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Article

Preparation of Reduced Graphene Oxide Sheets with Large Surface Area and Porous Structure for High-Sensitivity Humidity Sensor

by
Seo Jin Kim
,
Hong Jun Park
,
Eun Seop Yoon
and
Bong Gill Choi
*
Department of Energy Resources and Chemical Engineering, Kangwon National University, Samcheok 25913, Republic of Korea
*
Author to whom correspondence should be addressed.
Chemosensors 2023, 11(5), 276; https://doi.org/10.3390/chemosensors11050276
Submission received: 7 April 2023 / Revised: 30 April 2023 / Accepted: 2 May 2023 / Published: 4 May 2023
(This article belongs to the Special Issue Recent Advances in Electrochemical Biosensors for Agricultural, Biological, and Environmental Applications)
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Abstract

:
Humidity sensors provide environmental conditions suitable for several applications. However, they suffer from a limited reliable range originating from the low electrical conductivity and low water-sensitive sites of humidity-sensing materials. In this study, we developed high-sensitivity humidity sensors based on holey-reduced graphene oxide (HRGO) with a large surface area (274.5 m2/g) and an abundant pore structure. HRGO was prepared via the H2O2-etching-reaction-assisted hydrothermal processing of graphene oxide sheets. The resulting humidity sensor exhibited high sensitivity (−0.04317 log Z/%RH, R2 = 0.9717), a fast response time (<3 s), and long-term stability over 28 days. The impedance responses of the humidity sensor were almost similar between the mechanically standard and bent states. Furthermore, electrochemical impedance spectroscopy was performed to understand the humidity-sensing mechanism of the HRGO materials.

1. Introduction

Humidity (commonly expressed as relative humidity, RH) is a significant environmental parameter in various fields, including agriculture, industry, and health care [1,2,3]. Over the past few decades, humidity sensors have been extensively developed to achieve high sensitivity, fast response times, repeatability, and stability [4,5]. According to their sensing methods, humidity sensors are generally categorized into different types based on various parameters such as resistance [6,7], impedance [8,9], optical properties [10,11], surface acoustic waves [12,13], and quartz crystal microbalances [14,15]. In particular, impedance humidity sensors using an alternating electrical current (AC) have attracted significant attention owing to their high responsiveness, accurate detection, and simple structures. An impedance humidity device is mainly composed of a substrate, electrodes, and humidity-sensing materials. The sensor detects environmental humidity by measuring the variation in impedance while water molecules absorb and desorb on the surface of sensing materials under a sinusoidal voltage. Impedance-type humidity sensors have good sensitivity; however, these devices still require a fast response speed, high sensitivity at a low level of humidity, and stability during long-term measurement for various applications [16,17].
Humidity-sensing materials are crucial components for the improvement of sensing performance owing to their active interaction sites with water molecules [18,19]. To date, several humidity-sensitive materials, including metals (e.g., MnO2, SiO2, TiO2, ZnO2, and Mxene) [20,21,22,23], conducting polymers [24,25,26], and carbon materials [27,28,29], have been intensively explored to achieve high sensitivity and a wide detection range. Metal-based materials have excellent electrical conductivity, which enables the detection of water molecules at a low levels of humidity. Despite their humidity-sensing properties, metal-based materials’ intrinsically high cost and corrosion issues limit their practical applications [30,31]. Conductive polymers with hydrophilic functional groups have been used as humidity-sensitive materials because of their low cost, good sensitivity, and simple processability; however, their poor conductivity and stability should be improved [32,33]. Carbon materials have been widely studied in electronics owing to their mechanical and chemical stability and cost-effectiveness [34,35]. Among carbon-type materials, graphene (Gr) nanosheets have outstanding mechanical and electrical properties resulting from their stable lattice structure, which allows humidity sensors to respond highly sensitively to water molecules under low-humidity conditions [36,37]. However, pristine Gr with fewer functional groups, such as oxygen, which interacts with water molecules, exhibits insufficient water sensitivity at high humidity. As the presence of an oxygen group provides better sensitivity than those without this moiety, graphene oxide (GO) or reduced graphene oxide (RGO) has been used as a humidity sensor. To date, although a number of GO- and RGO-based humidity sensors have been developed [38,39,40,41], the sensing performance, including sensitivity, hysteresis, and response/recovery time, still needs to be improved for many applications of humidity sensors. GO has abundant oxygen groups that enable the adsorption of water molecules. However, the intrinsic insulation characteristics of GO restrict the formation of pathways for ions and charges, leading to a decrease in sensor performance [42,43]. Compared to those based on GO, RGO materials obtained via the reduction of GO exhibit enhanced electrical conductivity. However, the reduced oxygenated functional groups of RGO compared to GO limit their linear sensitivity in a wide RH range for humidity sensors [44].
In this study, we prepared holey RGO (HRGO) nanosheets with higher surface area (274.5 m2/g) and more abundant oxygenated groups than RGO sheets via a H2O2-etching-reaction-assisted hydrothermal method applied to graphene oxide (GO) to enable its use as a high-sensitivity humidity sensor. The humidity sensor was fabricated by depositing HRGO sheets onto the gap surface of two identical gold (Au) electrodes. The resulting HRGO-based humidity sensor (HR-sensor) exhibited high and linear sensitivity of 0.0432 log Z/%RH with an R2 = 0.97 in a range of RH 11–97%, a fast response time (<3 s), good repeatability (<2.5%), and excellent long-term stability over 28 days. The HR-sensor also maintained stable sensing signals under mechanical bending deformations. Furthermore, we validated the humidity-sensing mechanism of HR-sensor using an electrochemical impedance spectroscopy (EIS) under a humidity range of 11–97%.

2. Materials and Methods

2.1. Materials

Graphite (particle size ≤ 20 μm), potassium persulfate (K2S2O8), phosphorus pentoxide (P2O5), potassium permanganate (KMnO4), hydrogen peroxide (H2O2), and sodium sulfate (Na2SO4) were purchased from Sigma-Aldrich (St. Louis, MO, USA). To condition different RH levels based on saturated salt solutions, lithium chloride (11% RH, LiCl; SAMCHUN, Pyeongtaek, Republic of Korea), magnesium chloride (33% RH, MgCl2; Sigma-Aldrich, St. Louis, MO, USA), magnesium nitrate (52% RH, Mg(NO3)2; Junsei, Kyoto, Japan), copper (Ⅱ) chloride (67% RH, CuCl2, Junsei, Kyoto, Japan), and potassium chloride (85% RH, KCl; Sigma-Aldrich, St. Louis, MO, USA) were used. Potassium sulfate (97% RH, K2SO4) was purchased from Sigma-Aldrich (St. Louis, MO, USA), and sulfuric acid (H2SO4) and hydrochloric acid (HCl) were obtained from DAEJUNG Chemical Co. (Siheung-si, Republic of Korea). Deionized (DI) water was purified using a Milli-Q unit (normalized electrical resistivity: 18.2 MΩ cm, Millipore system, Darmstadt, Germany) to prepare all aqueous solutions and wash the samples.

2.2. Preparation and Characterization of HRGO

Graphene oxide was prepared by oxidizing graphite powder according to the modified Hummers method [45]. Graphite powder was dispersed in 10 mL of H2SO4 containing K2S2O8 (2 g) and P2O5 (2 g) at 85 °C for 5 h to obtain pre-oxidized graphite. The resultant solution was cooled by gradually adding 500 mL of DI water and left overnight. The mixture was washed with DI water under vacuum filtration, which was followed by drying under vacuum at room temperature. The pre-treated graphite powder was added to H2SO4 (100 mL) in an ice bath, and KMnO4 was added and magnetically stirred with the suspension under 300 rpm at 35 °C overnight. Afterward, 1 L of DI water was used to wash the mixture, and 30 mL of H2O2 was added to the resulting mixture. The mixture was centrifuged at 450× g for 30 min, and the resulting product was sequentially washed using HCl (10 wt%) and DI water to obtain graphite oxide. Ultrasonication was employed for 30 min to exfoliate graphite oxide layers, which was followed by vacuum filtration and freeze-drying for 3 days to obtain GO sheets. GO sheets (100 mg) were dispersed in a solution of DI water (35 mL) and H2O2 (15 mL) via magnetic stirring for 10 min and then sealed in a Teflon-lined autoclave and heated to 180 °C for 6 h. The as-obtained HRGO hydrogel was washed with DI water and ethanol to remove any residual solvent that may have been present on the surface of the HRGO sheets; this process was repeated three times. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) were conducted using a field-emission scanning electron microscope (S-4800, HITACHI, Tokyo, Japan) to investigate the Gr sheets’ morphology. Brunauer–Emmett–Teller (BET) measurements were performed using an ASAP 2010 surface area analyzer (Micromeritics, Norcross, GA, USA) with nitrogen adsorption and desorption techniques to determine the surface structure and the surface area of the Gr sheets. The chemical compositions of RGO and HRGO were determined via Fourier-transform infrared (FT-IR) KBr pellet methodology spectroscopy (JASCO FT-IR 4600, JASCO, Tokyo, Japan). Approximately 1 mg of Gr powder was mixed with 200 mg of KBr via manual grinding with an agate grinding mill. KBr-based pellets were produced by pressing the as-ground powder. Fourteen scans were performed for RGO and HRGO samples, and the results were averaged.

2.3. Fabrication and Characterization of HR-Sensor

The HR-sensor has a configuration consisting of two identical gold (Au) electrodes (electronic conductive paths) and water-sensitive sites (ionic conductive paths), as illustrated in Figure 1a. For the HR-sensor, the as-prepared HRGO sheets were dispersed in a mixture of ethanol and DI water at a certain volume ratio (7:3) to avoid the induction of the coffee ring effect and to serve as a water-sensing material. Subsequently, the HRGO dispersion (10 µL) was drop-casted onto the surface between the Au electrodes and then vacuum-dried overnight at room temperature to form sensing layers. At the same time, RGO was utilized as the control sample to compare and contrast the effects of HRGO sheets on a humidity sensor. Electrical double-layer capacitance (EDLC) was determined via a cyclic voltammetry (CV) technique using an electrochemical workstation (CHI 760E, CH Instruments Inc., Bee Cave, TX, USA). HRGO and RGO were used as working electrodes in this experiment, while a platinum wire and Ag/AgCl electrode (CHI 111, CH Instrument Inc., Bee Cave, TX, USA) filled with saturated KCl solution were used as counter and reference electrodes, respectively. The electrolyte used was a 1 M H2SO4 solution. To determine EDLC, the electrical potential was scanned from 0 to 1 V at a scan rate of 50 mV/s. Different humidity levels were prepared by saturating the salt solutions [46]. Controlled humidity environments were prepared by adding LiCl (RH 11%, 100 g), MgCl2 (RH 33%, 80 g), Mg(NO3)2 (RH 52%, 100 g), CuCl2 (RH 67%, 100 g), KCl (RH 85%, 50 g), or K2SO4 (RH 97%, 50 g) into a closed glass vessel filled with 100 mL of DI water while heating it to 80 °C to dissolve the salts. The resulting solution was then cooled to 25 °C to reach equilibrium and obtain the desired humidity levels for the humidity sensor measurement. The uncertainty of the RH levels was within 1%. The current–voltage (I–V) curve for HRGO was obtained within a potential range of −0.5 to 0.5 V to determine the working voltage amplitude. HR-sensor was aged by applying AC with a frequency of 100 Hz and a sinusoidal amplitude of 1 V for 24 h under a high humidity level of 97% to facilitate stable and reliable sensing measurements. Calibration curves for HR- and R-sensors were obtained by measuring the change in impedance in the humidity range of 11–97%. A mechanical deformation test was also performed on the HR-sensor. The test involved measuring the impedance variations at different humidity levels ranging from 11% to 97% in both normal and bent states for the HR sensor, and the results were compared. A hysteresis error test for the HR sensor was performed by recording impedance variation with an increase and decrease in humidity levels from 11% to 97%. Response and recovery times were obtained by measuring impedance changes while alternating humidity levels from 11% to 97% until the equilibrium value of 90% conversion was reached. These tests were repeated two times and the same results were obtained. The long-term stability of the HR-sensor was tested by observing impedance deviation at different RH levels, namely, 11, 33, 52, 67, 85, and 97%, every seven days over a period of 28 days. To demonstrate the sensing mechanism of the humidity sensor, EIS was performed using an electrochemical workstation (CHI 760E) employing a two-electrode setup and using HRGO as the working and reference electrodes. The frequency was changed from 10 to 100 kHz, applying an AC voltage of 0.5 V and a direct current voltage of 0 V under high (more than 52%), normal, and low (less than 52%) RH levels. All statistical analyses and graphing procedures were carried out using Microsoft Excel and Sigma-Plot (version 12.0) software. Sensing performance was determined by determining the average of five measurements for each of the three humidity sensors.

3. Results and Discussion

A schematic of the HR-sensor’s preparation is shown in Figure 1a. HRGO was synthesized via the hydrothermal reduction of GO and H2O2 etching reactions, which were performed according to a previously reported method. The use of H2O2 enabled the etching of the surface of the GO sheets, resulting in a pore structure in the basal plane. The as-obtained HRGO was deposited onto the Au surface of a two-electrode substrate to fabricate the HRGO-based humidity sensor (HR-sensor). Figure 1b reveals that the ultra-thin HRGO sheet has abundant nanopores in the range of 4–10 nm. In contrast, no pore structure was observed in the RGO sheet obtained from the hydrothermal reduction of GO in the absence of H2O2 (Figure 1c). Notably, HRGOs can be dispersed in an aqueous solution because of their residual oxygenated functional groups (Figure S1).
Nitrogen adsorption–desorption analysis was performed on HRGO and RGO to investigate their pore structures and specific surface areas. Figure 2a shows a typical type II isotherm and a well-developed hysteresis loop for the HRGO and RGO flakes. The specific surface areas for HRGO and RGO, which were evaluated based on a BET method, were 274.5 and 146.5 m2/g, respectively. The higher BET area of HRGO compared to that of RGO is attributed to the abundant pore structures of HRGO. Figure 2b shows the pore distributions for HRGO and RGO based on Barrett–Joyner–Halenda (BJH) analysis of their isotherm curves. HRGO exhibited a narrow pore size distribution in the range of 1.74–85.81 nm, with an average pore size of 9.72 nm STD. These findings suggest that the HRGO synthesis process successfully generates pore structures with increased surface area, which allows for enhanced sensitivity to water molecules.
EDLC is used to investigate electrochemically active areas, which are indicative of high-sensitivity performance. The higher electrochemical activity of HRGO compared to that of RGO was determined using the CV method (Figure 3). HRGO exhibited a higher CV area than RGO, which was measured in the potential range of 0–1 V at a scan rate of 50 mV/s in 1 M H2SO4 solution. The CV area is related to the electrical capacitive behavior of carbon-based electrode materials and depends primarily on a material’s surface area and pore structure. This indicates that HRGO had a higher active surface area than RGO. The superior textural properties of HRGO compared with RGO are favorable for the adsorption of water molecules in humidity sensors. The FT-IR spectra were analyzed to verify the functional groups of HRGO and RGO (Figure 4). The peak around 2300 cm−1 is related to the presence of carbon dioxide (CO2) in the atmosphere [47]. In addition, the peaks around 1509 cm−1 and 1648 cm−1 correspond to C=C and C=O vibrations [48,49]. Compared with the bands of RGO, HRGO had more oxygenated functional groups because of the nanopore defects of HRGO.
The humidity-sensing performance of the HR- and RGO-sensors (R-sensor) was systematically investigated by measuring the impedance changes under different RH atmospheres (ranging from RH 11% to 97%) that were controlled using saturated salt solutions (Figure S2). The saturated salt solution measurement is a simple and straightforward method for controlling and maintaining desired humidity conditions. This method is based on the principle of the one-degree-of-freedom in-phase rule, which allows for the precise control of RH levels [46]. When water molecules are adsorbed on the surface of water-sensitive materials, they serve as charge carriers, leading to changes in the electrical impedance of the humidity sensors. The selection of the appropriate AC voltage amplitude is a compromise between maximizing linear response (with a small amplitude) and the signal-to-noise ratio (with a large amplitude) in EIS measurements [50]. Impedance-type humidity sensors include highly insulative sensing layers and operate under non-aqueous electrolytes. These conditions result in low conductivity, leading to a high level of noise. Thus, a high AC voltage amplitude is suitable for attaining a reliable electrical signal for the sensors [17,51]. I–V characterization was performed to determine a linear AC voltage amplitude in a potential range of −0.5 V to 0.5 V. Figure S3 shows a linear slope of I–V responses, which is indicative of steady-state values. Once again, the input signal frequency is equal to that of the output signal. Based on this result, we selected an AC voltage magnitude of 0.5 V to obtain linearity and a sufficient signal-to-noise ratio. Figure 5 shows the typical impedance variations of the R- and HR-sensors measured at a frequency of 100 Hz in the RH range of 11–97%. In this range, the HR-sensor had a high degree of impedance variation of 3.46 orders of magnitude, which is 1.25-fold higher than that of the R-sensor (2.76 orders). Compared to the non-linear curve for the R-sensors, the HR-sensor exhibited a more linear curve. The HR-sensor exhibited a high R2 value of 0.9717 in the RH range of 11 to 97%. The sensing response value (S), which is the ability to detect water molecules effectively, was calculated from the impedance plot in Figure 5 according to the following equation [52]:
S = ZL/ZH
where ZL is the impedance under low humidity, and ZH is the impedance under high humidity. The HR-sensor had an S value of 2876.59 in the RH 11–97% range, which was five-fold higher than that of the R-sensor (576.95).
The flexibility of humidity sensors is required for practical applications in respiratory, non-contact, speech, and skin moisture sensors [53,54]. To demonstrate the combined mechanical and sensing performance, the sensitivity of HRGO was compared with two different mechanical deformations of the normal and bent states (Figure 6). The bent HR-sensor with a bending radius of 30° exhibited a linear curve (R2 = 0.9617) in a range of RH 11–97% and sensitivity of −0.04302 log Z/%RH. The impedance responses and sensitivity values of the bent HR-sensor are similar to those of the mechanically normal HR-sensor (−0.04317 log Z/%RH). This result indicates that the HR-sensor holds promise for use in wearable applications.
The sensing hysteresis of humidity sensors is an important parameter for obtaining reliable measurements. The hysteresis of the HR-sensor was investigated by measuring the impedance changes with increasing and decreasing RH levels from 11 to 97% (Figure 7). The hysteresis error was calculated using the following equation [52]:
Hysteresis error = △Zmax/ZFS × 100%
where △Zmax is the maximal impedance difference between the water adsorption and desorption processes at the same RH level, and ZFS is the impedance variation measured in the full-scale RH range. The hysteresis error of the HR-sensor was 2.57%, which was lower than that of the previously reported RGO-based humidity sensors [55,56].
Response and recovery times are crucial parameters for evaluating the efficacy of humidity sensors. These times were defined as the time taken to reach 90% of the steady impedance value in the adsorption and desorption processes, respectively (Figure 8). The HR-sensor exhibited a fast response time of less than 3 s and a good recovery time of 29 s, which are comparable to those of other humidity sensors [57,58]. When the humidity condition changes, water molecules are adsorbed and desorbed on the surface of the HRGO sheets to reach adsorption and desorption equilibria. The water molecules require time to enter and exit the layers of the HRGO sheets, and this process determines the hysteresis error and response/recovery time. The low hysteresis and quick response/recovery times observed are attributed to its hydrophilic functional groups and pore structure, which allow water molecules to transfer freely.
Figure 9 shows that the long-term stability of the HR-sensor was tested by measuring the impedance variations in a closed glass container with 11, 33, 52, 67, 85, and 97% RH levels over 28 days. Slight changes in impedance were observed over time, indicating the good stability and durability of the HR-sensor when exposed to prolonged periods of various humidity conditions. The maximum sensitivity variation for the HR-sensor was 1.98% at RH 11%, resulting in excellent long-term stability. This remarkable performance is ascribed to the sturdy HRGO framework, which effectively immobilizes water molecules within its porous structure without undergoing dissolution from the adsorbed water molecules.
The obtained sensing performance values of HRGO were superior or comparable to those of previously reported RGO-based humidity sensors (Table 1).
EIS was performed to analyze the conduction mechanism of the humidity sensor. Figure 10 shows typical Nyquist plots for the HR- and R-sensors measured at an RH level of 52% in the frequency range from 100 kHz to 10 Hz with a sinusoidal amplitude of 0.5 V. In typical impedance spectra, the horizontal axis represents the real component of impedance, which is related to resistance. In contrast, the vertical axis represents the imaginary component of impedance, which is related to capacitive and inductive reactance. The total impedance is calculated by summing the vectors of resistance and reactance. When EIS measurements were taken at the RH level of 52% (Figure 10a) for two sensors, the R-sensor had a large impedance semicircle plot, and the HR-sensor exhibited a smaller semicircle connected with a short straight line at a low-frequency range. The semicircle of the R-sensor was attributed to the intrinsic impedance of the RGO-sensing film, which can be modeled using an equivalent parallel circuit of a resistor (R) and a capacitor (Cdl) (Figure 10b). The absorbed water molecules on the surface of the RGO were insufficient for forming continuous pathways for ion and electron conduction. According to the equivalent circuit model for the HR-sensor (Figure 10c), the short tail impedance of the HR-sensor is related to the Warburg impedance (Zw), indicating the diffusion process of ion and charge transfer at the interface of the sensing material and the electrode. Compared to the R-sensor, a greater number of water molecules were adsorbed and accumulated on the surface of HRGO at the same RH level, resulting in enhanced association and dissociation of water molecules on the surface of HRGO. At the RH level of 52%, the impedance of the R-sensor was dominated by the contribution of RGO film conduction, while the polarization and diffusion of water molecules mainly contributed to the impedance of the HR-sensor. This result is attributed to the greater abundance of oxygenated groups in HRGO compared to RGO.
The conduction mechanism of the HR-sensor was intensively studied using EIS measurements at different RH levels, namely, 11, 33, 52, 67, 85, and 97%. At low RH levels of 11 and 33%, the Nyquist plots for the HR-sensor showed large semicircles (depicted in Figure 11), which are represented by a parallel circuit consisting of R (the resistance of the sensing film) and Cdl (the capacitance of the sensing film) [56,67]. Only a few water molecules were physically adsorbed onto the hydrophilic groups of the HRGO’s surface in the low-RH regime. The resistor’s properties are related to H3O+, and the capacitor was mainly dominated by proton conductivity [38]. The hopping transfer of protons between humidity-sensitive sites requires high energy to circumvent the resistance of hydrogen bonding, resulting in a relatively high level of impedance. Thus, the large impedance semicircles result from the intrinsic resistance and capacitance of the HRGO sensing film.
As the RH level increased to 52%, the semicircular arcs gradually constricted and became a straight line. The inclined line represents the Warburg impedance (Zw), which was established by the diffusion of ions (H3O+) between the sensing film and the electrode. Based on an equivalent circuit (Figure 12), the contribution of the resistance and capacitance of the HRGO sensing film reduces, while the polarization and diffusion of physisorbed water molecules become dominant. At high RH levels (>52%), physisorbed water molecules produced continuous water layers and accelerated H3O+ transfer based on a Grotthuss chain reaction (H2O + H3O+ → H3O+ + H2O), leading to a significant decrease in the intrinsic resistance of HRGO film (Figure 12). Under these high-humidity conditions, the humidity-sensing mechanism is attributed to the hopping effect of H3O+ and H+ ions in liquid-like physisorbed water layers. The semicircle disappears at a very high humidity of 97% RH; at this level, only a straight line is observed. The electrolytic conductivity rather than protonic conductivity mainly contributes to the impedance of the sensor [68]. This indicates that the resistance and capacitance of the sensor at high RH levels are attributed to the association and dissociation polarization between absorbed water molecules and the oxygenated groups of HRGO. Table S1 summarizes the parameters of the equivalent circuit for the HR-sensor at different RH levels; the results in the table were obtained by fitting the impedance spectra data using the software ZSimpWin. As the RH level increases, the resistance values decrease while the capacitance values increase. The physisorbed water molecules lead to a decrease in the intrinsic impedance of the HRGO sensing film. The polarization of absorbed water molecules on the HRGO’s surface is responsible for the increase in the capacitance applied in an electric field.

4. Conclusions

We successfully prepared holey-structured and reduced graphene oxide (HRGO) nanosheets as sensing materials in humidity sensors. The as-obtained HRGO had a large surface area (274.5 m2/g) and exhibited high electrochemical capacitance. The HR-sensor exhibited high sensitivity performance (−0.04317 log Z/%RH, R2 = 0.9717) under high and low humidity levels, and this finding is comparable to previously reported results. Compared to the R-sensor based on non-porous RGO sheets, the HR-sensor had a more linear sensitivity curve and a higher regression coefficient because of its abundant nanopores and large surface area. In addition, the sensitivity of the HR-sensor was retained under a mechanically bent state, indicating good combined mechanical and electrochemical performance. Further electrochemical measurements demonstrated good sensing performance of the HR-sensor, including a fast response time (<3 s), good repeatability, good long-term stability, and stable sensing signals under bending deformation. To understand the sensor’s humidity-sensing mechanism, we performed EIS over a wide RH range of 11 to 97%.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/chemosensors11050276/s1, Figure S1: Photographic image for HRGO sheets dispersed in DI water after a day, Figure S2: Illustration for saturated salt solution measurement, Figure S3: The current-voltage (I–V) curve for HRGO to determine the working voltage amplitude, Table S1: Parameter values of the equivalent circuit for HR-sensor at different RH levels.

Author Contributions

Conceptualization, B.G.C.; investigation, S.J.K. and H.J.P.; data curation, S.J.K., H.J.P. and E.S.Y.; writing—original draft, S.J.K., H.J.P. and B.G.C.; writing—review and editing, B.G.C.; supervision, B.G.C. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Research Foundation of Korea (NRF) Grant funded by the Ministry of Science and ICT (No. 2021R1A2C1009926), the Nanomedical Devices Development Project of NNFC in 2023, and the Technology Innovation Program (20015577) funded by the Ministry of Trade, Industry, and Energy (MOTIE, Korea).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The datasets used and/or analyzed during the current study will be made available by the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. (a) Schematic of the preparation of HRGO using the etching reaction of GO and HR-sensor with two-electrode configurations. High-resolution TEM images of (b) RGO and (c) HRGO sheets.
Figure 1. (a) Schematic of the preparation of HRGO using the etching reaction of GO and HR-sensor with two-electrode configurations. High-resolution TEM images of (b) RGO and (c) HRGO sheets.
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Figure 2. (a) Nitrogen adsorption and desorption BET isotherm and (b) pore size distribution for HRGO (red line) and RGO sheets (black line).
Figure 2. (a) Nitrogen adsorption and desorption BET isotherm and (b) pore size distribution for HRGO (red line) and RGO sheets (black line).
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Figure 3. CV curves for HRGO (red line) and RGO (black line) measured at a scan rate of 50 mV/s in 1 M H2SO4 with a potential window of 0 to 1 V.
Figure 3. CV curves for HRGO (red line) and RGO (black line) measured at a scan rate of 50 mV/s in 1 M H2SO4 with a potential window of 0 to 1 V.
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Figure 4. FT-IR spectra for HRGO (red line) and RGO sheets (black line).
Figure 4. FT-IR spectra for HRGO (red line) and RGO sheets (black line).
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Figure 5. Impedance variations in humidity range of 11 to 97% for HR- (red line) and R-sensors (black line).
Figure 5. Impedance variations in humidity range of 11 to 97% for HR- (red line) and R-sensors (black line).
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Figure 6. Calibration plots for the HR-sensor under normal (black line) and bent (red line; a radius of 30°) conditions with relevant regression (dotted lines) in an RH range from 11% to 97%.
Figure 6. Calibration plots for the HR-sensor under normal (black line) and bent (red line; a radius of 30°) conditions with relevant regression (dotted lines) in an RH range from 11% to 97%.
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Figure 7. Relative humidity hysteresis error test for the HR-sensor with an increase (black line) and decrease (red line) in an RH range from 11% to 97%.
Figure 7. Relative humidity hysteresis error test for the HR-sensor with an increase (black line) and decrease (red line) in an RH range from 11% to 97%.
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Figure 8. Response (red dots) and recovery time (black dots) for the HR-sensor with an increase and decrease in RH levels between 97% and 11% for 200 s each.
Figure 8. Response (red dots) and recovery time (black dots) for the HR-sensor with an increase and decrease in RH levels between 97% and 11% for 200 s each.
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Figure 9. Long-term stability test for the HR-sensor in different RH regions of 11, 33, 52, 67, 85, and 97% over a period of 28 days.
Figure 9. Long-term stability test for the HR-sensor in different RH regions of 11, 33, 52, 67, 85, and 97% over a period of 28 days.
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Figure 10. (a) Nyquist plots for R- and HR-sensors measured at a frequency range from 100 kHz to 10 Hz (with a sinusoidal voltage amplitude of 0.5 V) at a normal RH level of 52% for RGO (black line) and HRGO (red line and inset graph showing an enlarged view at the same frequency range); Corresponding equivalent circuits for (b) R- and (c) HR-sensors.
Figure 10. (a) Nyquist plots for R- and HR-sensors measured at a frequency range from 100 kHz to 10 Hz (with a sinusoidal voltage amplitude of 0.5 V) at a normal RH level of 52% for RGO (black line) and HRGO (red line and inset graph showing an enlarged view at the same frequency range); Corresponding equivalent circuits for (b) R- and (c) HR-sensors.
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Figure 11. Illustration of humidity-sensing mechanism between water molecules and HRGO sheets with the corresponding equivalent circuit and Nyquist curves at a frequency range of 100 kHz to 10 Hz under low-to-normal RH levels of 11, 33, and 52%.
Figure 11. Illustration of humidity-sensing mechanism between water molecules and HRGO sheets with the corresponding equivalent circuit and Nyquist curves at a frequency range of 100 kHz to 10 Hz under low-to-normal RH levels of 11, 33, and 52%.
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Figure 12. Illustration of humidity-sensing mechanism between a greater number of water molecules and HRGO sheets with the corresponding equivalent circuit and Nyquist curves at frequencies of 100 kHz and 10 Hz under high RH levels of 52, 67, 85, and 97%.
Figure 12. Illustration of humidity-sensing mechanism between a greater number of water molecules and HRGO sheets with the corresponding equivalent circuit and Nyquist curves at frequencies of 100 kHz and 10 Hz under high RH levels of 52, 67, 85, and 97%.
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Table
Table 1. Comparison of our HR-sensor with other reported humidity sensors.
Table 1. Comparison of our HR-sensor with other reported humidity sensors.
Sensing MaterialTypeWorking Range (% RH)SensitivityHysteresisResponse/Recovery Time (s)Ref.
GO/LIGC11–979.15 nF/%RH3.3%2/49[38]
GOC10–903.25 nF/%RH--/15.8[39]
RGOI11–95-9%16/47[40]
RGOI30–900.0423 log Z/%RH2.5%28/48[41]
nRGOR6.1–664.51%--[59]
PDDA/RGOR11–978.69–37.43%-94/108[60]
rGO:MoS2R30–800.973 kΩ/% RHLess than 1%240/900[7]
rGO-BiVO4I11–95–0.47%3.6/18[17]
rGO-SCI11–95–4.56%1.3/23.5[52]
CS-MWCNTR30–10010.35 Ω/% RH0.30 ± 0.001%30/40[61]
GO/NWFR44–91––8.9/11.76[62]
rCMGOR0–1000.33 MΩ/% RH1.1%0.025/0.125[43]
GO-NH2/mSiO2R23–9714.6 MΩ/% RH2.71%12.6/58.5[63]
GQDs prepared from wasteI40–90–2.2%15/55[64]
CS/AC (Chitosan/Activated carbon)V0–97––22/21[65]
MXene-GOR3–80–0.52x + 50.915.5%5/19[66]
HRGOI11–97−0.04317 log Z/%RH2.57%3/29This work
LIG; laser-induced graphene, nRGO; nitrogen-doped reduced graphene oxide, SC; 4-chloro-3-sulfophenylazo, MWCNT; multi-walled carbon nanotube, NWF; non-woven fabric, rCMGO; chemically modified RGO, GQDs; graphene quantum dots, CS; chitosan, AC; activated carbon, R; Resistance, I; Impedance, V; Voltage.
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Kim, S.J.; Park, H.J.; Yoon, E.S.; Choi, B.G. Preparation of Reduced Graphene Oxide Sheets with Large Surface Area and Porous Structure for High-Sensitivity Humidity Sensor. Chemosensors 2023, 11, 276. https://doi.org/10.3390/chemosensors11050276

AMA Style

Kim SJ, Park HJ, Yoon ES, Choi BG. Preparation of Reduced Graphene Oxide Sheets with Large Surface Area and Porous Structure for High-Sensitivity Humidity Sensor. Chemosensors. 2023; 11(5):276. https://doi.org/10.3390/chemosensors11050276

Chicago/Turabian Style

Kim, Seo Jin, Hong Jun Park, Eun Seop Yoon, and Bong Gill Choi. 2023. "Preparation of Reduced Graphene Oxide Sheets with Large Surface Area and Porous Structure for High-Sensitivity Humidity Sensor" Chemosensors 11, no. 5: 276. https://doi.org/10.3390/chemosensors11050276

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