Improvement of Gas-Sensing Performance of Large-Area Tungsten

Improvement of Gas-Sensing Performance of Large-Area Tungsten Disulfide Nanosheets by Surface Functionalization Kyung Yong Ko,† Jeong-Gyu Song,† Youngjun Kim,† Taejin Choi,† Sera Shin,† Chang Wan Lee,† Kyounghoon Lee,‡ Jahyun Koo,§ Hoonkyung Lee,§ Jongbaeg Kim,‡ Taeyoon Lee,† Jusang Park,*,† and Hyungjun Kim*,† †

School of Electrical and Electronic Engineering and ‡School of Mechanical Engineering, Yonsei University, 50 Yonsei-Ro, Seodaemun-Gu, Seoul 03722, Korea § Department of Physics, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05029, Korea S Supporting Information *

ABSTRACT: Semiconducting two-dimensional (2D) transition metal dichalcogenides (TMDCs) are promising gas-sensing materials due to their large surfaceto-volume ratio. However, their poor gas-sensing performance resulting from the low response, incomplete recovery, and insufficient selectivity hinders the realization of high-performance 2D TMDC gas sensors. Here, we demonstrate the improvement of gas-sensing performance of large-area tungsten disulfide (WS2) nanosheets through surface functionalization using Ag nanowires (NWs). Large-area WS2 nanosheets were synthesized through atomic layer deposition of WO3 followed by sulfurization. The pristine WS2 gas sensors exhibited a significant response to acetone and NO2 but an incomplete recovery in the case of NO2 sensing. After AgNW functionalization, the WS2 gas sensor showed dramatically improved response (667%) and recovery upon NO2 exposure. Our results establish that the proposed method is a promising strategy to improve 2D TMDC gas sensors. KEYWORDS: gas sensor, transition metal dichalcogenide, silver nanowire, surface functionalization, tungsten disulfide nanosheet

W

Among various gases, NO2 is one of the most common air pollutants, and it is produced by the emissions of fossil-fuel combustion and the exhaust fumes of cars. Since NO2 exposure causes skin damage and respiratory disorders, the American Industrial Hygiene Association has set a 5 min emergency exposure limit for NO2 at 35 parts per million (ppm).17 Furthermore, acetone is known to be a biomarker for diabetes, and sub-ppm acetone sensing can enable the noninvasive diagnosis of diabetes since the exhaled breath of diabetes patients contains more than 1.8 ppm of acetone.18−20 An improvement in the gas-sensing performance, including in response, selectivity, and recovery is essential to realize practical and reliable 2D TMDC gas sensors. Recently, research aimed at the improvement of response and selectivity has been actively performed using vertically aligned MoS221 and mercaptoundecanoic acid functionalized MoS2.16 However, these recent studies reported insufficient recovery for continual use. The recovery of TMDC gas sensors has been improved by

ith the advent of the era of the Internet of Things (IoT), various sensors that are embedded in physical objects and linked through a network have been in high demand.1 In particular, semiconductor gas sensors have attracted considerable attention for use in monitoring the atmospheric environment and for medical diagnosis, due to their simple sensing mechanism based on the resistance/current change upon gas exposure.2 In the past few decades, metal oxide semiconductors have been extensively studied as gas-sensing materials due to their low cost and ease of integration. Metal-oxide-based nanostructures such as nanospheres,3 nanorods,4 and nanowires4 have exhibited improved sensing performance because they have high surface-to-volume ratios. Semiconducting two-dimensional (2D) transition metal dichalcogenides (TMDCs; MX2: M = Mo, W; X = S, Se) have been considered as promising gas-sensing materials because they exhibit sensitivity to the atmospheric environment and a significant response due to their high surface-to-volume ratio.5−10 Thus, the sensing properties of MoS2 for detecting various gases, such as NO 2 , 6,8,11 NO, 12 NH 3 , 6,8,13−15 acetone,7,16 and ethanol,14,16 have recently been reported. © 2016 American Chemical Society

Received: June 2, 2016 Accepted: September 24, 2016 Published: September 24, 2016 9287

DOI: 10.1021/acsnano.6b03631 ACS Nano 2016, 10, 9287−9296

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Figure 1. (a) Photograph of the synthesized large-area 1L, 2L, and 4L WS2 nanosheets on an 8 in. SiO2 wafer. The WS2 nanosheets are uniform over a 4 in. length. (b) Raman spectra of 1L, 2L, and 4L WS2 nanosheets obtained using a 532 nm laser. Schematic image of the (c) pristine and (d) ANF WS2 nanosheets on the SiO2/Si substrate. Schematic image of the (e) pristine and (f) ANF WS2 gas sensors. (g) Photograph of the fabricated WS2 gas sensor using 1L, 2L, and 4L WS2. (h) Scanning electron microscopy image of the ANF WS2 nanosheet.

RESULTS AND DISCUSSION Figure 1a shows the synthesized large-area 1L, 2L, and 4L (where L refers to the number of layers, corresponding to sulfurized 20, 30, and 50 ALD cycles of WO3 films, respectively) WS2 nanosheets on SiO2 substrates (over 4 in.) laid on an 8 in. SiO2 wafer. In our previous work, we studied the thickness controllability and uniformity of WS2 nanosheets when ALD-based synthesis was employed.27 By increasing the number of plasma-enhanced atomic layer deposition (PEALD) cycles, the thickness of WO3 films was linearly increased with 10 cycles of nucleation delay, showing a growth rate of 0.9 Å/ cycle. The WO3 films that were synthesized by PEALD exhibited smooth and continuous surfaces (see Supporting Information, Figure S1a−f). Then, WS2 nanosheets were synthesized via sulfurization of the WO3 films. The thickness of the 1L, 2L, and 4L WS2 nanosheets was confirmed by atomic force microscopy (AFM; see Supporting Information, Figure S1g−i). Since the ALD process could be used to control the film thickness elaborately with large-area uniformity, the ALD-based WS2 could be a promising practical synthesis process for fabricating 2D TMDC gas sensors.27,29 The number of layers of WS2 nanosheets was measured through Raman spectroscopy using 532 nm laser excitation. As shown in the Raman spectra in Figure 1b, WS2 peaks are observed at approximately 353 and 418 cm−1. The 353 cm−1 peak corresponds to a combination of the in-plane phonon mode, E12g, and 2LA(M) peak, which is the strongest second-order Raman resonance peak of the longitudinal acoustic mode at the M point. The 418 cm−1 peak corresponds to the out-of-plane phonon mode. We fitted the Raman peaks using a Lorentzian function. The extracted peak positions of 2LA(M), E12g, and A1g modes are shown in Figure 1b for different numbers of layers. We observed that the position of the A1g peak blue shifts, whereas the positions of E12g and 2LA(M) peaks red shift (see Supporting Information, Figure S2a).30 Furthermore, as the number of layers increased

employing external energies such as thermal energy or optical energy, which are sufficient for the desorption of gas molecules from the surface.8,22 However, this improvement in recovery results in a deterioration in the response due to the increased desorption rate.7 Thus, another approach for improving the sensing performance of gas sensors is required. Noble metal functionalization is a promising method because the metal’s catalytic effect, which can reduce the energy required for reacting with gas molecules, improves response, selectivity, and recovery.23−25 In particular, a recent study aimed at enhancing the NO2-sensing performance of Ag-functionalized SnO2 microrods reported improvement in the response and recovery.26 Thus, surface functionalization using a noble metal can be considered as an effective tool for improving the sensing performance of gas sensors. Here, we demonstrate the improvement of gas-sensing properties of 2D WS2 nanosheets through AgNW functionalization. Large-area WS 2 nanosheets and AgNWs were synthesized by the sulfurization process of atomic layer deposition (ALD) WO3 and a modified CuCl2-mediated polyol process, respectively.27,28 Acetone and NO2 sensing was comparatively studied using pristine and AgNW-functionalized (ANF) WS2 gas sensors. Both pristine and ANF WS2 gas sensors show a good response and recovery for acetone sensing. However, the ANF WS2 gas sensor exhibited superior selective NO2 gas sensing in terms of response and recovery. We confirmed the effect of AgNW functionalization of WS2 nanosheets through X-ray photoelectron spectroscopy (XPS) and ultraviolet photoelectron spectroscopy (UPS). Further, to identify and analyze the significantly superior NO2-sensing performance of the ANF WS2 gas sensor, we performed firstprinciples calculations on adsorption of NO2 on WS2 and Ag using the density functional theory. 9288


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Figure 2. Gas-sensing results for the pristine WS2 gas sensors consisting of 1L, 2L, and 4L WS2 nanosheets upon (a) acetone exposure (0.5, 1, 2, 4, and 10 ppm) and (b) NO2 exposure (25, 50, 100, 200, and 500 ppm). (c) Energy band diagram of WS2 gas sensor junction with Cr/Au metal contact. (d) Energy band diagram of WS2 gas sensor under bias and effect of acetone/NO2 gas exposure.

maintained for 10 min to allow the gas sensors to recover. As shown in Figure 2a, the pristine 4L WS2 gas sensor showed a greater decrease in the current upon acetone exposure compared to 1L and 2L WS2 gas sensors. Furthermore, the current changes of the pristine WS2 gas sensors fabricated using 2L and 4L WS2 are clearly observed even for an acetone concentration as low as 0.5 ppm, while the pristine WS2 gas sensor fabricated using 1L WS2 shows negligible variation. Figure 2b shows the increased current of pristine WS2 gas sensors upon exposure to NO2; this behavior is opposite to the acetone-sensing behavior. These current changes indicate that the sensors differentiate between the target gas molecules, that is, acetone and NO2 and O2 molecules, which are present along with the target gases, because the target gas concentration is controlled by being diluted with a “balance gas”, such as dry air with 21% O2 and 79% N2. Thus, the changes in current depend on which molecules are adsorbed on the WS2 surface. Furthermore, in a recent study, density functional theory calculation results demonstrated the changes in electronic structures of WS2 upon adsorption of various gas molecules (H2, O2, H2O, NH3, NO, NO2, and CO).33 Each molecule shows different adsorption energy and degree of charge transfer to WS2. These differences are responsible for the differentiable sensing signals of WS2 gas sensors. Similar to the acetone-sensing results, the pristine 4L WS2 gas sensor shows the greatest increase in the current upon NO2 exposure compared to that of 1L and 2L WS2 gas sensors. Despite the great NO2-sensing response, the pristine WS2 gas sensors show incomplete recovered current after the NO2 supply was completely stopped, as indicated by comparison with the initial current during air exposure. These results are similar to the results of other TMDC gas sensor studies, and they are attributed to the strongly adsorbed NO2 molecules on WS2.8,33 Interestingly, our sensors show different sensing

from 1L to 4L, the peak difference (frequency difference) of A1g−E12g increases from 61 to 64.9 cm−1, while that of A1g− 2LA(M) increases from 66 to 69.4 cm−1, and this observation agrees with previously reported results (see Supporting Information, Figure S2b).30−32 Further, Raman mapping analysis showed good uniformity of the WS2 nanosheets (see Supporting Information, Figure S3). Next, we fabricated gas sensors using the synthesized largearea WS2 nanosheets. Figure 1c−f displays the synthesis process for pristine and ANF WS2 gas sensors. ANF WS2 was formed through spin-coating using AgNWs synthesized using a modified CuCl2-mediated polyol process, as shown in Figure 1d.28 Then, as schematically shown in Figure 1e,f, pristine and ANF WS2 gas sensors were fabricated with thermally evaporated metal contacts (Cr 5 nm, Au 50 nm). Figure 1g shows the pristine WS2 gas sensors fabricated using large-area 1L, 2L, and 4L WS2. Furthermore, the formation of AgNWs on WS2 was observed by capturing a scanning electron microscopy (SEM) image of the ANF WS2 nanosheet, as shown in Figure 1h. The coverage area of AgNWs was determined to be approximately 2.5% of the entire area of the WS2 nanosheet, through calculations using the ImageJ image analysis software (Wayne Rasband, National Institutes of Health, USA). Since the density of AgNWs is appropriate, that is, the NWs occupy a partial area without connection between metal contacts, we can evaluate the effect of AgNW functionalization. The gas-sensing performance of pristine WS2 gas sensors consisting of 1L, 2L, and 4L WS2 was systemically evaluated with a constant voltage bias (+1 V) between each pair of metal contacts. Figure 2a,b shows the current change of the pristine WS2 gas sensors upon exposure to acetone (concentrations: 10, 5, 2, 1, and 0.5 ppm) and NO2 (concentrations: 25, 50, 100, 200, and 500 ppm), respectively. The exposure to the target gas was maintained for 5 min, while the exposure to air was 9289


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Figure 3. Gas-sensing results of the ANF WS2 gas sensors consisting of 4L WS2 nanosheet upon (a) acetone exposure (0.5, 1, 2, 4, and 10 ppm) and (b) NO2 exposure (25, 50, 100, 200, and 500 ppm). (c) Comparison of response as a function of the number of layers between the pristine and ANF WS2 gas sensors for 10 ppm acetone and 500 ppm of NO2. Error bar: standard deviation of response. (d) Comparison of response between the pristine and ANF WS2 gas sensors for 25 ppm of NO2. Percent recovery of the pristine and ANF WS2 gas sensor for (e) acetone and (f) NO2 exposure as a function of gas concentration.

difference between WS2 and the metal contact is favorable for forming a high Schottky barrier.34,36,37 Figure 2d displays the carrier transport of pristine WS2 under a constant voltage bias, which shows that a large proportion of electron carrier transport is blocked by the Schottky barrier, while the minority carrier can pass through the valence band of pristine WS2. Thus, the current of the pristine WS2 gas sensor is decreased by the limited hole transport, which is attributed to the downward bending of the valence band upon acetone exposure, while an increased current (increase in hole transport) is indicated by the upward-bent valence band upon NO2 exposure. Figure 3a,b shows the gas-sensing property of the ANF WS2 gas sensor with a 4L WS2 nanosheet. The ANF 4L WS2 gas sensor shows a current change behavior similar to that of the pristine WS2 gas sensor upon acetone and NO2 exposure, as shown in Figure 2a,b, respectively. Interestingly, after AgNW functionalization, the 4L WS2 gas sensor exhibits a current level approximately 2 orders lower than that of the pristine WS2 gas sensor. Furthermore, ANF WS2 gas sensors consisting of 1L and 2L WS2 show similarly decreased current levels compared to those of the pristine WS2 sensor (see Supporting Information, Figure S5). This lowered current of ANF WS2 gas sensors is probably attributed to the n-type doping effect caused by the electrons transferred from AgNWs to WS2.42−44 The withdrawn electrons can decrease the current level of ANF WS2 because the concentration of holes, which dominantly

behaviors that are directly opposite to the sensing behaviors of the n-type MoS2 gas sensor upon exposure to acetone and NO2.8 The current of the WS2 gas sensor decreased upon acetone exposure, although acetone acts as an electron donor. On the other hand, increased current is exhibited upon NO2 exposure, although NO2 acts as an electron acceptor when it is adsorbed on the surface.33 These opposite behaviors, which appear similar to the p-type characteristics, probably originated from the ambipolar conductivity of WS2 and the high Schottky barrier between the metal contact and WS2, as noted in recent reports.34−36 Furthermore, the nonlinear I−V curve of the pristine WS2 gas sensor is observed as evidence of the existence of a considerable level of Schottky barrier (see Supporting Information, Figure S4a).6,36 The high Schottky barrier, which can be attributed to the high work function difference between the metal contact (Cr/ Au) and pristine 4L WS2, can be illustrated as shown in Figure 2c.36,37 It is worth noting that the work function for pristine 4L WS2 (4.39 eV) determined via UPS analysis was smaller than other reported values of the work function for WS2 multilayers, which range from 4.7 to 5.1 eV (see Supporting Information, Figure S4).37,38 We considered that this small work function is related to the electrical properties of our WS2 nanosheets synthesized by the ALD-based process because the work function is dependent on the electrical properties such as the carrier concentration.39−41 Thus, the high work function 9290


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Figure 4. (a) Binding energies of core levels in pristine and ANF WS2 samples. UPS results of pristine and ANF WS2 surfaces at the (b) low binding energy region and (c) high binding energy region. (d) Band alignment of pristine and ANF WS2 calculated using UPS data.

ANF 4L WS2 gas sensor to NO2 is superior to that observed in the recent works on 2D TMDC gas sensors;21,22 the exception is the NO2 response value of the MoS2 FET gas sensor with +15 V gate bias.8 Further, by applying the gate bias, the response of this MoS2 FET gas sensor was enhanced by the modulated carrier concentration. However, a practical sensing platform based on the FET gas sensor requires a significant amount of power and has a complex structure, for example, with a gating part; however, the fabrication and structure of our two-terminal-structure-based gas sensor are simple, and it consumes less power.47 Furthermore, as shown in Figure 3d, the ANF 4L WS2 gas sensor shows a significantly high response of 58% to 25 ppm of NO2, while the pristine 4L WS2 gas sensor shows only 8.7% response. Further, our ANF 4L WS2 gas sensor exhibits 32% response at even 1 ppm of NO2 (see Supporting Information, Figure S6). The recovery, which is one of the representative indexes of gas-sensing performance, significantly affects reliability and sustainability. Thus, the recovery characteristics of pristine and ANF 4L WS2 gas sensors were quantitatively investigated by calculating the percent recovery.48,49 The percent recovery is defined as follows:

contributes to charge transport, can be decreased through recombination. The response of the pristine WS2 gas sensor was calculated to conduct a quantitative study, as shown in Figure 3c. The sensor response is defined as follows: response (%) =

Ig − I0 I0

× 100% =

ΔI × 100% I0

(1)

Here, I0 and Ig are the currents of the gas sensor before and after exposure to the target gas, respectively. The responses of pristine and ANF WS2 gas sensors are shown in Figure 3c for 10 ppm acetone and 500 ppm of NO2, which are selected as the highest concentrations in this gas-sensing experiment. As shown in Figure 3c, the higher response was observed with increasing number of layers, which is similar to the other recent result for a TMDC gas sensor, showing a negative increasing response for acetone sensing from −31 to −51% and a positive increasing response for NO2 sensing from 16 to 52%.8 The detailed mechanism of this tendency was explained by the redox potential alteration of 2D TMDCs, which is dependent on the number of layers, but it remains unclear.8 Meanwhile, the ANF WS2 gas sensors show a considerably superior NO2sensing ability but a slightly lower response to acetone. Nevertheless, our pristine and ANF WS2 gas sensors show a high performance for low-concentration acetone sensing (0.5− 10 ppm), while the recently reported exfoliated MoS2 gas sensor could only detect acetone concentrations greater than 500 ppm.7 On the other hand, the ANF 4L WS2 gas sensor shows a 667% response, which is 12 times the response of the pristine 4L WS2 gas sensor, because Ag catalytically promotes the adsorption of NO2 molecules by generating intermediate states between the NO2 gas phase and adsorbed NO2 on WS2.26,45 The intermediate states contribute to the NO2 spillover to WS2, which was consistent with H spillover to graphene through Pd catalysts.46 This response value of the

percent recovery (%) =

Ig − Ir Ig − I0

× 100% (2)

Here, I0 is the current value before exposure to the target gas, Ig is the current value after 5 min of target gas exposure, and Ir is the recovered current value after 10 min of air exposure. As shown in Figure 3e, the pristine and ANF 4L WS2 gas sensors show a high percent recovery greater than 90%, which implies good recovery to acetone sensing. On the other hand, as shown in Figure 3f, the pristine WS2 gas sensor exhibits low percent recovery ranging from 15 to 82% for NO2 exposure (25−500 ppm). This low percent recovery is attributed to the strongly adsorbed NO2 molecules.47 However, the ANF 4L WS2 gas 9291


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Figure 5. Adsorption of NO2 molecules on S-edge zigzag or armchair edges of WS2. Optimized geometries of NO2 molecules adsorbed on (a) S-edge zigzag edge or (b) armchair edge of WS2 and (c) Ag(100) surface. (d) Calculated NO2 adsorption energies per NO2 molecule for the Ag(100) surface and different edges of WS2: WS2−B indicates the basal plane of WS2, whereas WS2-Z and WS2-A indicate the S-edge zigzag and armchair edges of WS2, respectively; further, the energy region of NO2 gas phase is shown as a gray band.

the work function of WS2 decreased after AgNW functionalization. Based on the increased electron concentration of ANF WS2 due to the n-type doping effect, the decreased acetone response and increased NO2 response of the ANF WS2 gas sensor, as shown in Figure 3c, can be understood.6,8 Since NO2 is an electron acceptor, more electrons of ANF WS2 are accepted under NO2 exposure.8 On the other hand, since acetone molecules act as electron donors, a decreased response is observed upon acetone exposure.8 To identify and interpret the significantly enhanced NO2sensing performance of the ANF WS2 gas sensor, we performed first-principles calculations on adsorption of NO2 on WS2 and Ag using the density functional theory52 implemented in the VASP package53 within the generalized gradient approximations.54 The adsorption of NO2 molecules on the Ag surface and S-edged zigzag or armchair edge of WS2 are shown in Figure 5a−c. For the calculation of NO2 adsorption energy to a Ag surface, the (100) surface was selected because the AgNWs have the (100) surface.28 NO2 molecules are adsorbed on the Ag surface and preferably along the edges of WS2, which results in cleavage of NO2 into NO and O. Thus, the energy of NO2 molecules is in the order of μNO2@gas > μNO2@Ag > μNO2@ WS2, as shown in Figure 5d, where μNO2 denotes the energy per NO2 molecule for the given phases. The experimental values55 of the chemical potential of NO2 gas range from −0.64 to −0.83 eV between 25 and 100 °C under a pressure of 1 atm, which reflects the temperature and pressure conditions in our experiment. From the NO2 gas phase, NO2 molecules are adsorbed on the Ag surface and spread on the WS2 receptor surface, which corresponds to the NO2 spillover because of the

sensor shows significantly improved percent recovery for NO2 sensing (over 90%) because the low surface energy of Ag promotes the chemisorption of nitrogen and oxygen species on the Ag surface during the recovery process.26 To distinguish the effects of AgNW functionalization further, XPS and UPS analyses were conducted. The XPS spectra in Figure 4a show that the binding energy (BE) of W 4f7 shifts from 31.98 to 32.38 eV and that of S 2p3 shifts from 161.68 to 162.08 eV. The upward shift of peaks can be understood to be a result of the n-type doping effect since the Fermi level lies at the zero energy shift toward the conduction band, which is consistent with results of previous n-type doping studies on MoS2.44,50,51 The n-type doping effect in ANF WS2 is considered to be a result of the electron carrier transport from AgNWs to the WS2 surface because the 2D TMDCs can be doped by the surface charge transfer doping method by decorating noble metal nanoparticles on the surface.42 The argument for the n-type doping effect per the XPS results can be reinforced by analyzing the UPS of pristine and ANF 4L WS2 nanosheets using a helium resonance lamp, which has a photon energy of 21.2 eV. As shown in Figure 4b, from the tangent line of the low BE cutoff, we determined the difference between the valence band maximum and Fermi level (EF) to be 0.91 and 1.06 eV for the pristine and ANF WS2, respectively.50 Figure 4c shows high BE cutoff values of 16.81 and 16.96 eV for the pristine and ANF WS2, respectively. Since the work function is defined as the difference between the injected photon energy (21.2 eV) and the high BE cutoff value, we calculate the work function of pristine and ANF WS2 as 4.39 and 4.24 eV, respectively. As illustrated in Figure 4d, the Fermi level of WS2 increased by 0.15 eV (n-type doping effect), while 9292


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which can generate the intermediate states between the NO2 gas phase and NO2 adsorbed on WS2 and dissociate the NO2 molecules into NO− and O−, as shown in Figure 6c.26 Furthermore, the increased electron concentration of WS2, which results from the n-type doping effect of AgNW functionalization, can enhance the NO2 response because the NO2 adsorption, which involves electron acceptance, can be improved, as shown in Figure 6d.6,8 Thus, the significant improvement in NO2 sensing by the ANF WS2 gas sensor is attributed to the synergetic effect of the catalytic effect and ntype doping effect resulting from AgNW functionalization.

Ag catalyst. This is consistent with the H-spillover model involving Pd catalysts.46 Our calculations show that the adsorption of NO2 on the zigzag (armchair) edges is more favorable than the basal plane exhibiting higher adsorption energy. However, the NO2 adsorption on surfaces also occurs when the NO2 concentration is sufficiently high. On the other hand, Bader charge analysis56 showed that 1.0 (1.4) and 1.7 (1.7) electrons are transferred from WS2 to NO and O adsorbed on the zigzag (armchair) edges, respectively, because N and O have high electron affinity. This result supports the increase in the current with the increase in the hole concentration. The schematic images in Figure 6 summarize the gas-sensing mechanism. When the pristine WS2 gas sensor is exposed to

CONCLUSIONS In summary, a significantly improved gas-sensing performance of large-area 2D WS2 was demonstrated through AgNW functionalization, which enables overcoming the limitations of 2D TMDC gas sensors such as low response, poor recovery, and insufficient selectivity. The pristine WS2 gas sensor shows a high response to acetone and NO2 but incomplete recovery for NO2 sensing. AgNW functionalization resulted in a 12-fold enhanced response (667%) to NO2 sensing due to the resultant catalytic effect and n-type doping effect of AgNWs. The NO2sensing recovery is also significantly improved, with percent recovery greater than 90%, which provides reliability and sustainability. Interestingly, a high selectivity to NO2 is also achieved. Thus, the AgNW functionalization of large-area 2D WS2 can be considered as a versatile solution to resolve the low NO2-sensing performance issues in terms of response, recovery, and selectivity. METHODS AND MATERIALS ALD-Based Synthesis of WS2 Nanosheets. Large-area WS2 nanosheets were synthesized using an ALD-based process with a controlled number of layers, as we previously reported.27 The ALDbased process consisted of the following two steps: (1) WO3 films were deposited on SiO2/Si substrates using ALD for 20, 30, or 50 cycles in a 6 in. ALD chamber at a 300 °C growth temperature. The precursor and reactant were WH2(iPrCp)2 (Air Liquide) and O2 plasma, respectively. (2) The WO3 films were sulfurized at 1000 °C for 30 min with the mixed flow of Ar (50 sccm) and H2S (5 sccm). Finally, the WS2 samples were cooled to room temperature with Ar flow (50 sccm). The samples prepared with 20, 30, and 50 cycles corresponding to 1L, 2L, and 4L WS2 nanosheets. Synthesis of Silver Nanowires. The AgNWs were synthesized using a modified CuCl2-mediated polyol process.28,57 First, 5 mL of ethylene glycol (EG) was added to a disposable glass vial and heated for 1 h using a silicon oil bath at 151.5 °C under magnetic stirring (260 rpm). Then, 40 μL of a 4 mM Cu additive solution was added to the preheated EG solution. After 5 min, 1.5 mL of a 147 mM polyvinylpyrrolidone (PVP) solution in EG was added to the heated EG. Then, 1.5 mL of a 94 mM AgNO3 solution was added slowly and dropwise to the heated EG over a period of 5 min. The reaction temperature was maintained at 151.5 °C for an additional 1 h under magnetic stirring at 260 rpm. After the synthesis, the reaction solution was cooled to room temperature. The synthesized AgNWs were diluted with acetone and centrifuged at 2000 rpm for 30 min to remove EG. Then, the AgNWs diluted with methanol were centrifuged three times under the same conditions to separate PVP residues from the AgNWs. The elimination of PVP was indicated by Fourier transform infrared spectra of AgNWs after multiple rounds of centrifugation with methanol (see Supporting Information, Figure S7). The final products were dispersed in ethanol and stored at room temperature. The average length and diameter of the AgNWs were approximately 9 and 500 nm, respectively. To measure the weight of the AgNWs, one-half of the stored AgNWs in the dispersed solution was collected on a Teflon filter and dried at 80 °C on a hot plate until

Figure 6. Schematic illustration of the gas-sensing mechanism. (a) Upon acetone gas exposure, the adsorbed oxygen species interact with the acetone molecules, and volatile species such as CO2 and H2O are generated. The electrons are returned to WS2. (b) After NO2 exposure, the NO2 molecules are adsorbed on the WS2 surface and more electrons are extracted from WS2. (c) Adsorption of catalytically enhanced NO2 molecules on the WS2 surface by AgNW functionalization causes an increase in the number of electrons extracted from the WS2 surface. (d) Electrons transfer from the AgNWs and increase the electron concentration of WS2, which in turn increases the number of adsorbed NO2 molecules.

acetone gas, as shown in Figure 6a, volatile molecules (CO2, H2O) are formed via reaction between acetone and oxygen species adsorbed on the WS2 surface. The oxygen species, such as O2− and O−, are adsorbed during the air-purging step since dry air includes 21% O2 and 79% N2. Then, the captured electrons will be released to the WS2, resulting in the electron− hole compensation or recombination and eventually suppressing the hole concentration, which dominantly affects the current flow of our WS2 surface. This suppressed hole concentration causes a decrease in the current, as shown in Figures 2a and 3a. On the other hand, when NO2 gas is supplied, the NO2 molecules will adsorb on the surface and extract electrons from the WS2, as shown in Figure 6b. These extracted electrons cause the increase in the hole concentration upon exposure to NO2, which increases the current, as shown in Figures 2b and 3b. Meanwhile, the ANF WS2 gas sensor could extract more electrons because the rate of reaction of NO2 molecules would be increased by the catalytic effect of Ag, 9293


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ACS Nano the solvent was completely evaporated. The weight of the filtered AgNWs was measured by using an electronic microbalance, and the concentration of the AgNWs in the solution was found to be 0.295 wt %. Functionalization of WS2 Nanosheets Using AgNWs. AgNWs were deposited on the 1L, 2L, and 4L WS2 nanosheets on SiO2 substrates. A few drops of an aqueous solution of AgNWs (0.295 wt %) were added to the WS2/SiO2 samples, which were spin-coated at 1000 rpm for 15 s. Finally, the AgNW/WS2/SiO2 samples were dried at 90 °C for 20 min. Gas Sensor Fabrication. The Cr/Au electrodes with 5 nm/50 nm thickness were deposited on the WS2 nanosheet by using a thermal evaporator. A stainless steel shadow mask was used to form the patterns of electrodes on the pristine and functionalized WS2 nanosheets. The dimensions of the substrate were 10 mm × 20 mm, and the dimensions of the two electrodes were 3 mm × 13 mm with a 1 mm distance between them. Characterization of WS2 and AgNW-Functionalized WS2. Optical microscopy (Olympus DX51), Raman spectroscopy (LabRam ARAMIS, HORIBA; 532 nm laser excitation wavelength), AFM (Multimode, VEECO), SEM (JSM-6701F, JEOL Ltd.), XPS (K-Alpha model, Thermo Scientific Co.), and UPS (AXIS−NOVA, KRATOS Inc.) were employed to characterize the pristine and functionalized WS2. Gas-Sensing Experiment. The sensing performance of the fabricated sensors was monitored in a sealed gas-sensing chamber. An electrical feed-through and gas inlet and outlet were installed in the chamber. We used dry air (21% O2 and 79% N2) as the purging gas. The target gas was diluted with dry air (final concentration: 25−500 ppm), and the operation temperature was 100 °C. The concentrations of each gas were adjusted by controlling the flow rates of the target gas and balance gas (air), which was achieved using mass-flow controllers. The target gas and purging gas were exposed for 5 and 10 min for each cycle of the gas-sensing test, respectively. Before target gas injection, the gas sensors were stabilized under air exposure for ∼1 h. Both the pristine and functionalized WS2 gas sensors were tested under the same sensing setup and gas-flow conditions.

dimensional chalcogenides for next generation electronic devices). Moreover, this work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. NRF2014R1A2A1A11052588), Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (No. 2015R1D1A1A01060064), the Yonsei University Futureleading Research Initiative, and Institute of BioMed-IT, EnergyIT, and Smart-IT Technology (BEST), a Brain Korea 21 plus program, Yonsei University. The tungsten precursor was supplied by Air Liquide.

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ASSOCIATED CONTENT S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsnano.6b03631. Observation of roughness of PEALD WO3 and thickness of WS2 nanosheets, Raman shift and peak difference of 1L, 2L, and 4L WS2, Raman mapping results of 1L, 2L, and 4L WS2, Schottky barrier between WS2 and metal contact (Cr/Au), gas-sensing results of ANF WS2 gas sensors (1L, 2L), NO2 sensing (1 ppm) result of ANF 4L WS2, Fourier transform infrared spectroscopy (PDF)

AUTHOR INFORMATION Corresponding Authors

*E-mail: [email protected]. *E-mail: [email protected]. Notes

The authors declare no competing financial interest.

ACKNOWLEDGMENTS This work was supported by the Center for Integrated Smart Sensors funded by the Ministry of Science, ICT & Future Planning as Global Frontier Project (CISS-2011-0031848). In addition, this work was supported by Korea Evaluation Institute of Industrial Technology (KEIT) funded by the Ministry of Trade, Industry and Energy (MOTIE) (Project No. 10050296, Large scale (Over 8″) synthesis and evaluation technology of 29294


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