPs, 10 nm) decorated on rGO sheets (SnO2NP-rGO) could be used to detect NO2 gas, exhibiting a short response/recovery time at a low operating temperature (50°C) [131]. The performance of this gas sensor (e.g., SnO2NP-rGO) shows significantly improved response/recovery time, selectivity, and reproducibility. As shown in the TEM image (Fig. 8a), the wrinkles are reduced on the SnO2NP-rGO sheet than on the rGO sheet. The n-type semiconducting SnO2NPs attract electrons from the rGO sheet, significantly increasing the active sites for NO2 gas molecule adsorption. The SnO2NP-rGO device detects 5 ppm of NO2 gas with a faster response time (135 s) and shorter recovery time (200 s) than the rGO sheet (Fig.

8b). Interestingly, SnO2NP-rGO displays a faster recovery than the AuNP-rGO composite material (386 s), as shown in Fig. 7b. On exposure to various concentrations of NO2 gas, the SnO2NP-rGO device has a fast response and recovery to initial state with a resistance to change corresponding to the relative concentration (Fig. 8c). It is worth nothing that the sensitivity of the SnO2NP-rGO composite is 0.5 ppm. Further, the composite responds selectively to 5 ppm of NO2 gas among the various gases at the same concentration (Fig. 8d). Although rGO sheets can detect NO2 gas selectively, the response is lower (1.13) than that of SnO2NP-rGO (3.31). The introduction of SnO2NPs to rGO sheets significantly improves the sensing efficiency of the rGO sheets for detecting NO2 gas. Zhang et al. also introduced AuNP-SnO2NP-rGO composite to improve the gas sensing performance such as response and recovery rate (Fig. 9a) [126]. In particular, at 5 ppm of the NO2 gas, the response signal (i.e., resistance change) is achieved in ~90% of total resistance change within 19 s (Fig. 9b). This response time (19 s) indicates that the AuNP-SnO2NP-rGO composite is significantly more efficient than the pristine rGO (798 s) or other composites such as AuNP-rGO (132 s) and SnO2NP-rGO (135 s). This efficiency may be attributed to the enhanced electrical conductance with the introduction of AuNP and SnO2NP to rGO sheets. In addition, AuNP as a metal nanoparticle plays a role in the catalytic platform on the composites. Moreover, the response signal is recovered to the initial state within 20 s after the NO2 gas is switched off. This is a very short time compared to rGO (8319 s), AuNP-rGO (386 s) and SnO2NP-rGO (200 s) to 5 ppm of NO2 gas exposure at 50°C. For the sensitivity and selectivity test, the AuNP-SnO2NP-rGO composite material-based NO2 gas sensor exhibited similar results to those of the conventional AuNP-rGO [130] and SnO2NP-rGO [131] composite-based sensors mentioned above. Specifically, the response of AuNP-SnO2NP-rGO composite showed a linear increase in the range of 5-50 ppm (Fig. 9c). In addition, no significant difference was observed among them regarding selectivity. Interestingly, the minimum sensing concentration of NO2 gas was not advanced compared to the two composites (i.e., AuNP-rGO and SnO2NP-rGO). In summary, it is demonstrated that the AuNP-SnO2NP-rGO composite-based gas sensor improved in terms of response and recovery efficiency.

Liu et al. show an improved gas sensing performance with the SnO2NP-S-rGO composite [118]. To form the composite, SnO2NPs are fabricated with sulfonated (S) rGO. The composite exhibits high response signal as well as short response/recovery time at room temperature, which is compared to two previous works, S-rGO composite [119] and SnO2NP-rGO composite [131], both of which have long response or recovery time to the NO2 gas. Especially, SnO2NP-S-rGO composite responds to 5 ppm of NO2 gas within 40 s and recovers to the initial state within 357 s without UV-light or high operating temperature. In contrast, SnO2NP-rGO composite requires 50°C to recover the response signal to the initial state after the NO2 gas has been switched off. Moreover, the SnO2NP-S-rGO composite exhibits more enhanced response signals than the conventional composites (i.e., S-rGO or SnO2NP-rGO) to the NO2 gas. The signal enhancement is due to the sulfonic (S-) chemical group on the rGO sheet and n-type semiconducting SnO2NP. Specifically, the sulfonic groups on the rGO sheets could provoke dispersion between the rGO sheets, and the S-rGO composite offers higher conductivity than pristine rGO sheet. The role of SnO2NP is to form p-n junctions between S-rGO and SnO2NP, thereby enhancing the sensing performances to the NO2 gas compared to pristine rGO sheet. In conclusion, it is verified that the SnO2NP-S-rGO composite-based NO2 gas sensors provide fast response/recovery rate and enhanced response signal at room temperature. Thus far, we have examined various NP-decorated rGO composite materials for detecting NO2 gas. Although the response/recovery time and sensitivity of these devices improve considerably compared with unmodified rGO materials, the operating temperature required to desorb NO2 gas molecules from the rGO sheet remains a problem. To address this issue, Liu et al. reported a SnO2NP-CNT-rGO composite material for detecting NO2 gas that can be operated at room temperature (Fig. 10) [132]. The introduction of CNTs to the rGO sheet can prevent restacking or wrinkling of the rGO sheet. Therefore, the number of adsorption sites for NO2 gas in SnO2NP-CNT-rGO composite is increased compared with that in rGO. Further, the electron-transfer rate for NO2 sensing improves because the conductivity of CNTs is superior to that of rGO [58]. Therefore, the CNT-rGO composite material can detect NO2 gas at a low temperature. The introduction of n-type semiconducting SnO2NPs to the CNT-rGO composite allows tuning of both the active sites for adsorption and

desorption of NO2 gas and the semiconductor properties owing to the formation of a p-n heterojunction structure between SnO2NP (n-type) and rGO (p-type). This p-n heterojunction allows electrons to be transferred between SnO2NPs and NO2 gas molecules, to achieve short response/recovery times. Although the SnO2NP-rGO composite material shows faster response and recovery rates than rGO sheets, the response to 5 ppm NO2 and recovery at room temperature are still slow (288 and 619 s, respectively) (Fig. 10a). It should be noted that the SnO2NP-rGO composite material exhibits very fast performance for NO2 gas detection without a high operating temperature. By introducing MWCNTs to the composite material (SnO2NP-CNT-rGO), a very short response time (8 s) and a fast recovery rate (77 s) to 5 ppm of the NO2are achieved at room temperature (Fig. 10b). Further, the resistance signal is recovered to the initial state when the target gas is removed. Examination of the response signal of the SnO2NP-CNT-rGO composite material to various concentrations of NO2 gas reveals that the response to NO2 gas increases rapidly with increasing concentrations of NO2 gas from 1 to 10 ppm, but the response increases more slowly at higher NO2 gas concentrations (10-100 ppm) at room temperature (Fig. 10c). Moreover, the SnO2NP-CNT-rGO composite material can detect low concentrations of NO2 gas (1 ppm) with a response signal of 1.6. Further, the response to 5 ppm NO2 is 2.53, whereas the responses to 5 ppm Cl2, NH3, and CO are less than 1.20 (Fig. 10d). Thus, the SnO2NP-CNT-rGO composite material displays good selectivity as an NO2 gas sensor without requiring a high operating temperature. We analyzed NO2 gas-sensing research based on 1D carbon material (CNT) and 2D carbon material (rGO). The above-described advanced techniques have facilitated considerable improvements in sensor properties such as response and recovery time, sensitivity, rigidity, device flexibility, and NO2 selectivity. In particular, from the perspective of enhancing the sensing efficiency, the improvement of target-gas adsorption on the sensing material is the most important factor. To achieve high response signals in short periods of time, the active sites for target gas molecules should be increased. Therefore, despite the high conductivity of CNT, rGO is a more appropriate material for NO2 sensors. Further improvements are achieved by the introduction of metal NPs to carbon materials to make composite materials.

3.5

Three-dimensional (3D)-like material: Stacked layers of rGO

3D carbon-based gas sensing materials have been developed to physically extend their active sites. Gas sensing has been achieved with 3D-structured devices with or without nanomaterials [133-135]. The first device type is formed from a 3D graphene foam network without nanomaterials [136-139], and the second is a stacked graphene layer with metal NPs or CNT [140]. In this review, we focus on stacked graphene layer structures that can detect NO2 gas. 3D structures offer remarkable advances for gas-sensing devices owing to their large specific areas (active sites) for target gas molecules. Various metallic NPs (e.g., Au, Pt, Pd, and SnO2) can be deposited on carbon materials, such as CNT and graphene, to form a composite material, as introduced in the previous sections. These composite materials exhibit improved sensor efficiency, including sensitivity, response/recovery time, recovery to the initial state, and flexibility, compared with CNT- or rGO-based NO2 gas sensors. Recently, Chen et al. reported a 3D-structured gas sensor composed of stacked graphene layers that incorporate metal NPs, as shown in Fig. 11a [140]. First, rGO sheets are chemically functionalized with naphthalene-1-sulfonic acid (NA) using π– π interactions to form NA-rGO sheets that have enhanced concentrations of holes as carriers. The electron-withdrawing ability of NA results in improved sensitivity for electron-acceptor gas molecules (i.e., NO2). NO2 gas molecules are adsorbed on lone pair electrons at electron-rich sites, such as S or O atoms in SO3-. Then, silver NPs (AgNPs) are introduced to the NA-rGO sheets through electrostatic interactions. The formation of the AgNP-NA-rGO composite material increases the specific area of the active sites, thus increasing the ability of the material to capture NO2 gas molecules. The AgNPs also play an important role in the isolation of graphene layers, allowing the formation of a layer-by-layer structure (i.e., 3D structure). This structure permits penetration by NO2 gas molecules, and reaction with the interlayers results in a significant improvement in sensitivity. In addition, the layer-by-layer structure provides sufficient space to realize gas desorption using pure air, which causes good reversibility. AgNP-NA-rGO composite materials are easily dispersed in solution

because the hydrophilicity of the sulfophenyl groups (-SO3H) improves the water solubility. The SEM image of the multilayer AgNP-NA-rGO material (Fig. 11b) shows that AgNPs are well dispersed on the NA-rGO surface; the inset image in Fig. 11b confirms the 3D structure of the composite. With such characteristics, the AgNP-NA-rGO composite exhibits improved sensitivity for 1-10 ppm NO2 compared with conventional NO2 gas-sensing devices. The sensitivity of AgNP-NA-rGO is two times better than that of bare rGO. Moreover, the signal increases as the concentration of NO2 gas increases. The AgNPNA-rGO composite shows an outstanding linear detection in the range of the NO2 gas concentration (1-10 ppm) and the sensitivity is measured as approximately 0.13 ppm-1 (Fig. 11c). Further, the dynamic curve shows that the initial state is recovered. Finally, because of the functional groups of NA, the selectivity of AgNP-NA-rGO is enhanced for NO2 gas in comparison with electron-donor gas molecules such as acetone, ethanol, and NH3 (Fig. 11d).

4

Other carbon nanomaterials

In addition to the CNT and graphene, other carbon nanomaterials have been fabricated for NO2 gas sensors. For examples, such as carbon fiber (CF) and carbon black (CB) have been utilized, they have not been used as frequently as CNT or graphene. It may be due to the insufficient area where the gas molecules can be adsorbed. To overcome this obstacle, CF or CB has been blended with other nanomaterials such as polyaniline (PAni), nickel hydroxide, and polymer [141, 142] which can provide large active sites, thereby enhancing electrical conductance to detect the NO2 gas. Fonseca et al. introduced a conducting polymer (i.e., PAni) to CF [47]. The PAni in PAni-CF composite acts as a high conductivity material that becomes emeraldine salt in oxidation state. As the content ratio of PAni against CF increases, the electrical conductivity of the composite also increases. Accordingly, the sensitivity and the response rate of the gas sensor also improve. In the results, the electrical conductance of PAni-CF composite drastically changes with the adsorption of the NO2 gas. While Fonseca et al. did not quantify the recovery rate, they detected the NO2 gas (10-300 ppm) at room temperature, suggesting the possibility of the NO2 gas detection with PAni-CF composite.

Yun et al. utilized micro size fibers (i.e., cotton yarn and polyester yarn) which are covered with rGO [48]. Specifically, the rGO sheets were wrapped around the cotton yarn (rGO-CY) (Fig. 12a) and polyester yarn (rGO-PY) (Fig. 12b). In the SEM images, the numerous wrinkle and ripple patterns of rGO-CY and rGO-PY represent the rGO sheets which are coated on the surface of the yarns. The wrinkle and ripple patterns enlarge the active site for the gas molecules. Moreover, the patterns continuously exist on the entire yarn structure, which is beneficial for the extension of the active site compared to the flat surface where the rGO sheets are covered. Accordingly, the composites exhibit ultra-sensitivity, high response, and selectivity to the NO2 gas. The conductivity of rGO-CY and rGO-PY changes with exposure to the NO2 gas at room temperature; the LOD was 0.25 ppm. This study thus suggests practical applications for a wearable and flexible NO2 gas sensor. While CB is the least expensive and earliest nanosized material, it is limited in NO2 gas sensing because of the low binding capability of the gas molecules. Thus, CB has been modified by titanium dioxide (TiO2) [44] or α-type nickel hydroxide (α-Ni(OH)2) [45]. Specifically, Liou et al. reported TiO2-coated CB (TiO2-CB) for the detection of NO2 gas. To find the optimum condition for fabricating TiO2-CB, Liou et al. modified the content ratio of TiO2 for making a TiO2-CB composite and changed the operating temperature (i.e., 50-200°C). Liou et al. revealed that the sensitivity of the TiO2-CB composite is enhanced by increasing the quantity of TiO2 to CB (ratio=16:1), and the recovery signal became efficient at a high operating temperature (150°C). They also found that the response signal is perfectly recovered regardless of the concentration of the NO2 gas (1-100 ppm), suggesting the possibility of TiO2-CB for detecting the NO2 gas. Chu et al. designed a flower-like 3D composite which is structured by CB nanospheres and α-type nickel hydroxide (α-Ni(OH)2) nanosheets [45]. In specific, the 3D flower-like hierarchical structure is a α-Ni(OH)2-CB composite (Ni-CB) which provides a broad area of active sites for adsorbing the NO2 gas molecules. Ni-CB exhibits high sensitivity, fast response time (2 s), improved limit of detection (0.5 ppm) and an excellent repeatability at room temperature. It is attributed to the composite structure of the mesoporous nanosheet (α-Ni(OH)2) and high conductivity of CB. Fig. 12c shows that Ni-CB can detect the

different concentrations of the NO2 gas (0.5-100 ppm), and can recover the response signal to the initial state after the target gas has been switched off. Moreover, it can detect 100 ppm of the NO2 gas within 2 s, which is the most rapid NO2 gas detection. In addition, the selectivity of Ni-CB is exceptional (Fig. 12d).

Perspective and conclusions We holistically thoroughly examined gas sensors targeting NO2 based on carbon nanomaterials (i.e., CNT, rGO, carbon fiber and carbon black) and discussed the enhanced sensing performance achieved for chemically modified or NP-decorated carbon materials. These composite materials have been advanced for detecting toxic NO2 gas with improved sensing properties, such as fast response/recovery rate and good recovery efficiency, reproducibility, sensitivity, and selectivity. Moreover, the flexibility and robustness of such gas sensors are improved by using various nanomaterials (for composite materials) or sensor substrates. We also discussed the NO2 sensing efficiency between CNT and rGO. Although rGO is slightly less conductive than CNT, it has been utilized to develop gas sensors because of its large area of active sites (2D planar surface). The use of rGO sheets leads to high sensitivity and enables detection of low concentrations of NO2 gas compared with the same volume of CNTs. Recently, chemically modified rGO has been advanced for improving the selectivity to NO2 gas against other gases. NP-mediated or stacked rGO layers have been fabricated to detect the NO2 gas with focusing on enhanced sensitivity and recovery efficiency. Amusingly, the stacked rGO layers have advantages such as fast response/recovery rate, excellent sensitivity, and improved recovery efficiency at room temperature without UV-light irradiation. To improve the performance of stacked rGO layers, composites with various nanomaterials, such as CNTs, metal/metal oxide NPs, and nanowires, could be utilized for the gas-sensing device to detect NO2 gas. We anticipate that the carbon-based nanomaterial composites would exhibit enhanced sensing properties for NO2 detection. We expect that amorphous carbon materials could be utilized as low-cost and mass-produced materials for detecting NO2 gas. We believe that this review of the history of carbon material-based NO2 gas sensors

will be helpful for many researchers in the biosensor field, especially with regards to sensors of toxic gases and environmentally harmful volatile organic compounds. Beyond this, the knowledge can be extended to various medical applications, such as the examination of exhaled gas, which often includes NOx, from patients who suffer from lung [143, 144], breast [145], and ovarian cancers [146], as well as Alzheimer’s disease [147].

Acknowledgments This work was supported by the National Research Foundation (NRF) of Korea, funded by the Korean Government (MSIP) (grant No. NRF2016R1A2B4010269).

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Author Biography Sang Won Lee received his B.S. and Master’s degree (M.E.) in Biomedical Engineering from Yonsei University, Wonju in 2013 and 2015. He is currently doing his Ph.D. course in School of Biomedical Engineering at Korea University, Seoul, South Korea. His main research focuses on detecting toxic gas molecules using an amperometric method based on various carbon materials such as carbon nanotube, graphene, and amorphous carbon material.

Wonseok Lee is currently doing his Ph.D. course in Biomedical Engineering from Yonsei University, Wonju, South Korea. His research focused on formation and degradation of amyloid fibrils which is associated with neurodegenerative diseases such as Alzheimer’s and Parkinson's. He is also interested in development of new biomaterials for sensing toxic ions or molecules using optical, electrical, and mechanical sensors.

Yoochan Hong received B.S. and Ph.D. degrees from Department of Biomedical Engineering, Yonsei University, Korea in 2008 and 2015, respectively. He

was a postdoc fellow at Department of Radiology, Yonsei University College of Medicine. Now he is working for Korea Institute of Machinery and Materials (KIMM) as a senior researcher. His research focuses on synthesis and modification of various nanoparticles as well as molecular detection of biological/physical interactions using localized surface plasmon resonance phenomenon.

Gyudo Lee received his B.S. and Ph.D. degrees from Department of Biomedical Engineering, Yonsei University, Korea in 2008 and 2014, respectively. He completed his postdoc at Harvard University. He joined School of Biomedical Engineering, Korea University as a research professor. His main research interest focuses on the quantitative detection of biomolecular interactions including antigen-antibody binding, protein aggregation, and nanomaterial-based sensing of toxic molecules.

Dae Sung Yoon is a professor of Biomedical Engineering, Korea University, Seoul, South Korea. He received B.S. and Ph.D. from Department of Ceramic Engineering, Yonsei University in 1991 and from Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea in 1996, respectively. He completed his postdoctoral fellow at University of Pennsylvania in 2000. He worked for Samsung Electronics as a principal research scientist and for Nano-Bio Research Center, Korea Institute of Science and Technology (KIST) as a senior research scientist. Prior to joining Korea University, he was a professor of Biomedical Engineering, Yonsei University, and he also experienced as a visiting professor at Harvard Medical School. His research focuses on investigation of disease-related biomolecular interactions using atomic force microscopy, nanomechanical bioassay using microcantilever devices, synthesis of nano-biomaterials and composites, and their applications, biochemical and biophysical investigation of underlying principles of cancers and Alzheimer disease, and biomimetics for biomedical applications.

Figures and captions

Fig. 1. (a) Atomic force microscopy (AFM) image of a single-walled carbon nanotube (SWCNT) used for detecting NO2 gas. The diameter of the SWCNT is ~1.8 nm. (b) Changes in electrical conductance of a semiconducting SWCNT to the NO2 gas exposure. Current versus voltage curves recorded before and

after exposure to NO2 gas. (c) Conductance versus time in 200 ppm of the NO2 flow. (d) Data for different SWCNT samples in 20 and 2 ppm NO2 flows. The two curves have been shifted along the time axis for clarity. Figures reproduced with permission from Ref. [20], © 2000 Science.

Fig. 2. (a) Interdigitated electrodes (IDE). (b) SEM image of SWCNTs across the two gold electrodes. Figures reproduced with permission from Ref. [84], © 2000 American Chemical Society.

Fig. 3. (a) SEM image of multi-walled CNTs (MWCNTs) decorated with 0.3 at% AuNPs. (b) Mean sensitivity of pristine CNTs and AuNP-MWCNT composites (0.3 at% and 1.1 at%) toward NO2 gas at different operating temperatures (45-200°C). (c) SEM image of MWCNTs decorated with 1.5 at% PdNPs. (d) Mean sensitivity of pristine CNTs and PdNP-MWCNT composites (0.3 at% and 1.5 at%) to NO2 gas at different operating temperatures (45-200°C).

Figures reproduced with permission from Ref. [90], © 2017 Beilstein.

Fig. 4. (a) SEM image of a GO sheet bridging two neighboring Au fingers of an interdigitated electrode. Gases are detected by measuring the change in the current while applying a constant DC bias to the device. (b) Ids-Vds curves of the GO device. Curve A: without annealing; Curve B: successively annealed in Ar at 100 and 200°C (1 h each); Curve C: further annealed in Ar at 300°C (1 h). The inset shows the Ids-Vds curve (Vds = 0.01 V after 300°C annealing). (c) Response curves show that annealing at 300°C improved the sensitivity and response time of the sample but increased the recovery time compared with the behavior of the sample annealed at 200°C. Figures reproduced with permission from Ref. [106], © 2009 American Institute of Physics.

Fig. 5. (a) Response of N-doped rGO to the concentration of NO2 gas (2.5-100 ppm). (b) Selectivity of N-doped rGO to NO2 gas among various gases. Figures reproduced with permission from Ref. [113], © 2016 Royal Society of Chemistry. (c) Response-recovery curves to 5 ppm NO2 of the sensor based on SnO2NP/N-rGO composite. (d) Response and recovery curves of the sensor based on SnO2NP/N-rGO composite to the different NO2 concentrations of 1, 3, 5, and 10 ppm at room temperature. Figures reproduced with permission from Ref. [114], © 2017 Elsevier.

Fig. 6. (a) Current versus voltage curves of blank, rGO-, S-rGO-, and EDA-rGO-based sensors. (b) Response variation of the S-rGO-based sensor as a function of NO2 concentration (5-45 ppm). (c) Response variation of the EDA-rGO-based sensor as a function of NO2 concentration (1-30 ppm). (d) Responses of the S-rGO-based sensor to 50 ppm of NO2, NH3, H2O, and toluene. Figures reproduced with permission from Ref. [119], © 2013 John Wiley & Sons, Inc.

Fig. 7. (a) TEM image of the AuNP-rGO composite material (scale bar: 100 nm). (b) Response curve of AuNP-rGO composite on exposure to 5 ppm NO2 at 50°C. (c) Transient curves for dynamic sensing of 0.5-5 ppm NO2 by AuNP-rGO composite at 50°C. (d) Responses of AuNP-rGO composite to 5 ppm of various gases at 50°C. Figures reproduced with permission from Ref. [130], © 2016 MDPI AG.

Fig. 8. (a) TEM image of the SnO2NP-rGO composite material. (b) Response curve of SnO2NP-rGO composite on exposure to 5 ppm NO2 at 50°C. (c) Transient curves for dynamic sensing of NO2 by SnO2NP-rGO composite. (d) Responses of SnO2NP-rGO composite to various gases (Cl2, NO, CO, H2O (25% RH), and NO2) at 50°C. Figures reproduced with permission from Ref. [131], © 2014 Elsevier.

Fig. 9. (a) TEM image of the AuNP-SnO2NP-rGO composite material. (b) Response curve of AuNP-SnO2NP-rGO composite on exposure to 5 ppm NO2 at 50°C. (c) Dynamic NO2 sensing transients curve of the AuNP-SnO2NP-rGO composite (5-50 ppm). Figures reproduced with permission from Ref. [126], © 2014 Royal Society of Chemistry.

Fig. 10. (a) Response and recovery curve of the sensor based on SnO2NP-rGO composite (5 ppm NO2, operated at room temperature). (b) Response and recovery curve of the sensor based on SnO2NP-CNT-rGO composite (5 ppm NO2, operated at room temperature). (c) Response of the sensor based on SnO2NPCNT-rGO composite to 1-100 ppm of NO2 at room temperature. (d) Selectivity of the sensor based on SnO2NP-CNT-rGO composite to 5 ppm of various gases,

including NO2, Cl2, CO, and NH3 at room temperature. Figures reproduced with permission from Ref. [132], © 2015 Elsevier.

Fig. 11. (a) Ideal gas-sensing mechanism for gas sensors based on multilevel hybrid composites. (b) SEM image of a typical multilevel AgNP-NA-rGO composite deposited on the surface of an interdigitated electrode. (c) Linear relationship with NO2 concentration in the range of 1-10 ppm. (d) Selective responses of the AgNP-NA-rGO composite-based sensor to 10 ppm of NO2, acetone, ethanol, and NH3. Figures reproduced with permission from Ref. [140],

© 2015 Royal Society of Chemistry.

Fig. 12. (a) SEM images of single rGO-decorated cotton yarn (rGO-CY). (b) SEM images of single rGO-decorated polyester yarn (rGO-PY). Figures reproduced with permission from Ref. [48], © 2015 Macmillan Publishers Limited, part of Springer Nature. (c) Responses of the Ni-CB composite to 0.5-100 ppm NO2 at room temperature. (d) Responses of Ni-CB composite to different gases at room temperature. Figures reproduced with permission from Ref. [45], © 2015 Royal

Society of Chemistry.

Material

Operating temperature

Detection range (ppm)

LOD (ppm)

Response time

Recovery time

Reference

α-Ni(OH)2-carbon black

22°C (RT)

0.5-100

0.5

2s

-

[45]

SWCNT

165°C

0.01-0.1

0.044

<600 s

600 s under UV light

[53]

MWCNT

RT

1-15

1

-

-

[54]

PtNP-SWCNT

25°C (RT)

2-5

2

>180 s

-

[50]

PdNP-MWCNTs

200°C

0.1-10

0.009

<600 s

>600 s

[92]

PtNP-MWCNTs

200°C

0.1-10

0.003

<600 s

>600 s

[92]

AuNP-MWCNTs

RT

0.1-1

0.1

>600 s

-

[82]

Epitaxial graphene

RT

2.5-50

-

>600 s

>1200 s

[59]

Ozone treated graphene

RT

0.2-200

0.0013

>720 s

>1500 s

[121]

Graphene nanomesh

RT

1-10

0.015

>300 s

-

[109]

Cs doped GO

RT

0.09-12.2

0.09

240 s

220 s

[120]

SnO2NP-rGO (2D)

50°C

0.5-500

-

135 s

200 s

[131]

SnO2NP-rGO (3D)

22-70°C

14-110

2

-

373 s

[137]

SnO2NP-S-rGO

RT

1-50

0.45

40 s

357 s

[118]

Cu2O nanowire-rGO

RT

0.4-2

0.064

-

-

[110]

AuNP-rGO

50°C

0.5-5

-

132 s

386 s

[130]

rGO nanofiber

RT

0.25-4.5

-

-

-

[138]

CNT-rGO

RT

0.5-10

-

3600 s

>3600 s

[58]

CNT-rGO-SnO2NP

RT

1-100

-

8s

77 s

[132]

3D graphene aerogel

RT

10-200

-

190 s

224 s

[139]

Table 1 Gas sensing properties of carbon material-based sensors for detecting NO2 gas. (CNT: carbon nanotube, SWCNT: single-walled carbon nanotube, MWCNT: multi-walled carbon nanotube, G: graphene, GO: graphene oxide, rGO: reduced graphene oxide, NP: nanoparticle, α-Ni(OH)2: a-type nickel

hydroxide, Cs: caesium, RT: room temperature, ppm: parts per million