Rational Design of Aminopolymer for Selective Discrimination of

pollution tracker due to its low-power consumption, miniaturi- zation ..... Sensing response of CNT/mPEI with molar ratio from 1:0 to 1:4 onto (d) CO2...
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Rational Design of Aminopolymer for Selective Discrimination of Acidic Air Pollutants Soo-Yeon Cho, Kyeong Min Cho, Sanggyu Chong, Kangho Park, Sungtak Kim, Hohyung Kang, Seon Joon Kim, Geunjae Kwak, Jihan Kim, and Hee-Tae Jung ACS Sens., Just Accepted Manuscript • DOI: 10.1021/acssensors.8b00247 • Publication Date (Web): 05 Jun 2018 Downloaded from http://pubs.acs.org on June 5, 2018

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Rational Design of Aminopolymer for Selective Discrimination of Acidic Air Pollutants Soo-Yeon Cho†,‡,〦, Kyeong Min Cho†,‡,〦, Sanggyu Chong†, Kangho Park †,‡, Sungtak Kim§, Hohyung Kang†,‡, Seon Joon Kim†,‡, Geunjae Kwakǁ, Jihan Kim*,†, and Hee-Tae Jung*,†,‡ †

Department of Chemical and Biomolecular Engineering (BK-21 Plus), Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea ‡ KAIST Institute for Nanocentury, Daejeon 34141, Korea § Plant Engineering Division, Energy & Environment Research Team, Institute for Advanced Engineering (IAE), Yongin 17180, Korea ǁ C1 Gas Conversion Research Group, Carbon Resources Institute, Korea Research Institute of Chemical Technology (KRICT), Daejeon 34114, Korea Key words: air pollutant, gas sensor, carbon nanotube, selectivity, methylation

ABSTRACT: Strong acidic gases such as CO2, SO2, and NO2 are harsh air pollutants with major human health threatening factors, and as such, developing new tools to monitor and to quickly sense these gases are critically required. However, it is difficult to selectively detect the acidic air pollutants with single channel material due to the similar chemistry shared by acidic molecules. In this work, three acidic gases (i.e. CO2, SO2, and NO2) are selectively discriminated using single channel material with precise moiety design. By changing the composition ratio of primary (1°), secondary (2°), and tertiary (3°) amines of polyethylenimine (PEI) on CNT channels, unprecedented high selectivity between CO2 and SO2 is achieved. Using in-situ FT-IR characterizations, distinct adsorption phenomenon of acidic gases on each amine moiety is precisely demonstrated. Our approach is the first attempt at controlling gas adsorption selectivity of solid-state sensor via modulating chemical moiety level within single channel material. In addition, discrimination of CO2, SO2, and NO2 with single channel material solid-state sensor is firstly reported. We believe that this approach can greatly enhance air pollution tracking systems for strong acidic pollutants and thus aid future studies on selective solid-state gas sensors.

Global warming and climate change cause environmental air pollution that poses severe health risk to people all around the world. Burning fossil fuels that include coal, petroleum, and natural gas lead to formation of gaseous oxides.1 Representative gaseous oxides such as carbon dioxide (CO2), sulfur dioxide (SO2), and nitrogen dioxide (NO2) are harsh air pollutants responsible for formation of ground-level photochemical smog and acid rain due to their strong acidic characteristics.2-4 In addition, parts per million (ppm) or even parts per billion (ppb) concentrations of these acidic gases in the ambient air can cause dysfunction of various organs of living beings, which can ultimately lead to respiratory illness, cardiovascular disease or even death.5-7 Thus, precise measurement and realtime tracking of ambient concentration of these acidic air pollutants (CO2, SO2, NO2) are critical to secure safety and health of human beings. Traditionally, technologies such as gas chromatography, infra-red (IR) sensor, and solid-state sensor have been used to track and to monitor air pollutants. Based on the different strengths of mobile interaction between analytes-column and number of IR absorption peaks of the analytes, gas chromatography and IR sensor can selectively detect strong acidic air pollutants.8-11 However, given that the detection tools are ex-

tremely expensive, huge, and complex, it would be difficult to extend this technology for future pollution detecting systems. Thus, among these technologies, solid-state gas sensor based on customized electronics and internet-of-things (IoT) has been viewed as the best candidate for user-oriented ambient pollution tracker due to its low-power consumption, miniaturization, device compatibility, multi-channel operation and integrated circuit (IC) possibilities.12 In order to use solid-state sensor for acidic air pollutants detector, it is important to demonstrate precise discrimination and selective tracking of strong acidic air pollutants with single channel material as it is difficult to integrate multi-channel material into a single chip fabrication process.12 However, since the acidic air pollutants (CO2, SO2, NO2) possess similar chemical properties, it is very difficult to differentiate these gas molecules using single channel material.7 In solid-state sensors, sensing signal is based on variations of electrical properties (i.e. resistance variation) that result from channelanalytes chemical interactions. Therefore, it is difficult to perfectly discriminate sensing signals from analytes having similar molecular structures and properties using only a single channel material. In addition, selective detection using single channel material should be applicable for concentration range

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down to permissible exposure limit (PEL) (PEL; acceptable average exposure over the continuous working period of 8 hours) and up to ‘immediately dangerous to life concentration’ (IDLH), with stable and reliable response/recovery behavior at room temperature operations.1 Up until now, metal oxide semiconductors (MOS) including WO3, SnO2, and ZnO have been primarily used as channel materials for solid-state air pollution detector because MOS based solid-state sensors have shown high sensitivity to acidic air pollutants based on thickness change of electron depletion layer (EDL) by oxygen ion (O- or O2-) adsorption/desorption.13-16 However, previous MOS sensors have not shown precise discrimination of acidic air pollutants with single channel material.14 In addition, MOS based acidic pollutants sensors can be operated only at high temperatures of 300 to 400 °C. This can lead to high power consumption of devices, which is not acceptable in low-power operating IoT based gas sensors.17 Other materials including carbon nanomaterials, organo-metal complex, and ionic liquid have also been suggested to detect acidic air pollutants, but unfortunately, none of these materials have satisfied the requirements posed above.18-22 Herein, we developed a selective sensor of acidic air pollutants (CO2, SO2, NO2) using a single channel carbon nanotube (CNT) material. In this work, CNT is modified by attaching polyethylenimine (PEI) with rich amine groups to selectively adsorb CO2, SO2, and NO2. Pristine CNT sensor is selective only to NO2, and unprecedented high selectivity between CO2 and SO2 is achieved with precise amine moiety control of PEI, allowing the three acidic air pollutants to be selectively discriminated with a single channel material. The amine moiety controlled PEI/CNT sensors show high sensitivity (>2%) and fast response/recovery behavior (10~20 sec) onto acidic pollutants from sub-ppm to % level with room temperature operations. It is noteworthy that our approach is the first successful attempt at discriminating all acidic gases (CO2, SO2, NO2) with single channel material via modulation of chemical moiety level.

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Figure 1. Design of CNT sensing channels with chemical moiety controlled aminopolymers for selective sensing of acidic pollutants.

Design of CNT sensing channels with chemical moiety controlled aminopolymers for selective sensing of acidic pollutants. Schematic illustrations of Figure 1 show the material design and device structure of selective acidic air pollutants detectors. CNT is utilized as a single channel material due to its high sensitivity and selectivity onto NO2, as opposed to CO2 and SO2,23,24 thus selectivity toward acidic gases can be achieved by surface functionalization on CNT. We measured the resistance variance between each Au electrodes where the CNT network provides electrical pathway with junction of each strands.25 In the presence of target gases, the interaction between the gas molecule and CNT channels changes the electrical behavior of the channel, which is converted into electrical signal. Accordingly, the interaction property of surface modifier on CNT determines the selectivity precisely. Regarding the aminopolymer for sensitive sensing of acidic gases, primary (1°, -RNH2) and secondary amine (2°, -R2NH) moieties adsorb the CO2 and SO2 strongly via the acid-base reaction due to its high basicity.26,27 On the other hand, tertiary amines (3°, -R3N) with lower basicity interact selectively with SO2 but not CO2 since SO2 has high polarity.28,29 Accordingly, PEI functionalized CNT (CNT/PEI) induces CO2, SO2 sensing ability as 1° and 2° amine groups of PEI chains can adsorb the both CO2 and SO2 strongly. Indeed, methylated-PEI (mPEI) functionalized CNT (CNT/mPEI) could show selective sensing behavior on SO2 not CO2 due to selective adsorption behavior on 3° amine. Thus, we would design and precisely control the amine moieties in polymer, which provides sensitive and selective interaction with acidic gases. The detail chemistry, adsorption mechanism and sensing property of designed CNT channels will be investigated in the manuscript thoroughly.

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Figure 2. Preparation of CNT sensing channels with chemical moiety controlled aminopolymers. (a) Schematic illustration of amine moiety control of PEI with methylation process. (b) 1H NMR spectrum and (c) FT-IR spectrum of PEI (black) and mPEI (red). (d) Raman spectrum and (e) SEM and TEM images (inset) of CNT, CNT/PEI and CNT/mPEI sensing channels.

To synthesize the polymer with sensitive and selective response to CO2 and SO2, the amine moiety of PEI needs to be controlled precisely. Figure 2a depicts the simple one-step methylation of PEI when the 1° and 2° amine are converted to 3° amine site (Eschweiler-Clarke reaction).30 Formaldehyde and formic acid are reacted with unsaturated amine sites (1° and 2° amine) in PEI at 95 °C for 12 h and the color of polymer was changed from transparent to orange. The 1H NMR was conducted to confirm the amine moiety change in PEI and mPEI (Figure 2b). Commercially available branched PEI consists of 1°:2°:3° amine sites with ratio of 4:3:2. In the spectra of mPEI, the prominent peak appeared at 2.3 ppm, which is attributed to protons in methyl group on 3° amine, while broad peak at 1.7 ppm assigned to 1° and 2° amine disappeared. In addition, the methylation of amines shifted the peak to higher field of 2.5 ~ 2.8 ppm, which is associated with protons at the linker between amine sites. These results indicate that 1° and 2° amine in PEI was methylated and consequently fully converted to 3° amine.28 FT-IR spectroscopy further confirm the amine moiety control in PEI (Figure 2c). The FT-IR spectra of PEI showed strong peaks at 1590, 3275 and 3355 cm-1 associated with N-H scissoring and stretch bonding, while these peaks disappeared after methylation of N-H bonding.29 In addition, the atomic ratio of carbon to nitrogen increased from 1.98 to 3.06 as a consequence of N-methylation (Table S1). Overall, we have managed to perfectly design and synthesize amine functional polymers consisting of basic amine groups and only tertiary amine sites. To verify that PEI and mPEI are well incorporated onto CNT surfaces, we carried out Raman spectroscopy and morphological characterizations. The aqueous solution of pristine CNT for fabricating channel film showed absorption band at 260 nm due to excitation of π electrons.31 The solution of CNT/PEI and CNT/mPEI showed different absorbance peak due to interaction between CNT and each aminopolymer (Figure S1). The Raman spectra of bare CNT show characteristic D band and G band at 1353 and 1585 cm-1, respectively (Figure 2d). Generally, the D band arises from disordered struc-

ture of graphitic carbon and G band arises from in-plane vibration of sp2 carbon in graphene.32,33 After functionalization of mPEI, ID/IG of mPEI/CNT shows significant increase to 1.55 with the result indicating that polymer hinders the graphitic vibration of CNT. Interestingly, even after PEI functionalization, the change in intensity ratio of D band to G band (ID/IG) was not observed. In addition, the G band is blue shifted from 1585 cm-1 to 1589 cm-1. Accordingly, the electron rich amine groups in PEI induce the interaction with π electrons of CNT without hindrance of graphitic vibration.34,35 In Figure 2e, pristine CNT channels are highly interconnected with ~20 nm diameter nanotubes. Similarly, CNT/PEI channel has highly dense network consisting of bundle of nanotubes with increasing thickness of nanotubes by PEI functionalization. The phase imaging in AFM further revealed that the nanotubes in CNT/PEI possess smooth surfaces and thick diameter compared to the pristine CNT (Figure S2). In addition, uniform wrapping of amorphous carbon around single strand of multi-walled CNT was observed in TEM image (insets, Figure 2b). These observations clearly demonstrate that PEI uniformly wraps around the pristine CNT. On the other hand, the different wrapping morphology was observed in CNT/mPEI channels. The surface of nanotubes became rough and the pore of channels was clogged with thicker nanotube. Clearly, it was observed in AFM and TEM images that the mPEI covers the CNT network roughly with mat-like structure. The amine moiety difference between PEI and mPEI cause the morphological difference in CNT/PEI and CNT/mPEI due to polarity changes by methylation of 1° and 2° amines. In addition, X-ray photoelectron spectroscopy was further exploited to existence of aminopolymers on CNT (Figure S3). N 1s XPS spectra of CNT do not show any existence of nitrogen. Meanwhile, the peaks appeared at binding energy of about 400 eV, which corresponds to various amine sites on CNT/PEI and exclusively tertiary amine sites on CNT/mPEI. The observed amine species confirm the existence of aminopolymers on CNT/PEI and CNT/mPEI.36

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Figure 3. Device characterizations and selective acidic gas sensing performance. (a) Optical microscope and SEM image of functionalized CNT sensors showing device structure. (b) Current−bias (IDS−VDS) curves of CNT, CNT/PEI and CNT/mPEI sensors. (c) Channel resistance variation of CNT with various composition ratio of PEI and mPEI Selective gas sensing performance of CNT, CNT/PEI, and CNT/mPEI sensor for harsh air pollutants (CO2, SO2, NO2). (d) Real-time gas response behavior and (e) response amplitude to CO2, SO2, NO2. (f) The maximal resistance change ((∆R/Rb)max (%)) onto wide concentration range of CO2, SO2, NO2.

Figure 3 shows the device characterizations and the selective CO2, SO2, NO2 sensing performances of the CNT, CNT/PEI, and CNT/mPEI sensors. In order to monitor the sensing signal of pristine CNT, CNT/PEI, and CNT/mPEI toward acidic air pollutants (CO2, SO2, NO2), the micro-films of the materials were fabricated by filtration of dispersions using a porous alumina membrane filter. 37-39 The films were then transferred onto SiO2 substrates printed with an interdigitated microelectrode. Optical microscope and top-view SEM image show that ultra-thin functionalized CNT film is uniformly integrated with 100 µm Cr/Au electrode (Figure 3a). To investigate the contact resistance at the junction between the functionalized CNT channel and metal electrodes, cur-

rent−bias (IDS−VDS) curves were obtained (Figure 3b). The IDS−VDS curves of CNT, CNT/PEI, and CNT/mPEI all exhibit good Ohmic contact characteristics (i.e. linear curve), indicating that contact resistance is not a dominant factor and that CNT channels are well-connected to the pre-deposited Au/Cr electrode with low-power operation.15 Especially, CNT/mPEI device shows low-gradient IDS−VDS curves, indicating higher channel resistance between the source and the drain. Figure 3c presents the channel resistance variation of the sensors with various composition ratios of PEI and mPEI. With addition of mPEI, CNT channel shows drastic increase of resistance from ~50 Ω to ~650 Ω due to reduction of conduction pathway between CNT bundles by mPEI interruption. On the other hand,

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with the addition of PEI, the resistance stays at ~50 Ω, showing no signs of reduction in the channel conductance. As pristine PEI is low-work function modifier with electron-rich properties of amine groups, charge carriers can travel across the CNT networks by hopping through PEI molecules.34,40 Figure 3d shows the real-time gas response behavior of CNT, CNT/PEI, and CNT/mPEI sensors to CO2, SO2, and NO2 exposure. These devices were simultaneously loaded on a home-made gas sensing chamber, and the sensing signals of each film were measured with multichannel sensing systems (the detailed schematic of the entire gas delivery system is described in Figure S4).41,42 A constant drain bias was applied to the two-probe sensor, and the electrical resistance change of the sensor upon exposure to air pollutants was monitored and recorded as the sensing signal. The real time sensing results of CNT, CNT/PEI and CNT/mPEI show that when three successive 1% CO2 pulses were injected for 5 min, they were selectively detected by the CNT/PEI sensor with 1% response amplitude. CNT/PEI sensors having huge amounts of 1° and 2° amine groups can strongly adsorb the CO2 with chemisorption process forming carbamate species as demonstrated in Figure 5. These species induce charge carrier hindrance onto CNT main channel increasing resistance of the sensors.43 On the contrary, the pristine and the CNT/mPEI sensors without the 1° and 2° amine groups did not show any response to the injected CO2. In the case of CNT/mPEI, neither chemisorption nor physisorption of CO2 occurred with 3° amines of the mPEI. Next, we tried three consecutive injections of 100 ppm SO2 pulses and this caused the CNT/PEI and CNT/mPEI sensors to respond markedly with 1% and 1.5% response amplitude, respectively. As similar to the CO2, CNT/PEI sensor strongly chemisorbs SO2 and form sulfate. In the case of CNT/mPEI, 3° amine of the mPEI strongly physisorbs the SO2 and form dipole moments. Thus, CNT/mPEI sensor can show sensitive detection of SO2. Figure S5 shows the distinct difference of response/recovery behavior to SO2 between CNT/PEI and CNT/mPEI sensors. CNT/mPEI sensor shows ~6 times slower response speed than CNT/PEI, however, ~60 times faster recovery speed. This is due to the relatively weak SO2 physisorption onto mPEI as opposed to in PEI, which is based on sulfamate formation.15,37 The pristine CNT sensors barely respond to 100 ppm SO2 pulses. Finally, for consecutive injections of 100 ppm NO2, all three channels show significant responses with about 2.5% response amplitude implying that the pristine CNT sensor shows superior NO2 selectivity over CO2 and SO2. Overall, using these CNT based three channels, harsh air pollutants of CO2, SO2, and NO2 can be efficiently discriminated even these gases show similar oxidizing, acidic properties. Figure 3e shows the bar graphs of response amplitude of each sensors to CO2, SO2, and NO2. It is clearly observed that CO2 and SO2 selectivity of CNT can be achieved with PEI and mPEI functionalization. It is interesting that NO2 sensitivity improvements of CNT with PEI and mPEI functionalization is not dominant as CO2 and SO2 cases. Even with PEI and mPEI functionalization, sensitivity is slightly enhanced about 1.4 times. This is due to the unstable chemisorption of NO2 molecules on PEI and mPEI: NO2 cannot form chemisorption species but form zwitter ion, which is intermediate step between physisorption and chemisorption. Thus, unlike in the case of CO2 and SO2 that chemisorbs onto the PEI and mPEI, NO2 cannot stably adsorb onto these materials. In addition, it is noticeable that pristine CNT channel shows p-

type response (negative resistance variation to oxidizing gases), however, CNT/PEI and CNT/mPEI show the opposite ntype response (positive variation to oxidizing gases). PEI and mPEI having rich amine groups with electron-donating property is acting as n-dopants transferring electron charge from PEI and mPEI to CNT channel,40 leading to the opposing behaviors. However, in the case of NO2, CNT/PEI and CNT/mPEI sensors also show p-type response as with the case for the pristine CNT channel, and this can be attributed to the strong p-doping characteristics of NO2 gas itself.44 Figure 3f shows the maximal resistance change ((∆R/Rb)max (%)) for a wide range of CO2, SO2, and NO2 concentrations. Here, Rb and ∆R represent the baseline resistance of each sensors and the resistance change (Rg(after exposure to analyte)Rb(baseline resistance)), respectively. Real time response data of each sensor for a wide concentration range is shown in Figure S6. It is clearly seen that only the CNT/PEI sensors shows selective detection of CO2 (from 0.05% to 1%). Response amplitudes of CNT/PEI are enhanced with increasing CO2 concentration for all of the range indicating that CNT/PEI sensor can distinguish CO2 concentration from ppm to percent level. For the SO2, both CNT/PEI and CNT/mPEI show response from 5 ppm (PEL) to 100 ppm (IDLH). Especially for CNT/mPEI, there is a linear relationship between (∆R/Rb)max (%) and SO2 concentration with significant response amplitude (Figure S7). On the other hand, (∆R/Rb)max saturates at around 50 ppm for CNT/PEI, indicating that linear response range of CNT/PEI is below 50 ppm level. Pristine CNT shows slightly increasing, but almost negligible, p-type response for SO2 above 20 ppm. Finally, in NO2, all three sensors show significant response to NO2 over 5 ppm showing linearly increased amplitude with concentration. It is noticeable that contrary to CO2 and SO2 cases, CNT/PEI and CNT/mPEI sensors show ptype response to NO2, which can be attributed to strong pdoping characteristics of NO2 gas itself as described previously.44 However, CNT/PEI sensor maintain its n-type response to low concentration of NO2 (below 30 ppm) indicating that ndoping characteristics of PEI is more significant than that of mPEI.40 Thus, by observing the response type of CNT/PEI and CNT/mPEI, we can determine the NO2 concentration ranges. With the data of the Figure 3f, the principal component analysis (PCA) is performed to investigate the discrimination ability of the sensing system with variation of target gases. PCA was performed in MATLAB using its built-in function Singularvalue Decomposition (SVD). Three highest value of singular values and corresponding right singular vectors were chose to graph the PCA results. PCA results shows that our single channel material detecting system can easily discriminate concentration range of each gases with three vectors (PC1, PC2, PC3) (Figure S8). Thus, if mixed gases are exposed to our systems, increased or decreased concentration of each gases can be calculated with calibration of three vectors. Overall, it is clear that our sensor systems can precisely discriminate three acidic gases (CO2, SO2, NO2) with wide concentration range from PEL to IDLH. In previous approaches, channel materials or different class of dopants would have been needed for selectivity control, however, our approach can efficiently control gas adsorption selectivity by just modulating chemical moiety of single channel material.13

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Figure 4. Gas response variation of CNT/PEI and CNT/mPEI with controlled doping concentrations. Sensing response of CNT/PEI with molar ratio from 1:0 to 1:4 onto (a) CO2 and (b) SO2. (c) The maximal resistance change ((∆R/Rb)max (%)) of CNT/PEI onto CO2, SO2, and NO2 with various doping ratio. Sensing response of CNT/mPEI with molar ratio from 1:0 to 1:4 onto (d) CO2 and (e) SO2. (f) The maximal resistance change ((∆R/Rb)max (%)) of CNT/mPEI onto CO2, SO2, and NO2 with various doping ratio.

Next, we investigate the relationship between the response amplitude of the CNT sensors and the composition ratio of PEI and mPEI (Figure 4). Figure 4a-b illustrates the sensing responses of CNT/PEI onto 1% CO2 and 100 ppm SO2 with varying molar ratio from 1:0 to 1:4. It can be clearly seen that for both CO2 and SO2, CNT/PEI sensor shows drastic enhancement of gas response with increasing PEI concentration. At PEI concentration ratio of 1:4, gas response is fifteen times greater compared to the case for pristine CNT. This is due to increase of carbamate and sulfamate formation on CNT/PEI channel with CO2 and SO2 adsorption, respectively, as demonstrated earlier. (∆R/Rb)max (%) plot confirms that CO2 and SO2 response drastically enhances with increasing PEI concentration ratio within the n-type response range (Figure 4c). On the contrary, NO2 response is only slightly enhanced with increasing PEI concentration ratio within the p-type response range. Real-time NO2 response is shown in Figure S9. Figure 4d-e shows the sensing responses of CNT/mPEI onto CO2 and SO2 with varying molar ratio from 1:0 to 1:4. It is clearly seen that CNT/mPEI sensor did not show any response to CO2 even with high concentration ratio (1:4) of mPEI. Even small responses to CO2 in the pristine CNT is removed with mPEI functionalization. As demonstrated earlier, CO2 are neither physisorbed strongly nor chemisorbed with tertiary amine of mPEI, and as such, CNT/mPEI did not show any response to CO2 even with high concentration functionalization. On the contrary, SO2 response of CNT/mPEI is drastically enhanced with increase of mPEI concentration ratio due to strong physisorption between SO2 and tertiary amine. (∆R/Rb)max (%) plot confirms that response amplitude start to drastically improve after 10:1 doping concentration and at 1:4 doping ratio, response is about 17 times higher than that of pristine CNT (Figure 4f). In CNT/PEI, NO2 response is slightly enhanced

with increase of mPEI but not by a significant amount. As a result, three acidic gases (CO2, SO2, NO2) can be selectivity discriminated with composition ratio control of PEI and mPEI.

Figure 5. Selective adsorption chemistry of CO2 and SO2 on CNT, CNT/PEI and CNT/mPEI film. In situ FT-IR spectra of CNT/PEI under the (a) 1% CO2 and (c) 100 ppm SO2. In situ FTIR spectra of CNT/mPEI under the (b) 1% CO2 and (d) 100 ppm SO2. (e) Schematic illustration of gas adsorption chemistry on CNT/PEI and CNT/mPEI.

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To demonstrate the selective gas sensing performance by amine moiety control on CNT channels, home-made in situ FT-IR spectroscopic study is used on CNT/PEI and CNT/mPEI systems under 1% CO2 and 100 ppm SO2. Adsorption species on sensing channel are observed by monitoring the change of IR absorption peak. The samples were prepared by painting PEI/CNT, mPEI/CNT pastes onto potassium bromide (KBr) pellet. First, CNT/PEI showed variety peaks which were gradually increased from 1200 to 1700 cm-1 under CO2 exposure (Figure 5a). The CNT/PEI showed peaks at 1380, 1438 and 1580 cm-1, which are attributed to the symmetric and asymmetric stretches of carboxylate ion. In addition, the band at 1305 may be associated with C-N stretch of the carboxylate ion. These peaks suggest that carbon dioxide bind to the 1° or 2° amine sites on CNT/PEI. Furthermore, the absorption band at 1480 and 1630 cm-1 are assigned to the symmetric and asymmetric deformations of the ammonium ions. This can be seen in formation of alkylammonium carbamate ion pairs, where the CO2 reacts with amine of PEI and stabilize with adjacent amine site.45-47 On the adsorbed SO2, three prominent peaks at 1170, 1195 and 1540 cm-1 were observed in PEI/CNT (Figure 5c). The appearance of peaks at 1170 and 1195 cm-1 were associated with stretching of the adsorbed sulfate, indicating chemisorption between SO2 and 1° or 2° amine sites in PEI, (similar to that of CO2 adsorption with CNT/PEI).48 From these in-situ FT-IR spectroscopy results for gas adsorption, the CNT/PEI channels chemisorb acidic gases on the amine site of PEI, which is in good agreement with previous studies on amine-adsorbent for acidic gas capture (Figure 5e).45,46 The CNT/mPEI showed different CO2 and SO2 adsorption behaviors compared to that of CNT/PEI. Under the CO2 exposure, this can be seen from the three dominant peaks at 1355, 1463 and 1687 cm-1, assigned to deformation, symmetric and asymmetric stretches of bicarbonate species, respectively (Figure 5b).45 Typically, the bicarbonate species are observed in physisorption in the presence of water or weak chemisorption on hydroxyl group on CNT surfaces. This indicates less likelihood of strong CO2 adsorption due to the low density of hydroxyl group on CNT and low adsorption energy of bicarbonate species. However, the different peaks at 1245 and 1473 cm-1 were presented in CNT/mPEI in the presence of SO2, which were assigned to stretch of adsorbed SO2 and methyl group on 3° amine sites (Figure 5d).49,50 The charge complex between SO2 and 3° amine is visible, indicating that the functionalized mPEI causes selective SO2 adsorption on CNT channels. Interestingly, our analysis in CNT/mPEI shows no significant changes in CO2 adsorption compared to pristine CNT. However, CNT/mPEI adsorbed SO2 through interaction between 3° amine and SO2 with strong polarity (Figure 5e). Thus, we verify our hypothesis that CNT/PEI sensitively adsorb CO2, SO2 and CNT/mPEI selectively adsorb only SO2. It is noticeable that the simple chemical moiety control achieves the sensitive and selective acid gas adsorption using CNT as a single channel material. To further understand the selective gas sensing phenomenon, density functional theory (DFT) calculations were conducted to determine the theoretical binding energies of CO2, NO2, and SO2 with the amine moieties of PEI and mPEI (Figure 6). The adsorption calculations of all gases for 1° and 2° amines of PEI was resolved into the following steps: physisorption, zwitterion formation, and chemisorption.16,51-53 As for the 3° amines of both PEI and mPEI, only the physisorption calcula-

tions were conducted with basis set superposition error (BSSE) correction imposed between the polymer cluster and gas molecule. CO2 exhibits significant binding energies only under the presence of the 1° and 2° amines of PEI, which is in accordance with how the strong signals were observed for CO2 only when the CNT/PEI sensor was used. SO2 shows exceptional binding energies with all of the amine moieties of PEI and mPEI, regardless of whether full chemisorption takes place or not. These results agree well with the experimental observation of strong signals with both the PEI and mPEI coated sensors. NO2 is found to be unstable in the fully chemisorbed anionic state with the 1° and 2° amines, and thus it does not show any significant change in its binding strength when different amine moieties are present. Accordingly, our experimental results also do not show any significant change in the signal strength of NO2 between the CNT, CNT/PEI and CNT/mPEI gas sensors. The overall trend observed in the gas binding energies with amines of PEI and mPEI is in good agreement with the experimentally observed trend in the gas signal strengths of CNT/PEI and CNT/mPEI sensors developed in this study. Details of the DFT calculations and the minimum energy configuration are presented in the Methods section and Figure S10.

Figure 6. DFT simulation results of acidic gas adsorption behavior on PEI and mPEI. The binding energies diagram of three acidic gases on (a) 1° amine sites, (b) 2° amine sites, (c) 3° amine sites of PEI, and (d) 3° amine sites of mPEI

In conclusion, for the first time, we demonstrated the selective detection of strong acidic air pollutants (CO2, SO2, NO2) using single channel material based solid-state sensors. With modulation of chemical moieties of aminopolymer and functionalization with CNT channel, gas adsorption selectivity is efficiently controlled: pristine CNT is selective to NO2, CNT/mPEI is selective to SO2 and NO2, and CNT/PEI is selective to all gases (CO2, SO2, NO2). Controlling the concentration ratio of PEI and mPEI, response amplitude of the sensors are selectively modulated. This is due to distinct adsorption mechanism of acidic gases with 1°, 2°, and 3° amines. In addition, the amine moiety controlled mPEI/CNT sensors show fast response/recovery behavior onto strong acidic pollutants from sub-ppm to percent level with room temperature operations. Selective discrimination between three acidic gases over wide concentration range using single channel material

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is firstly reported (Table S2). We believe that this approach that uses mPEI chemistry can be universally applied to various channel materials and may greatly motivate future studies on air pollution tracking systems for strong acidic pollutants using solid-state gas sensors.

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ASSOCIATED CONTENT Supporting Information. Experimental method. Elemental analysis of aminopolymer. UV-Vis measurement, AFM images, XPS measurement. Schematics of gas sensing system. Response and recovery time, real-time gas response onto wide concentration of sensors. Statistical analysis of the gas response of the systems. Real-time NO2 sensing data with various doping ratio of PEI and mPEI. Binding configuration of DFT simulation. Comparison table regarding selective sensing of acidic pollutants (PDF). This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION Corresponding Author * E-mail : [email protected], [email protected]

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Author Contributions ⊥

These authors contributed equally. 17.

ACKNOWLEDGMENT This research was supported by a National Research Foundation of Korea (NRF) grant funded by the Ministry of Science, ICT and Future Planning, Korea (MSIP, NRF-2012R1A2A1A01003537) and a Global Frontier grant funded by the Center for Advanced Soft Electronics under the Global Frontier Research Program of the Ministry of Science, ICT and Future Planning, Korea (MSIP, NRF-2012M3A6A5055744). S.C. would like to thank Bonglim Suh for valuable discussions regarding the ab initio calculations.

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Three acidic gases (CO2, SO2, and NO2) are selectively detected using single channel material with precise moiety design. By changing the composition ratio of primary, secondary, and tertiary amines of polyethylenimine (PEI) on CNT channels, unprecedented high selectivity between CO2 and SO2 is achieved.

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