Comparative Study on the Effect of Protonation Control For

applied sciences

Article Comparative Study on the Eﬀect of Protonation Control for Resistive Gas Sensor Based on Close-Packed Polypyrrole Nanoparticles

Wooyoung Kim 1, Sunghun Cho 2,* and Jun Seop Lee 3,* 1 School of Chemical and Biological Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-742, Korea; [email protected] 2 School of Chemical Engineering, Yeungnam University, Gyeongsan 38541, Korea 3 Department of Materials Science and Engineering, Gachon University, 1342 Seongnam-Daero, Sujeong-Gu, Seongnam-Si, Gyeonggi-Do 13120, Korea * Correspondence: [email protected] (S.C.); [email protected] (J.S.L.); Tel.: +82-31-750-5814 (S.C.); +82-53-810-2535 (J.S.L.) Received: 23 January 2020; Accepted: 3 March 2020; Published: 8 March 2020

Abstract: Conducting polymers are often used as sensor electrodes due to their conjugated chain structure, which leads to high sensitivity and rapid response at room temperature. Numerous studies have been conducted on the structures of conducting polymer nanomaterials to increase the active surface area for the target materials. However, studies on the control of the chemical state of conducting polymer chains and the modiﬁcation of the sensing signal transfer with these changes have not been reported. In this work, polypyrrole nanoparticles (PPyNPs), where is PPy is a conducting polymer, are applied as a sensor transducer to analyze the chemical sensing ability of the electrode. In particular, the protonation of PPy is adjusted by chemical methods to modify the transfer sensing signals with changes in the polymer chain structure. The PPyNPs that were modiﬁed at pH 1 exhibit high sensitivity to the target analyte (down to 1 ppb of NH3) with short response and recovery times of less than 20 s and 50 s, respectively, at 25 ◦C.

Keywords: polypyrrole; protonation; chemical sensor; nanoparticles; chemical state; ammonia gas

1. Introduction In the past few decades, chemical gas sensors have been widely used in several applications, including the detection of combustible, flammable, and toxic gases [1–5]. Various semiconductive materials are used as transducers for chemical sensors, and extensive investigations have been conducted to improve their performance [6–9]. The critical indicators for sensor performance include high sensitivity to the target analyte, short response and recovery times, and cycle stability [10,11]. Among these, the sensitivity and cycle stability are optimized via the control of the morphology of electrode materials. However, the response and recovery times can be adjusted by modifying the semiconductive properties of the electrode material, unlike other factors. Conducting polymers, which are semiconductive materials, have been investigated for sensor applications, owing to their versatility originating from the conjugated backbone structure consisting of alternating single and double bonds [12,13]. Conducting polymers have been used as sensor transducers with inherent electronic, optical, and mechanical transducing properties because of their unique properties [14–16]. Considerable efforts have been directed toward the fabrication of nanometer-scale conducting polymers, owing to their beneficial characteristics, such as small size, high surface-to-volume ratio, and amplified signals, to enhance the sensitivity [17–20]. In recent years, several studies have focused on increasing the surface area of conducting polymer nanomaterials

Appl. Sci. 2020, 10, 1850; doi:10.3390/app10051850 www.mdpi.com/journal/applsci Appl. Sci. 2020, 10, 1850 2 of 13 to maximize the interactions between the transducers and analytes [21–24]. Cho et al. fabricated multidimensional conductive nanofilms that consisted of graphene-coated carboxyl polypyrrole nanowires for application as a Hepatitis B surface antigen aptamer sensor electrode [21]. Bao et al. synthesized three-dimensional polyaniline hydrogels with high surface areas and conductivities for application in glucose oxidase sensors [24]. However, research on controlling the electrical signal transmission speed of the electrode materials is limited. Among the most popular conducting polymers, polypyrrole (PPy) exhibits several beneficial characteristics, including high electrical conductivity, redox property, and environmental stability [25–27]. PPy has been extensively investigated in sensor applications, owing to its unique chemical and electrical properties [28–30]. In particular, PPy has different electronic band structures, such as neutral, polaron, and bipolaron states, which can be facilely modified by controlling the doping ratio [31,32]. However, its structure rather than the doping ratio is more often modified for application in sensor transducer materials. Herein, the sensing performance of polypyrrole nanoparticles (PPyNPs) as a sensor transducer in different chemical states is investigated. First, PPyNPs with a uniform diameter of 60 nm were synthesized via a modified monodisperse method, and then subjected to chemical treatment while using aqueous solutions of different pH levels (pH 1–13). The charge carrier (hole) density and diameter of the particles decreased with an increase in pH, owing to the deprotonation of the polymer chain under basic conditions. The nanoparticles with controlled protonation were subsequently introduced on an interdigitated array electrode surface via spin-coating for application as an NH3 gas-sensing transducer. The sensor electrode at pH 1 exhibited high sensitivity to the target analyte (down to 1 ppb of NH3), with short response and recovery times of less than 20 s and 50 s, respectively, at 25 ◦C.

2. Materials and Methods

2.1. Materials

Iron chloride (III) FeCl3 (97%), poly(vinyl alcohol) (PVA, Mw 9000), dodecyl trimethylammonium bromide (DTAB, 98%), and pyrrole (98%) were purchased from Sigma–Aldrich and used as purchased. ≥ Sodium hydroxide (NaOH, 95%) and hydrochloric acid (HCl, 35~37%) were purchased from Samchun Pure Chemical Company (Pyeongtaek-si, Korea).

2.2. Fabrication of PPyNPs

PPyNPs were prepared while using PVA, FeCl3, and pyrrole in distilled water. A 0.5 g sample of PVA in distilled water (50 mL) was magnetically stirred (300 rmp) at 25 ◦C for 1 h. After the dissolution of PVA in distilled water, 0.02 mol of FeCl3 was added into the aqueous PVA solution with 300 rpm. After 1 h of equilibration, 0.06 mol of pyrrole monomer was rapidly added into the aqueous PVA/FeCl3 solution and then stirred for 4 h. After the completion of polymerization, the resulting nanoparticles were separated from the dispersion by centrifugation and then washed several times with water to remove the impurities. The remaining PPyNP precipitate was dried in a vacuum oven at room temperature for 6 h.

2.3. Protonation Control of PPyNPs PPyNPs were added to the aqueous solutions with diﬀerent pH values and sonicated for 1 h to uniformly disperse the nanoparticles in the solution. Except for pH 7, HCl and NaOH were used for realizing acidic and basic conditions, respectively. The pH 7 solution is used commercial phosphate buﬀers (Samchun Co.). Subsequently, the solutions with PPyNPs were stirred at a low rate for an additional 1 h to allow for the completion of the reaction between the particles and solvent. The mixed solution was centrifuged and dried overnight at 60 ◦C in an oven. Appl. Sci. 2020, 10, 1850 3 of 13

2.4. Electrical Sensing Measurement of Hazardous Gases Spin-coating was conducted to obtain a uniformly coated sensor electrode array. In detail, 0.1 wt% PPyNP containing aqueous solution is used. 10 µL of the solution was deposited on the electrode and following spin-coating was conducted (1000 rpm, 60 s). Afterwards, the electrode was dried at 60 ◦C in an inert atmosphere for 6 h to obtain good electrical ohmic contact between the PPyNPs and electrodes. The sensor electrode was placed inside the vacuum chamber (100 Torr) and connected to a source meter to monitor the resistance change while using a computer. In this experiment, a bubbler was used to vaporize the organic compounds from ammonia and methanol solutions and to mix the vapors with N2 gas using a mass flow controller to modify the concentrations of the analyte gases. The sensor electrode was exposed to various concentrations of analyte gases (1 ppb–100 ppm) for 100 s and then purged with N2 gas to recover the conductance. The measurement was performed by applying a constant 6 current of 10− A to the electrode and the sensitivity was calculated by measuring the normalized electrical resistance change, ∆R/R = (R R )/R , where R and R are the measured real-time resistance 0 − 0 0 0 and initial resistance, respectively. The response time was defined as the time that is required for a sensor to attain 90% of the maximum signal after gas exposure, and the recovery time was defined as the time that is required by a sensor to attain 10% of the preceding signal after purging with N2 gas. The sensing performance was evaluated under ambient conditions (ca. 20% relative humidity).

2.5. Characterization The ﬁeld emission-scanning electron microscopy (FE-SEM) images were obtained while using the JSM-6701F system (JEOL Ltd., Tokyo, Japan). X-ray photoelectron spectroscopy (XPS) data were acquired using a Sigma probe (Thermo, Waltham, MA, USA). The electrical conductivity was measured using a Keithley 2400 system. Raman spectra were obtained while using a LabRam Aramis (Horiba Jobin Yvon, Bensheim, Germany) spectrometer. Ultra-violet visible and near infra-red (UV-vis-NIR) spectra were collected on a UV-3600 Plus spectrophotometer (Shimadzu, Tokyo, Japan).

3. Results and Discussion

3.1. Transformation of Polymer Chain Structure Uniform PPyNPs (ca. diameter of 60 nm) as a sensor transducer material were synthesized via a modified monodisperse method [30]. Here, polyvinyl alcohol (PVA) and ferric chloride (FeCl3) were dissolved in deionized water to form the PVA/iron cation (Fe3+) complex that acted as the oxidizing and forming agent during the polymerization reaction. Subsequently, the pyrrole monomer was introduced into the aqueous PVA/Fe3+ complex solution with vigorous stirring to allow for the formation of PPyNPs at the reactive sites, where the pyrrole monomer contacted the PVA/Fe3+ complex. The charge carrier density and mobility of the PPy chain change reversibly with different protonation states, as shown in Figure1. The expanded state of the polymer chain is formed upon protonation, while the contracted state is formed upon deprotonation. The PPyNPs were dispersed in aqueous solutions with pH values ranging from pH 1 to 13 to achieve different chemical states of the polymer chains. The concentrations of the charge carriers in the polymer chain were determined while using UV-vis-NIR spectroscopy. UV-vis-NIR spectra were collected to examine the types and transition of the polymer chain at various pH values (Figure2). The polymer nanoparticles at pH 1 show the highest absorption intensity of the band above 1000 nm and around the 450 nm region because of the high carrier density in the polymer chain, which causes a reduction in the band gap, as shown in Figure2a. An increase in pH results in the reduction of the band intensity above 1000 nm and a blue shift of the medium intensity around 450 nm. These spectral changes show that a high pH results in the loss of protons (reduction) from the polymer chain [33]. Thus, the polymer chains transform from expanded to contracted states with an increase in pH. Figure2b also shows the maximum absorption at different wavelengths (300, 450, and 1000 nm). The absorption of the bands in the high-NIR region (1000 nm) continuously decreases as the chain structure changes from an expanded to contracted state. Appl. Sci. 2020, 10, x FOR PEER REVIEW 4 of 13 expanded to contracted state. In addition, the intensity of absorption at 450 nm (visible) shifts to a low wavelength with an increase in intensity at 300 nm (UV) due to the same reason. Raman spectroscopy was performed to characterize the different chemical states of the PPyNPs. Figure 3a shows the Raman spectra at different pH values (pH 1–13). The bands at 1049 and 1332 cm−1 corresponded to the in-plane C-H and C-C stretching vibrations, respectively. Moreover, the strong bands at 1421 and 1591 cm−1 are attributed to the C=C symmetric and C=C asymmetric vibrations, respectively. These bands shift to 1415 and 1562 cm−1, respectively, with an increase in pH indicating the transformation of the polymer chains from quinoid to benzenoid structures. Specifically, the positively doped species are located at the geometrical defects and form the quinoid structure. Therefore, high pH decreases the amount of (bi)polarons and changes the polymer chain structures to quinoid structures [34,35]. Furthermore, high-resolution N 1s X-ray photoelectron spectroscopy (XPS) was employed to confirm the change in the chemical state of the PPy chain at different pH values (Figure 3b–f). The peaks at ca. 400 eV (related to the neutral amine N of the pyrrole unit (-NH-)) and ca. 398 eV (attributed to imine (-N=)) are observed in all cases [36]. For the nanoparticles at pH 1 and 4, two types of positive nitrogen peaks, including the N peaks at 403.0 eV (=NH+-) and 401.4 eV (-NH+-), are observed. At high pH, a peak corresponding to the positively charged N (-NH+-) is observed at 401.4 eV. While using these data, the protonation of the nanoparticles can be calculated in terms of the ratio of the positive nitrogen peak area over the total nitrogen peak area (N+/Ntotal) [37]. On treatment with a base, N+/Ntotal is lower than those that were obtained under other conditions, because the positive nitrogen (N+) content in the structure decreases (i.e., deprotonation) at high pH. Thus, an increase in the protonation (i.e., lower pH) of the particle increases the amount of positively charged N in the structure. Field emission scanning electron microscopy (FE-SEM) measurements were performed for each nanoparticle to determine the morphological transformations of the PPyNPs with varying pH values (Figure 4). The morphologies of the PPyNPs change reversibly at different pH values through the osmotic effect of the counter ion (Cl−). Upon protonation, the electrons are ejected from the PPyNPs Appl.and Sci. a positive2020, 10, 1850 charge develops in the polymer chain. Thereafter, the anions in the solution4 of can 13 displace and induce a volume expansion in the polymer through the insertion of the counter ions and subsequent uptake of the solvent. Consequently, the average diameter of the individual In addition, the intensity of absorption at 450 nm (visible) shifts to a low wavelength with an increase nanoparticles reduces from 68.71 nm at pH 1 to 60.63 nm at pH 13. in intensity at 300 nm (UV) due to the same reason.

Appl. Sci. 2020, 10Figure, x FOR 1. PEERChemical REVIEW structures of polypyrrole (PPy) in diﬀerent chemical states. 5 of 13

Figure 1. Chemical structures of polypyrrole (PPy) in different chemical states. (a) pH 1 0.90

0.85 pH 13 pH 1

0.80

Abs. (a.u.) pH 13

0.75 400 600 800 1000 Wavelength (nm)

(b) 0.92 300 nm 450 nm 1000 nm 0.88

0.84

Abs. (a.u.)

0.80

2 4 6 8 10 12 pH

Figure 2. (a) Ultra-violet visible and near infra-red (UV-vis-NIR) absorption spectra of polypyrrole Figure 2. (a) Ultra-violet visible and near infra-red (UV-vis-NIR) absorption spectra of polypyrrole nanoparticles (PPyNPs) at diﬀerent pH values. (b) Normalized absorption spectra of PPyNPs with a nanoparticles (PPyNPs) at different pH values. (b) Normalized absorption spectra of PPyNPs with a change in pH at diﬀerent wavelengths (black for 300 nm, red for 450 nm, and blue for 1000 nm). change in pH at different wavelengths (black for 300 nm, red for 450 nm, and blue for 1000 nm).

Raman spectroscopy was performed to characterize the diﬀerent chemical states of the PPyNPs. (a) (b) (c) (1591 cm-1) (1562 cm-1) 1 Figure3a shows theC=C symmetry Raman spectra at di ﬀerentN 1s pH values (pH -NH- 1–13). The bandsN 1s at 1049 and 1332 -NH- cm C=C asymmetry (1421 cm-1) (1415 cm-1) − C-C stretching pH 1 -N= pH 4 -N= (1332 cm-1) + + corresponded to the in-planeC-H C-H in-plane and C-C stretching vibrations, -NH - respectively. Moreover, the -NH strong- (1049 cm-1) + pH 13 =NH+- =NH -

pH 10

pH 7

pH 4 Intensity (a.u.)

Intensity (a.u.)

Intensity (a.u.) pH 1

1800 1600 1400 1200 1000 396 400 404 408 396 400 404 408 Raman shift (cm-1) Binding energy (eV) Binding energy (eV)

(d) (e) (f) N 1s -NH- N 1s -NH- N 1s -NH- pH 7 -NH= pH 10 -NH= pH 13 -NH= + + -NH - -NH - -NH+-

Intensity (a.u.)

396 400 404 408 396 400 404 408 396 400 404 408 Binding energy (eV) Binding energy (eV) Binding energy (eV)

Figure 3. (a) Raman spectra of PPyNPs at different pH values (black: pH 1, red: pH 4, blue: pH 7, green: pH 10, and pink: pH 13). N 1s X-ray photoelectron spectra (XPS) of PPyNPs at different pH values: (b) pH 1, (c) pH 4, (d) pH 7, (e) pH 10, and (f) pH 13. Appl. Sci. 2020, 10, x FOR PEER REVIEW 5 of 13

(a) pH 1 0.90

0.85 pH 13 pH 1

0.80

Abs. (a.u.) pH 13

0.75 400 600 800 1000 Wavelength (nm)

(b) 0.92 300 nm 450 nm 1000 nm 0.88

0.84

Abs. (a.u.) Appl. Sci. 2020, 10, 1850 5 of 13 0.80 1 bands at 1421 and 1591 cm− are attributed to the C=C symmetric and C=C asymmetric vibrations, 2 4 61 8 10 12 respectively. These bands shift to 1415 and 1562 cm− ,pH respectively, with an increase in pH indicating the transformation of the polymer chains from quinoid to benzenoid structures. Speciﬁcally, the positively doped species are located at the geometrical defects and form the quinoid structure. Therefore, high pH Figure 2. (a) Ultra-violet visible and near infra-red (UV-vis-NIR) absorption spectra of polypyrrole decreases the amount of (bi)polarons and changes the polymer chain structures to quinoid structures [34, nanoparticles (PPyNPs) at different pH values. (b) Normalized absorption spectra of PPyNPs with a 35]. change in pH at different wavelengths (black for 300 nm, red for 450 nm, and blue for 1000 nm).

(a) (b) (c) (1591 cm-1) (1562 cm-1) C=C symmetry N 1s -NH- N 1s -NH- C=C asymmetry (1421 cm-1) (1415 cm-1) C-C stretching pH 1 -N= pH 4 -N= (1332 cm-1) + + C-H in-plane -NH - -NH - (1049 cm-1) + pH 13 =NH+- =NH -

pH 10

pH 7

pH 4 Intensity (a.u.)

Intensity (a.u.)

Intensity (a.u.) pH 1

1800 1600 1400 1200 1000 396 400 404 408 396 400 404 408 Raman shift (cm-1) Binding energy (eV) Binding energy (eV)

(d) (e) (f) N 1s -NH- N 1s -NH- N 1s -NH- pH 7 -NH= pH 10 -NH= pH 13 -NH= + + -NH - -NH - -NH+-

Intensity (a.u.)

396 400 404 408 396 400 404 408 396 400 404 408 Binding energy (eV) Binding energy (eV) Binding energy (eV)

FigureFigure 3. 3.(a )(a Raman) Raman spectra spectra of of PPyNPs PPyNPs at at di ﬀdifferenterent pH pH values values (black: (black: pH pH 1, 1, red: red: pH pH 4, 4, blue: blue: pH pH 7, 7, green:green: pH pH 10, 10, and and pink: pink: pH pH 13). 13). N N 1s 1s X-ray X-ray photoelectron photoelectron spectra spectra (XPS) (XPS) of of PPyNPs PPyNPs at at di differentﬀerent pH pH values:values: (b ()b pH) pH 1, 1, (c )(c pH) pH 4, 4, (d ()d pH) pH 7, 7, (e )(e pH) pH 10, 10, and and (f) ( pHf) pH 13. 13.

Furthermore, high-resolution N 1s X-ray photoelectron spectroscopy (XPS) was employed to confirm the change in the chemical state of the PPy chain at different pH values (Figure3b–f). The peaks at ca. 400 eV (related to the neutral amine N of the pyrrole unit (-NH-)) and ca. 398 eV (attributed to imine (-N=)) are observed in all cases [36]. For the nanoparticles at pH 1 and 4, two types of positive nitrogen peaks, including the N peaks at 403.0 eV (=NH+-) and 401.4 eV (-NH+-), are observed. At high pH, a peak corresponding to the positively charged N (-NH+-) is observed at 401.4 eV. While using these data, the protonation of the nanoparticles can be calculated in terms of the ratio of the + positive nitrogen peak area over the total nitrogen peak area (N /Ntotal)[37]. On treatment with a + base, N /Ntotal is lower than those that were obtained under other conditions, because the positive nitrogen (N+) content in the structure decreases (i.e., deprotonation) at high pH. Thus, an increase in the protonation (i.e., lower pH) of the particle increases the amount of positively charged N in the structure. Field emission scanning electron microscopy (FE-SEM) measurements were performed for each nanoparticle to determine the morphological transformations of the PPyNPs with varying pH values (Figure4). The morphologies of the PPyNPs change reversibly at di fferent pH values through the osmotic effect of the counter ion (Cl−). Upon protonation, the electrons are ejected from the PPyNPs and a positive charge develops in the polymer chain. Thereafter, the anions in the solution can displace and induce a volume expansion in the polymer through the insertion of the counter ions and subsequent uptake of the solvent. Consequently, the average diameter of the individual nanoparticles reduces from 68.71 nm at pH 1 to 60.63 nm at pH 13. Appl. Sci. 2020, 10, 1850 6 of 13

Appl. Sci. 2020, 10, x FOR PEER REVIEW 6 of 13

(d) 20 pH 1 Mean = 68.71 nm 15

Counts 5

0 20 40 60 80 100 120 Diameter (nm)

(e) 20 pH 7 Mean = 63.26 nm

Counts 5

0 20 40 60 80 100 120 Diameter (nm)

(f) 20 pH 13 Mean = 60.63 nm

Counts 5

0 20 40 60 80 100 120 Diameter (nm)

FigureFigure 4. 4.( (aa––cc)) FieldField emissionemission scanningscanning electronelectron micrographs micrographs of of PPyNPs PPyNPs and and ( d(d––ff)) size size distribution distribution of of thethe nanoparticles nanoparticles within within a unita unit area area (1 µ(1m µm1 ×µ 1m) µm) at di atﬀ erentdifferent pH valuespH values ((a,d ):((a pH,d): 1; pH (b, e1;): ( pHb,e): 7; pH (c,f ):7; × pH(c,f 13).): pH 13).

3.2.3.2. ElectricalElectrical ConductivityConductivity TheThe electricalelectrical conductivityconductivity ofof thethe PPyNPsPPyNPs isis investigatedinvestigated toto determinedetermine thethe chargecharge transfertransfer withwith 1 changeschanges in in pH pH (Figure (Figure5). 5 Di). Dffifferenterent protonation protonation levels levels control control the the electrical electrical conductivity conductivity (128 (128 S cm S− cmat−1 1 pHat pH 1 to 1 1.9to 1.9 S cm S cm− at−1 at pH pH 13), 13) as, as an an increase increase in in acidity acidity increases increases the the carrier carrier density density (hole) (hole) in in polymer polymer chains.chains. ThisThis isis becausebecause protonproton dopingdoping occursoccurs duringduring thethe acidicacidic treatmenttreatment andand thetheβ β-carbon-carbon inin thethe polymerpolymer chainchain structurestructure isis preferentiallypreferentially protonatedprotonated[ 38[38]].. ProtonationProtonation isis essentialessential forfor inducinginducing thethe short-rangeshort-range ordering ordering of theof the polymer polymer backbone backbone and for and the foreffi cientthe protonefficient transport proton in transport the conjugated in the chains,conjugated and itchains, is achieved and it by is increasingachieved by the increasing amount of the C= amountC stretching of C=C [39 stretching]. Additionally, [39]. Additionally, a significant decreasea significant in the decrease electrical in conductivity the electrical is observed conductivity under is basic observed conditions under due basic to a conditions drastic reduction due to in a thedrastic number reduction of charge in the carriers number during of charge deprotonation. carriers during deprotonation. Appl. Sci. 2020, 10, x FOR PEER REVIEW 7 of 13 Appl. Sci. 2020, 10, 1850 7 of 13

Appl. Sci. 2020, 10, x FOR) PEER200 REVIEW 7 of 13 -1 60 nm PPyNP

150) 200

-1

s cm 60 nm PPyNP

( 150

100s cm

(

100 50 50 0 Conductivity 0

Conductivity 2 4 6 8 10 12 Doping2 4 solution6 8 (pH10 ) 12 Doping solution (pH)

FigureFigure 5.5. ElectricalElectrical conductivitiesconductivities ofof PPyNPsPPyNPs atat variousvarious pHpH values.values. Figure 5. Electrical conductivities of PPyNPs at various pH values. 3.3. Preparation of PPyNP-Based Sensor Electrode 3.3. Preparation of PPyNP-Based Sensor Electrode 3.3. Preparation of PPyNP-Based Sensor Electrode PPyNPs were immobilized on the interdigitated array electrode to determine the sensing PPyNPs were immobilized on the interdigitated array electrode to determine the sensing performancePPyNPs of the particles were immobilized as a function on the of interdigitated pH. The conduction array electrode pathway to determine and eﬀective the sensing surface performance of the particles as a function of pH. The conduction pathway and effective surface area area wereperformance utilized to of compare the particles the as performance a function of pH of the. The particles conduction with pathway the variation and effective in their surface chemical area were utilizedwere utilized to compare to compare the performance the performance of the of the particles particles with with the the variation variation in ththeireir chemical chemical state. state. state. Figure6 shows the data for the source-drain current as a function of the source-drain voltage Figure Figure 6 shows 6 shows the data the datafor the for source the source-drain-drain current current as as a a function function of of the source source-drain-drain voltage voltage (ISD-VSD) for the nanoparticles; the results indicate that the nanoparticles are in good electrical contact (ISD-VSD)(I forSD-V theSD) fornanoparticles; the nanoparticles; the results the results indicate indicate that that the the nanoparticles nanoparticles areare in goodgood electrical electrical contact contact with the sensor substrate. However, the uniform decoration of the particles improves the conduction with thewith sensor the sensorsubstrate. substrate. Howeve However, ther, uniformthe uniform decoration decoration of of the the particles particles improves the the conduction conduction pathway, i.e., increases the sensitivity to the analyte. The randomly stacked arrangement of the PPyNPs pathway,pathway, i.e., increases i.e., increases the sensitivity the sensitivity to the to the analyte. analyte. The The randomly randomly stacked stacked arrangement arrangement of of the the that werePPyNPs prepared that bywere drop-casting prepared by hasdrop a-casting higher has contact a higher resistance contact thanresistance the uniformthan the uniform array that array was PPyNPs that were prepared by drop-casting has a higher contact resistance than the uniform array obtainedthat by spin-coatingwas obtained dueby spin to the-coating interruption due to the of interruption the conduction of the pathway conduction through pathway the through accumulated the that was obtained by spin-coating due to the interruption of the conduction pathway through the particle-particleaccumulated assembly. particle- Therefore,particle assembly. PPyNPs Therefore, were deposited PPyNPs onwere the deposited electrode on via the spin-coating electrode via to accumulated particle-particle assembly. Therefore, PPyNPs were deposited on the electrode via determinespin the-coating sensing to determine performance the sensing in real performance time with minimum in real tim contacte with minimum resistance. contact resistance. spin-coating to determine the sensing performance in real time with minimum contact resistance.

0.5 (mA) 0.0

SD I -0.5 dI/dV = 0.92 x 10-2

(mA) 0.0 dI/dV = 1.13 x 10-2

I -1.0 -2 -0.5 dI/dVdI/dV = 1.320.92 xx 10 10-2 -1.5 dI/dV = 1.13 x 10-2 -1.0 -0.1 0.0 0.1-2 dI/dV = 1.32 x 10 Drop casting V (V) -1.5 SD (d) -0.11.5 0.0 0.1 Drop casting pH 1 V (V) 1.0 pH 7 SD (d) 1.5 pH 13 0.5 pH 1 1.0 pH 7

0.0

(mA)

SD pH 13 0.5I -0.5 dI/dV = 0.47 x 10-2 dI/dV = 0.66 x 10-2 -1.0 -2

0.0 (mA) dI/dV = 0.94 x 10

SD I -0.5-1.5 -2 -0.1 0.0dI/dV = 0.47 x 100.1 Spin-coating V dI/dV (V) = 0.66 x 10-2 -1.0 SD dI/dV = 0.94 x 10-2 Figure 6. (a,b) Field emission scanning electron-1.5 microscopy (FE-SEM) images and (c,d) source-drain voltage-current curves of the PPyNP-decorated sensor-0.1 electrodes prepared0.0 by (a,c) drop0.1-casting or Spin-coating V (V) (b,d) spin-coating. SD FigureFigure 6.6.( (aa,b,b)) FieldField emissionemission scanningscanning electronelectron microscopymicroscopy (FE-SEM)(FE-SEM) imagesimages andand ((cc,d,d)) source-drain source-drain voltage-currentvoltage-current curvescurves ofof thethe PPyNP-decoratedPPyNP-decorated sensorsensor electrodeselectrodes preparedprepared byby ((aa,c,c)) drop-castingdrop-casting oror (b(b,d,d)) spin-coating. spin-coating. Appl. Sci. 2020, 10, 1850 8 of 13

3.4. Comparison of Sensing Performance The changes in the real-time responsive resistance were measured for different concentrations of gases at 25 ◦C. Figure7a shows the sensing performance of the electrodes toward NH 3 gas, which is one of the reducing gases, with respect to the pH. The NH3 molecules generate electrons, owing to the reduction characteristics during detection. These electrons are transferred to the PPyNPs, thereby reducing the amount of the charge carriers (hole) in the polymer chain. Therefore, the resistance of the sensor electrode increases, owing to the p-type semiconductor characteristics of the polymer. The sensor electrodes exhibit being highly sensitive toward NH3 down to 10 ppb due to the uniformly decorated nanoparticles on the IDA electrode. However, the response amounts of the electrodes display increase with reducing pH of solution. The more protonated PPyNPs (treated at pH 1) have more holes in the chain structure, indicating a higher degree to change in external electron flow. On the other hand, the electrode that was treated at pH 13 shows the smallest amount of resistance change, even though it has the smallest diameter. Thus, a reduction in the amount of holes, rather than a reduction in the surface area, has a greater effect on response change. Figure7b shows the recovery times of the electrodes, exhibiting a decrease from 59 s (pH 13) to 19 s (pH 1). The numerous charge carriers (hole) at pH 1 induce the rapid transfer of electrons from the analyte and reduce the response time to <20 s. However, the recovery times of the electrodes exhibit similar values, i.e., 66 s for pH 13, 61 s for pH 7, and 49 s for pH 1, because the detachment of the target molecule is related to the applied external energy rather than to the charge carriers and number of active sites (Figure7c). Moreover, the sensing performance with decreasing NH3 concentration was also measured to confirm the reproducibility of the electrode. Figure7d shows that the sensing ability of the electrode remains constant, regardless of the direction of change in NH3 concentration. In addition, we also compared the response and recovery times of the electrode with the direction of concentration changes. The response time of the sensor electrode is similar (19 s) in both cases, as shown in Figure7e. However, the recovery time for backward direction (60 s) presents a little longer than forward direction (49 s), due to exposure to large amount of NH3 molecules during detection (Figure7f). Therefore, PPy-based sensor electrodes have good reproducibility for environmental changes. Additionally, methanol (MeOH) was used to determine the sensing ability for an oxidizing gas (opposite charge-transfer direction) (Figure8a). The electrode oxidized at pH 1 is superior to other electrodes for the same reason, as observed in the case of NH3. Figure8b shows the variation in the normalized resistance of the electrodes as a function of NH3 and MeOH gas concentrations. The 2 3 linear-behavior range is larger for the electrode oxidized at pH 1 (1 ppb–10 ppm for NH3 and 0.1–10 ppm for MeOH) than for the other electrodes. Therefore, the sensor electrode oxidized at pH 1 can be effectively utilized as a signal transducer for detecting NH3 and MeOH gases at various concentrations. Additionally, outstanding cycle stability is required for use of the electrode materials in practical sensor devices. Figure8c shows the change in the resistance of the electrode at pH 1 upon periodic exposure to 10 ppb NH3 gas. During the five repetitive on–off tests, the resistance changes remain relatively constant, without a delay in the response or recovery. Furthermore, the sensor electrodes maintain their sensing ability during exposure to 0.1 ppm of NH3 over 15 days (Figure9). Appl. Sci. 2020, 10, 1850 9 of 13 Appl. Sci. 2020, 10, x FOR PEER REVIEW 9 of 13

(a) 20 (b) 4 pH 1 NH3 pH 1 NH3 0.1 ppm pH 7 15 3 pH 7 19 s pH 13 pH 13 53 s 10 (%)

(%)

0 2

5 R/R

R/R



 1 59 s 0 10 ppb 0.1 ppm 1 ppm 10 ppm 100 ppm 0 0 400 800 1200 0 50 100 150 200 Time (s) Time (sec)

(%) 10

(%)

61 s 0

R/R 5

66 s R/R

 1  0 100 ppm 10 ppm 1 ppm 0.1 ppm 10 ppb 0 200 240 280 0 300 600 900 1200 1500 Time (sec) Time (s)

(e) 4 (f) pH 1 forward NH3 0.1 ppm 4 pH 1 forward NH3 0.1 ppm pH 1 backward pH 1 backward 3 19 s 3 49 s

(%)

2 (%) 60 s

R/R

 1 R/R  1

0 0 0 50 100 150 200 200 240 280 Time (sec) Time (sec)

Figure 7. Reversible and reproducible responses are measured at a constant current (10 6 A) for Figure 7. Reversible and reproducible responses are measured at a constant current (10− −6 A) for PPy-based electrodes. (a) Normalized resistance changes upon sequential exposure to increasing PPy-based electrodes. (a) Normalized resistance changes upon sequential exposure to increasing concentrations of NH3 at diﬀerent pH values. (b) Response and (c) recovery times of PPyNPs toward concentrations of NH3 at different pH values. (b) Response and (c) recovery times of PPyNPs toward 0.1 ppm of NH3 at diﬀerent pH values. (d) Normalized resistance changes of pH 1 based-electrode 0.1 ppm of NH3 at different pH values. (d) Normalized resistance changes of pH 1 based-electrode upon sequential exposure to decrease concentrations of NH3.(e) Response and (f) recovery times of pH upon sequential exposure to decrease concentrations of NH3. (e) Response and (f) recovery times of 1 based-electrode toward 0.1 ppm of NH3, depending on the direction of increase (black) and decrease pH 1 based-electrode toward 0.1 ppm of NH3, depending on the direction of increase (black) and (green) in concentration of NH3. decrease (green) in concentration of NH3. Appl. Sci. 2020, 10, 1850 10 of 13 Appl. Sci. 2020, 10, x FOR PEER REVIEW 10 of 13

(a)

1 ppm 10 ppm 100 ppm 500 ppm 1000 ppm 0

(%)

0 -2

R/R pH 1

 -4 pH 7 MeOH pH 13

0 400 800 1200 Time (sec) (b)

(%) Off

0 Off 2 Off Off Off

R/R

 0

On On On On On

0 400 800 1200 Time (sec)

FigureFigure 8. 8.(a ()a Change) Change in in normalized normalized resistance resistance with with di differentﬀerent MeOH MeOH concentrations. concentrations. (b ()b Calibration) Calibration curvescurves of of PPyNPs PPyNPs as as functions functions of of NH NH3 and3 and MeOH MeOH concentrations; concentrations; black black for for pH pH 1, 1, red red for for pH pH 7, 7, and and blueblue for for pH pH 13. 13. (c ()c Periodic) Periodic exposure exposure of of PPyNPs PPyNPs treated treated at at pH pH 1 to1 to 10 10 ppb ppb of of NH NH3 gas.3 gas.

The selectivity of the sensor electrodes is also important for practical applications. Figure 10 exhibits the variation in the normalized4 pH resistance 1 of the electrodeNH3 0.1 atppm pH 1 upon exposure to various pH 7 volatile gases at low concentrations (1 ppm for NH3 and MeOH; 100 ppm for others). NH3 yields a pH 13 signal change that is more than3 ﬁve times larger when compared to those of the other gases, although its concentration is lower than those of other gases. Therefore, NH3 can be distinguished from other gases based on the extent and direction2 of the resistance change.

Response (%)

0 0 3 6 9 12 15 Time (Day) Appl. Sci. 2020, 10, x FOR PEER REVIEW 10 of 13

(a)

1 ppm 10 ppm 100 ppm 500 ppm 1000 ppm 0

(%)

0 -2

R/R pH 1

 -4 pH 7 MeOH pH 13

0 400 800 1200 Time (sec) (b)

(%) Off

0 Off 2 Off Off Off

R/R

 0

On On On On On

0 400 800 1200 Time (sec)

Figure 8. (a) Change in normalized resistance with different MeOH concentrations. (b) Calibration Appl. Sci.curves2020, 10 of, 1850PPyNPs as functions of NH3 and MeOH concentrations; black for pH 1, red for pH 7, and11 of 13 blue for pH 13. (c) Periodic exposure of PPyNPs treated at pH 1 to 10 ppb of NH3 gas.

4 pH 1 NH3 0.1 ppm pH 7 pH 13 3

Response (%)

0 0 3 6 9 12 15 Appl. Sci. 2020, 10, x FOR PEER REVIEW 11 of 13 Time (Day)

Figure 9. Normalized resistance changes of the electrodes with periodic exposure to 0.1 ppm of NH3 Figure 9. Normalized resistance changes of the electrodes with periodic exposure to 0.1 ppm of NH3 forfor 15 15 days days (black: (black pH: pH 1; 1; red: red: pH pH 7; 7 blue:; blue: pH pH 13). 13).

1 ppm MeOH and NH 8 3 100 ppm Other VOCs

(%) 4

R/R

 0

3 NH DMF Water AcetoneBenzene HexaneToluene Chloroform MeOH -4

Figure 10. Sensing performance histogram of the PPyNPs treated at pH 1 toward diﬀerent oxidizing

andFigure reducing 10. Sensing volatile performance gases. The histogram concentrations of the ofPPyNPs the gases treated are at 1 ppmpH 1 fortoward NH3 differentand MeOH oxidizing and 100and ppm reducing for other vol gases.atile gases. The concentrations of the gases are 1 ppm for NH3 and MeOH and 100 ppm for other gases. 4. Conclusions 4. ConclusionsIn summary, the chemical states of PPyNPs are investigated at various pH levels for application in hazardous-gasIn summary, sensors. the chemical The structure states of of the PPyNPs polymer are chaininvestigated changes at from various the expandedpH levels for to contractedapplication state,in hazardous with an increase-gas sensors. in pH. The The structure nanoparticles of the at pH polymer 1 show chain higher changes electrical from conductivity the expanded (128 S to 1 cmcontracted− ) and larger state diameters, with an than increase those at in other pH. pH The levels, nanoparticles due to an atincrease pH 1 in show the amount higher of electrical charge carriersconductivity (hole) (128 in the S cm chain−1) and structure larger anddiameters the osmotic than those effect at of other the counterpH levels ions., due As to anan NHincrease3 sensing in the transduceramount of material, charge carriers the nanoparticles (hole) in the at pHchain 1 have structure short and response the osmotic and recovery effect of times the ofcounter less than ions. 20 As s andan 50NH s,3 respectively,sensing transducer with high material, sensitivity the nanoparticles (down to 1 ppb) at pH at 251 have◦C. Thus, short the response performance and recovery of the conductivetimes of less nanostructures than 20 s and is 50 optimized s, respectively, through with chemical-state high sensitivity control, (down and to the 1 ppb) proposed at 25 method°C. Thus, can the beperformance effectively applied of the conductive for the development nanostructures of electrical is optimized devices through and sensor chemical systems.-state control, and the proposed method can be effectively applied for the development of electrical devices and sensor Authorsystems. Contributions: W.K. performed the experiments; S.C. conceived and designed the experiments; J.S.L. analyzed the data and wrote the paper. All authors have read and agreed to the published version of the manuscript. Funding:Author Contributions:This research received Wooyoung no external Kim performed funding. the experiments; Sunghun Cho conceived and designed the experiments; Jun Seop Lee analyzed the data and wrote the paper. Acknowledgments: This work was supported by the National Research Foundation of Korea (NRF) grant funded byFunding: Korea government This research (NRF-2018R1C1B5041562). received no external funding. Conflicts of Interest: The authors declare no conflict of interest. Acknowledgments: This work was supported by the National Research Foundation of Korea (NRF) grant funded by Korea government (NRF-2018R1C1B5041562).

Conflicts of Interest: The authors declare no conflict of interest.

References

1. He, Y.; Li, D.; Gao, W.; Yin, H.; Chen, F.; Sun, Y. High-performance NO2 sensors based on spontaneously functionalized hexagonal boron nitride nanosheets via chemical exfoliation. Nanoscale 2019, 11, 21909– 21916. 2. Jannat, A.; Haque, F.; Xu, K.; Zhou, C.; Zhang, B.Y.; Syed, N.; Mohiuddin, M.; Messalea, K.A.; Li, X.; Gras, S.L.; Wen, X.; et al. Exciton-Driven Chemical Sensors Based on Excitation-Dependent Photoluminescent Two-Dimensional SnS. ACS Appl. Mater. Interfaces 2019, 11, 42462−42468. 3. Mi, H.-Y.; Liu, J.-L.; Guan, M.-M.; Liu, Q.-W.; Zhang, Z.-Q.; Feng, G.-D. Fluorescence chemical sensor for determining trace levels of nitroaromatic explosives in water based on conjugated polymer with guanidinium side groups. Talanta 2018, 187, 314–320.

References

1. He, Y.; Li, D.; Gao, W.; Yin, H.; Chen, F.; Sun, Y. High-performance NO2 sensors based on spontaneously functionalized hexagonal boron nitride nanosheets via chemical exfoliation. Nanoscale 2019, 11, 21909–21916. [PubMed] 2. Jannat, A.; Haque, F.; Xu, K.; Zhou, C.; Zhang, B.Y.; Syed, N.; Mohiuddin, M.; Messalea, K.A.; Li, X.; Gras, S.L.; et al. Exciton-Driven Chemical Sensors Based on Excitation-Dependent Photoluminescent Two-Dimensional SnS. ACS Appl. Mater. Interfaces 2019, 11, 42462–42468. [PubMed] 3. Mi, H.-Y.; Liu, J.-L.; Guan, M.-M.; Liu, Q.-W.; Zhang, Z.-Q.; Feng, G.-D. Fluorescence chemical sensor for determining trace levels of nitroaromatic explosives in water based on conjugated polymer with guanidinium side groups. Talanta 2018, 187, 314–320. [PubMed]

4. Kim, W.; Lee, J.S.; Jang, J. Facile synthesis of size-controlled Fe2O3 nanoparticle-decorated carbon nanotubes for highly sensitive H2S detection. RSC Adv. 2018, 8, 31874–31880. 5. Kim, S.G.; Jun, J.; Lee, J.S.; Jang, J. A highly sensitive wireless nitrogen dioxide gas sensor based on an organic conductive nanocomposite paste. J. Mater. Chem. A 2019, 7, 8451–8459. 6. Barbosa, M.S.; Suman, P.H.; Kim, J.J.; Tuller, H.L.; Orlandia, M.O. Investigation of electronic and chemical sensitization effects promoted by Pt and Pd nanoparticles on single-crystalline SnO nanobelt-based gas sensors. Sens. Actuator B-Chem. 2019, 301, 127055. 7. Kekkonen, J.; Finnilä, M.A.J.; Heikkilä, J.; Anttonen, V.; Nissinen, I. Chemical imaging of human teeth by a time-resolved Raman spectrometer based on a CMOS single-photon avalanche diode line sensor. Analyst 2019, 144, 6089–6097. 8. Si, H.; Pan, N.; Zhang, X.; Liao, J.; Rumyantseva, M.N.; Gaskov, A.M.; Lina, S. A real-time on-line photoelectrochemical sensor toward chemical oxygen demand determination based on field-effect transistor

using an extended gate with 3D TiO2 nanotube arrays. Sens. Actuator B-Chem. 2019, 289, 106–113. 9. Cho, S.-Y.; Jang, D.; Kang, H.; Koh, H.-J.; Choi, J.; Jung, H.-T. Ten Nanometer Scale WO3/CuO Heterojunction Nanochannel for an Ultrasensitive Chemical Sensor. Anal. Chem. 2019, 91, 6850–6858. 10. Broza, Y.Y.; Zhou, X.; Yuan, M.; Qu, D.; Zheng, Y.; Vishinkin, R.; Khatib, M.; Wu, W.; Haick, H. Disease Detection with Molecular Biomarkers: From Chemistry of Body Fluids to Nature-Inspired Chemical Sensors. Chem. Rev. 2019, 119, 11761–11817. 11. Piro, B.; Mattana, G.; Noël, V. Recent Advances in Skin Chemical Sensors. Sensors 2019, 19, 4376. 12. Jang, J. Conducting Polymer Nanomaterials and Their Applications. Adv. Polym. Sci. 2006, 199, 189–259. 13. Cho, S.; Lee, J.S.; Joo, H. Recent Developments of the Solution-Processable and Highly Conductive Polyaniline Composites for Optical and Electrochemical Applications. Polymers 2019, 11, 1965. 14. Moon, J.-M.; Thapliyal, N.; Hussain, K.K.; Goyal, R.N.; Shim, Y.-B. Conducting polymer-based electrochemical biosensors for neurotransmitters: A review. Biosens. Bioelectron. 2018, 102, 540–552. 15. Wang, G.; Morrin, A.; Li, M.; Liu, N.; Luo, X. Nanomaterial-doped conducting polymers for electrochemical sensors and biosensors. J. Mater. Chem. B 2018, 6, 4173–4190. 16. Park, S.J.; Park, C.S.; Yoon, H. Chemo-Electrical Gas Sensors Based on Conducting Polymer Hybrids. Polymers 2017, 9, 155. 17. Li, S.; Liu, A.; Yang, Z.; He, J.; Wang, J.; Liu, F.; Lu, H.; Yan, X.; Sun, P.; Liang, X.; et al. Room temperature gas sensor based on tin dioxide@ polyaniline nanocomposite assembled on ﬂexible substrate: Ppb-level

detection of NH3. Sens. Actuator B-Chem. 2019, 299, 126970. 18. Bhadra, J.; Popelka, A.; Abdulkareem, A.; Ahmad, Z.; Touati, F.; Al-Thani, N. Fabrication of polyaniline–graphene/polystyrene nanocomposites for flexible gas sensors. RSC Adv. 2019, 9, 12496–12506. 19. Hassan, G.; Sajid, M.; Choi, C. Highly Sensitive and Full Range Detectable Humidity Sensor using PEDOT: PSS, Methyl Red and Graphene Oxide Materials. Sci. Rep. 2019, 9, 15227. 20. Zhang, Q.; Wang, X.; Fu, J.; Liu, R.; He, H.; Ma, J.; Yu, M.; Ramakrishna, S.; Long, Y. Electrospinning of Ultrafine Conducting Polymer Composite Nanofibers with Diameter Less than 70 nm as High Sensitive Gas Sensor. Materials 2018, 11, 1744. 21. Cho, K.H.; Shin, D.H.; Oh, J.; An, J.H.; Lee, J.S.; Jang, J. Multidimensional Conductive Nanofilm-Based Flexible Aptasensor for Ultrasensitive and Selective HBsAg Detection. ACS Appl. Mater. Interfaces 2018, 10, 28412–28419. [PubMed] Appl. Sci. 2020, 10, 1850 13 of 13

22. Lee, J.S.; Kim, S.G.; Jun, J.; Shin, D.H.; Jang, J. Aptamer-Functionalized Multidimensional Conducting-Polymer Nanoparticles for an Ultrasensitive and Selective Field-Eﬀect-Transistor Endocrine-Disruptor Sensors. Adv. Funct. Mater. 2014, 24, 6145–6153. 23. Lee, J.S.; Kim, W.; Cho, S.; Jun, J.; Cho, K.H.; Jang, J. Multidimensional hybrid conductive nanoplate-based aptasensor for platelet-derived growth factor detection. J. Mater. Chem. B 2016, 4, 4447–4454. 24. Pan, L.; Yu, G.; Zhai, D.; Lee, H.R.; Zhao, W.; Liu, N.; Wang, H.; Tee, B.C.-K.; Shi, Y.; Cui, Y.; et al. Hierarchical nanostructured conducting polymer hydrogel with high electrochemical activity. Proc. Natl. Acad. Sci. USA 2012, 109, 9287–9292.

25. Shen, L.; Huang, X. Tuning the morphologies and electrical properties of azobenzene-4,40-dicarboxylate-doped polypyrrole via ultraviolet light irradiation and medium pH alteration. Polymers 2019, 176, 188–195. 26. Santino, L.M.; Diao, Y.; Yang, H.; Lu, Y.; Wang, H.; Hwang, E.; D’Arcy, J.M. Vapor/liquid polymerization of ultraporous transparent and capacitive polypyrrole nanonets. Nanoscale 2019, 11, 12358–12369. 27. Hea, W.; Zhao, G.; Sun, P.; Hou, P.; Zhu, L.; Wang, T.; Lib, L.; Xu, X.; Zhai, T. Construction of Longan–like hybrid structures by anchoring nickel hydroxide on yolk–shell polypyrrole for asymmetric supercapacitors. Nano Energy 2019, 56, 207–215. 28. Tang, X.; Raskin, J.-P.; Kryvutsa, N.; Hermans, S.; Slobodian, O.; Nazarovc, A.N.; Debliquy, M. An ammonia sensor composed of polypyrrole synthesized on reduced graphene oxide by electropolymerization. Sens. Actuator B-Chem. 2020, 305, 127423. 29. Domínguez-Renedo, O.; Navarro-Cuñado, A.M.; Arnáiz-Lozano, V.; Alonso-Lomillo, M.A. Molecularly imprinted polypyrrole based electrochemical sensor for selective determination of 4-ethylphenol. Talanta 2020, 207, 120351. 30. Jun, J.; Oh, J.; Shin, D.H.; Kim, S.G.; Lee, J.S.; Kim, W.; Jang, J. Wireless, Room Temperature Volatile Organic Compound Sensor Based on Polypyrrole Nanoparticle Immobilized Ultrahigh Frequency Radio Frequency Identification Tag. ACS Appl. Mater. Interfaces 2016, 8, 33139–33147. 31. Camurlu, P. Polypyrrole derivatives for electrochromic applications. RSC Adv. 2014, 4, 55832–55845. 32. Patil, A.O.; Heeger, A.J.; Wudl, F. Optical Properties of Conducting Polymers. Chem. Rev. 1988, 88, 183–200. 33. Arjomandi, J.; Shah, A.-u.-H.A.; Bilal, S.; Hoang, H.V.; Holze, R. In situ Raman and UV–vis spectroscopic studies of polypyrrole and poly(pyrrole-2,6-dimethyl-β-cyclodextrin). Spectroc. Acta Pt. A-Molec. Biomolec. Spectr. 2011, 78, 1–6. 34. Santos, M.J.L.; Brolo, A.G.; Girotto, E.M. Study of polaron and bipolaron states in polypyrrole by in situ Raman spectroelectrochemistry. Electrochim. Acta 2007, 52, 6141–6145. 35. Nguyen Thi Le, H.; Bernard, M.C.; Garcia-Renaud, B.; Deslouis, C. Raman spectroscopy analysis of polypyrrole films as protective coatings on iron. Synth. Met. 2004, 140, 287–293. 36. Carrasco, P.M.; Cortazar, M.; Ochoteco, E.; Calahorra, E.; Pomposo, J.A. Comparison of surface and bulk doping levels in chemical polypyrroles of low, medium and high conductivity. Surf. Interface Anal. 2006, 39, 26–32. 37. Joo, J.; Lee, J.K.; Lee, S.Y.; Jang, K.S.; Oh, E.J.; Epstein, A.J. Physical Characterization of Electrochemically and Chemically Synthesized Polypyrroles. Macromolecules 2000, 33, 5131–5136. 38. Li, Y.; He, G. Effect of preparation conditions on the two doping structures of polypyrrole. Synth. Met. 1998, 94, 127–129. 39. Cheah, K.; Forsyth, M.; Truong, V.-T. Ordering and stability in conducting polypyrrole. Synth. Met. 1998, 94, 215–219.

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