Graphene Nanoribbons/Manganese Oxide Nanocomposite Modified Electrode for Detection of Antimicrobial Drug Nitrofurantoin

Nagarajan, Ramila D.; Magesh, Vasanth; Sundramoorthy, Ashok K.; Murugan, Preethika; Atchudan, Raji; Ganapathy, Dhanraj; Arya, Sandeep; Mahmoud Karami, Abdulnasser; Govindasamy, Mani

doi:https://doi.org/10.1155/2023/5484059

Journal of Nanomaterials

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Abstract Introduction Experimental Results and Discussion Conclusion Data Availability Conflicts of Interest Authors’ Contributions Acknowledgments References Copyright Related Articles

Research Article | Open Access

Volume 2023 | Article ID 5484059 | https://doi.org/10.1155/2023/5484059

Graphene Nanoribbons/Manganese Oxide Nanocomposite Modified Electrode for Detection of Antimicrobial Drug Nitrofurantoin

Ramila D. Nagarajan,¹Vasanth Magesh,²Ashok K. Sundramoorthy,²Preethika Murugan,³Raji Atchudan,⁴Dhanraj Ganapathy,²Sandeep Arya,⁵Abdulnasser Mahmoud Karami,⁶and Mani Govindasamy⁷

Academic Editor: Dong Kee Yi

Received04 Nov 2022

Revised03 Feb 2023

Accepted14 Feb 2023

Published22 Apr 2023

Abstract

The design and development of a new kind of cost-effective electrode material with excellent selectivity and stability are still a great challenge in the field of electrochemical sensors. Recently, researchers have paid more attention to the electrochemical reduction of nitro compounds due to their hazardous nature. Nitro compounds play a vital role in various industrial applications. However, the direct discharge of nitro compounds to the environment as industrial wastewater is harmful. In this study, a nanocomposite made of 1D graphene nanoribbons decorated with manganese dioxide (GNR-MnO₂) was prepared to fabricate an electrochemical transducer for the determination of nitrofurantoin (NFT) in biofluids. First, 1D GNR was prepared by unzipping of multiwalled carbon nanotubes. Second, the GNR was decorated with MnO₂ by the hydrothermal reduction method. As-prepared GNR-MnO₂ nanocomposite was comprehensively characterized by field emission scanning electron microscopy with EDX, XRD, UV–visible, electrochemical impedance spectroscopy, and cyclic voltammetry. Moreover, GNR-MnO₂-coated glassy carbon electrode (GCE) exhibited good electrocatalytic activity toward NFT. The electroreduction of NFT was found at −0.40 V which was 50 mV lower than bare GCE. GNR-MnO₂ nanocomposite modified GCE showed a well-defined linear reduction peak current for NFT from 10 nM to 1,000 µM. The selectivity of the sensor was also analyzed in the presence of other nitro compounds which confirmed that NFT can be selectively detected at −0.4 V. The GNR-MnO₂ modified electrode was also able to separate reduction peaks of other nitro compounds. In addition, the detection of NFT was carried out in human urine samples with a good recovery of 99.60%–98.60%.

1. Introduction

Synthesis of high-performance catalytic material for the development of compact sensors is on demand. The modern sensor technology has offered many ways to use chemical and biosensors effectively to analyze the environmental, medical, and food samples [1]. The usage of toxic metals, highly poisonous nitro compounds, corrosive acids, and dyes could cause serious soil and water contaminations. Somehow, these toxic substances have been used in various industrial process, consumer products, and pharmaceuticals (nitro compounds used as drugs). Apart from those, nitroaromatic compounds have been used in the chemical industry, and also in the preparation of explosives, pesticides, dyes, pharmaceutical products, etc. The nitro functional group plays a major role in the chemical and biological activities of nitro-substituted compounds [2]. Due to the strong electronegativity of nitro group, they are harmful to the environment. If the nitro compounds are directly discharged into the water bodies, they can pollute the water and cause carcinogenesis in the human body upon high exposure [3]. Nitrofurantoin (NFT), an antimicrobial drug, is active against the Gram-positive and Gram-negative microbes [4, 5]. Basically, NFT belongs to the family of nitrofuran and it has been used as a medicine for the treatment of coccidiosis and the patients suffering from the deficiency of glucose-6-phosphate [6]. Despite that NFT has excellent antimicrobial activity, still it lacks of metabolic toxicity. The toxicity effect arises from the reduction of nitro group into hydroxylamine and nitroso derivatives by the anionic radical mechanism which helps for the reduction of nitro group. After consumption of NFT as an antimicrobial drug, it gets metabolized in the human body. As a result, 25%–30% of NFT is excreted as in the original form and about 1%–2% excretes through urine as aminofurantoin [7, 8]. Moreover, the reduction process of NFT (nitro group) has the versatile ability to produce the reactive oxygen species. So, the direct discharge of NFT into the ecosystem could be harmful to the environment [9] Thus, it is necessary to monitor the level of NFT concentration in the environmental, biological, and pharmaceutical samples to avoid the harmful effect of NFT [10]. Normally, determination of NFT was carried out by spectrophotometry [11], high-performance liquid chromatography [12], and fluorescence method [13]. These methods have some limitations such as the requirement of pretreatment of samples, time-consuming process, skilled technical persons, and high cost [13]. Recently, electrochemical sensors have been used for the accurate quantification of NFT in environmental samples with high sensitivity and selectivity. In the electrochemical sensors, the electrocatalytic materials play a vital role because of their high surface-to-volume ratio and catalytic activity which helped to achieve high selectivity and sensitivity against the particular analyte in the samples [14]. The nanomaterials were classified as 0D (quantum dots) [15, 16], 1D (carbon nanotube, nanorod, and nanowire) [17, 18], 2D (graphene, MXene, MoS₂, etc.) [19–21], and 3D (nanoparticles with different morphology) [22, 23]. These nanomaterials exhibited unique properties and showed higher electrocatalytic activity in the determination of various analytes [24]. Recently, NFT determination was reported using the graphene oxide/Fe₃O₄ nanorods composite-based sensor and used to determine NFT from 0.005 to 100 μM. This sensor was used to quantify NFT in the pig liver sample [25]. The electrochemical determination of NFT was also studied by barium stannate [26], 3D flower nickel oxide boron doped carbon nitride nanocomposite [27], NiFe anchored functionalized multiwalled carbon nanotube (MWCNT) [4], and MgFe₂O₄ nanoparticles [28] based sensors.

Moreover, due to their high electrical conductivity, mechanical properties, hydrophilicity, low cost and biocompatibility, 1D and 2D materials, and their nanocomposite have been used to prepare electrochemical sensors, for examples, graphene [29], boron nitride [30], MXene [31], and graphene nanoribbons (GNRs). GNR is a 1D material which has been used in the development of battery, supercapacitor, and sensors [32]. Recently, the GNR/Co₃O₄ nanocomposite-based sensor was prepared for the selective detection of H₂O₂ [33] and also oxidized GNR showed a good charging capacity of 1,400 mA hr/g in lithium-ion storage [34]. GNR-based sensors were also used to determine epinephrine [32] and nitrogen dioxide [35]. It was found that hybrid material made of GNR and manganese oxide (MnO₂) showed high electrocatalytic activity compared to individual materials.

Herein, for the first time, we demonstrated the application of GNR/MnO₂ nanocomposite modified electrode to selectively determine NFT concentration by the electrochemical reduction process. The GNR/MnO₂ nanocomposite was comprehensively characterized by UV–visible spectroscopy (UV–vis), field emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectroscopy (EDX) and X-ray diffraction (XRD) analysis. Moreover, the GNR/MnO₂ composite modified electrode was prepared and its electrochemical properties were evaluated against NFT by cyclic voltammetry (CV). GNR/MnO₂ was also used for the selective determination of NFT from 10 nM to 1,000 µM. Finally, selective detection of NFT in human urine sample was demonstrated using a GNR/MnO₂ nanocomposite modified electrode. The effect of various interference on the sensor response was also tested in the presence of a few nitro compounds to investigate the selectivity of the sensor.

2. Experimental

Manganese chloride, NFT, sodium acetate, MWCNTs, sodium hydroxide, and ascorbic acid were purchased from Sigma-Aldrich, India. Sulphuric acid, nitrophenol (NP), nitrobenzene (NB), sodium nitrate, and potassium chloride were purchased from Sisco Research Laboratories, India. The phosphate buffer solution (PBS, pH = 7.4) was prepared using NaH₂PO₄ and Na₂HPO₄ for the sensing of NFT. All the solutions were prepared using the milli-Q-water (18.2 MΩ·cm @ 25 ± 2°C).

Electrochemical studies were carried out using a three-electrode system with an electrochemical workstation (Model: CHI-760E), USA. The prepared GNR-MnO₂ nanocomposite material was confirmed by UV–vis using a 2000c nanodrop spectrophotometer, NanoDrop Technologies, USA. All the experiments were performed at room temperature (25 ± 0.2°C). The surface morphologies of GNR and GNR-MnO₂ were examined by high resolution scanning electron microscope (HR-SEM, 2100 plus electron microscope) (JEOL, Japan).

2.1. Preparation of MnO₂

MnO₂ was prepared by hydrothermal method. Briefly, 4 mM MnCl₂ was dissolved in ethanol:water (37 + 3 mL) solution and kept for constant stirring at 600 rpm. After that, 5 mM sodium acetate was added with continuous stirring for 1 hr. Further, the reaction mixture was transferred into 100 mL steel-lined autoclave, and the temperature was maintained at 180°C for 12 hr. After the completion of the reaction, brown precipitate was obtained. The brown precipitate was separated by centrifugation method and washed with ethanol and water. Finally, a dark brown MnO₂ powder was obtained and dried at 60°C (Scheme 1).

2.2. Preparation of GNR/MnO₂ Nanocomposite

First, GNRs were prepared as reported elsewhere [33]. From the obtained powder, dispersion of GNRs was prepared with the concentration of 1.5 mg/mL. Second, the prepared GNR dispersion (10 mL) was added into the reaction mixture of MnCl₂ (4 mM)/ethanol:water/sodium acetate (5 mM), as given in Section 2.1. The same hydrothermal synthesis procedure of MnO₂ was carried out. The obtained product was washed several times and precipitate was collected after centrifugation and drying at 60°C [36]. Finally, the prepared GNR/MnO₂ nanocomposite was dispersed in 10 mL distilled H₂O (0.5 mg/mL) using a high-frequency ultrasonicator. The same procedure was used to prepare individual MnO₂ and GNR dispersions for control experiments.

2.3. Preparation of GNR/MnO₂ Modified Electrode

The glassy carbon electrode (GCE) was cleaned on the polishing cloth using alumina slurry until a mirror-like surface appeared. Five microliters of GNR or MnO₂ or GNR/MnO₂ dispersion was drop casted on the polished GCE surface and dried at 50°C for 10 min. The GNR/MnO₂ film modified electrode was used for the electroreduction of NFT in PBS. All the electrochemical studies were carried out at room temperature after purging out dissolved oxygen from the buffer solution using nitrogen gas. To study the interference effect, nitro compounds such as nitrophenol, nitroaniline, nitrobenzene, and sodium nitrate were tested on GNR-MnO₂/GCE in the presence of NFT.

2.4. Preparation of Real Sample

The 30 mL of urine sample was collected from the adult (age 25). The collected urine sample was centrifuged at 4,000 rpm for 10 min and the supernatant was collected. Then, the supernatant was diluted at 1 : 1 ratio with distilled H₂O and mixed well for 2 min. It was again centrifuged at 4,000 rpm for 10 min to collect the supernatant and analyzed by amperometry.

3. Results and Discussion

3.1. UV–Vis Analysis of GNR, MnO₂, and GNR/MnO₂ Nanocomposite

Scheme 1 shows the synthesis process of GNR-MnO₂ nanocomposite for the electrochemical reduction of NFT. UV–vis spectrum of as-prepared GNR was recorded which showed a strong absorbance band at 250 nm due to the partially oxidized GNRs (Figure 1(a)) [37]. On the other hand, the prepared MnO₂ showed the two transition peaks at 284 and 380 nm which were related to the d–d metal transition of MnO₂ nanoparticles (Figure 1(b)) [38]. In the case of GNR-MnO₂ nanocomposite, UV–vis spectrum revealed the corresponding MnO₂ absorbance peaks which were red shifted from 284 to 290 and 380 to 400 nm (Figure 1(c)). These observed red shift indicated the interactions between the GNR and the MnO₂ in the nanocomposite [31].

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3.2. XRD Pattern Analysis

The GNR, MnO₂, and GNR-MnO₂ nanocomposite samples were analyzed by XRD, as shown in Figure 2. The GNR showed a diffraction peak at 25.4° corresponded to the (002) crystal plane (Figure 2(a)). Another disorder peak was appeared at 42.8°, due to the oxidized GNR [39]. The XRD pattern of MnO₂ showed peaks at (2θ values) 18°, 28.6°, 36.7°, 38.6°, 41.9°, 49.7°, 56.4°, 60.2°, 65.4°, 69.6°, and 72.9° corresponded to (200), (310), (400), (211), (420), (301), (600), (521), (002), (541), and (312) planes, as shown in Figure 2(b). The observed diffraction angles and the planes were corresponded to the α-MnO₂ nanoparticles [40]. Finally, XRD pattern of the GNR-MnO₂ was also recorded which showed the corresponding peaks of GNR-MnO₂. It is worth to note that XRD peaks of the composite sample were slightly shifted toward a higher angle (Figure 2(c)). This observed shift may be due to the presence of synergistic interaction between GNR and MnO₂ in nanocomposite material.

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3.3. Surface Morphology Analysis

The surface morphology of as-prepared GNR was characterized and reported by our group [17]. It was shown that MWCNTs were unzipped into GNRs. To study the electrocatalytic activity, MnO₂ nanoparticles were prepared with the average particle sizes of 50–70 nm (Figure 3(a)). To investigate the role of GNRs, the synthesis of MnO₂ was carried out in the presence of GNRs by hydrothermal process. FE-SEM images of as-prepared GNR-MnO₂ nanocomposite confirmed that MnO₂ nanoparticles decorated on the surface of GNR (Figure 3(b)). In addition, the EDX spectra of MnO₂ and GNR-MnO₂ composite were recorded which confirmed the presence of respective elements (Figure 3(c)). In the EDX spectrum of GNR-MnO₂ composite, elements such as Mn (64.15%), carbon (9.67%), and oxygen (26.15%) were present, as shown in Figure 3(d). Thus, both the FE-SEM and EDX analysis were confirmed that MnO₂ nanoparticles successfully incorporated on to GNRs.

3.4. Cyclic Voltammetry (CV) and Electrochemical Impedance Spectroscopy (EIS)

The electrode kinetics of the modified electrode was studied by CV and electrochemical impedance spectroscopy (EIS) in 2 mM [Fe(CN)₆]³⁻ with 0.1 M KCl at a scan rate of 50 mV s⁻¹. The bare GCE showed a well-defined redox peak of ferricyanide with the anodic to cathodic peak separation (ΔE_p = E_pc−E_pa) of 70 mV. However, the GNR-MnO₂ composite modified GCE exhibited a higher peak potential separation value (202 mV) and lower peak current than the bare GCE. It was due to the electrostatic repulsion between the negatively charged GNR-MnO₂ composite and [Fe(CN)₆]³⁻ (Figure 4(a)). Next, both the modified and bare GCEs were analyzed by EIS. The equivalent circuit model was fitted to the EIS spectrum of the GNR-MnO₂/GCE (Figure 4(b). The obtained solution resistance (R_s) and charge-transfer resistance (R_ct) values of bare GCE were 237.9 and 257.1 Ω, respectively. Similarly, the R_s and R_ct of GNR/MnO₂/GCE were measured as 225.2 and 4,100 Ω, respectively, in 0.1 M KCl containing 2 mM [Fe(CN)₆]³⁻.The R_ct of the GNR-MnO₂/GCE was increased up to 4,100 Ω compared to bare GCE (257 Ω). Hence, it was confirmed that the surface resistance of GCE was increased upon coating of GNR-MnO₂ (Figure 4(b)). The effective surface areas of the electrodes were calculated using CV in [Fe(CN)₆]³⁻. The active surface area for the bare GCE and the modified electrode were 0.07 and 0.126 cm², respectively.

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3.5. Electrochemical Behavior of Modified Electrodes

For the determination of NFT, different modified electrodes were prepared and tested in 0.1 M PBS. The bare GCE, MnO₂/GCE, GNR/GCE, and GNR-MnO₂/GCE were used to record cyclic voltammograms (CVs) in the potential window between −0.8 V and 1.2 V in PBS. Figure 5(a) (curve i) shows CVs of bare GCE without any peaks. However, after the modification with 5 µL GNR dispersion, GNRs/GCE showed a higher capacitance current than bare GCE (Figure 5(b), curve i). Furthermore, GNR showed a broad redox peak centered at 0.125 V (E_pa ∼ 0.2 and E_pc ∼ 0.05 V). This redox peak was observed due to the presence of quinone functional groups on the surface of GNR which was generated during the unzipping process [41, 42]. Figure 5(c) (black curve i) showed a notable redox peak at 0.8 V (E_pc ∼ 0.65 and E_pa ∼ 0.95 V) with high peak currents which were assigned to MnO₂ [43]. Finally, the GNR/MnO₂/GCE was used to record CVs which exhibited redox peak of MnO₂ with high peak currents due to the higher active surface area of the composite modified electrode (Figure 5(d)), black curve i). Each one of these modified electrodes were employed in the electroanalysis of NFT.

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3.6. Electrochemical Analysis of NFT

Next, CVs were recorded in the presence of NFT on bare GCE which showed the reduction peak at −0.45 V with the peak current of 1.45 µA, (Figure 5(a), red curve ii) [44]. Figure 5(b) (red curve ii) indicated the CVs of NFT reduction peak on GNR/GCE at −0.38 V with the small increment in the peak current of 3.0 µA. Followed by, the MnO₂ modified electrode was used to record CVs with NFT which showed reduction peak at −0.42 V with the cathodic peak current of 2.9 µA (Figure 5(c), red curve ii). Interestingly, the GNR-MnO₂ nanocomposite-coated electrode showed the reduction peak of NFT at −0.40 V, with the reduction of overpotential about 50 mV compared to bare GCE with the peak current of 4.5 µA. The higher reduction peak current of NFT observed at the nanocomposite modified electrode indicated the high electrocatalytic activity of the hybrid material. The electrochemical reduction mechanism of NFT is also shown in Scheme 2 [45]. Compared to other reported methods, NFT reduction peak observed at lower potential on GNR-MnO₂/GCE (−0.40 V). For examples, graphene oxide/Fe₃O₄ nanorods composite showed the reduction potential of NFT at −0.41 V [25] and the barium stannate modified sensor showed NFT reduction peak at −0.46 V [26] (Table 1). Thus, it is confirmed that the proposed GNR-MnO₂ is a good composite material to develop NFT sensor.

3.7. Effect of pH on NFT Reduction

The pH of the supporting electrolyte on electroreduction of 10 µM NFT was studied by CV in different pH solutions (pH 2, 4, 6, 7.4, and 8). Depending on the pH, the potential of the NFT reduction peak was shifted. When the pH was decreased from pH 8 to pH 2, reduction peak potential was shifted from a higher negative potential to positive potential side, as shown in Figure 6(a). From this pH study, it was found that pH 7.4 exhibited a lower reduction potential with a higher peak current than the other pH solutions. The linear plot between the pH vs. the reduction potential of NFT resulted with a slope value of 25 mV/pH (Figure 6(b)). This value indicated that the electrochemical reduction of NFT undergoes the equal number of protons and electrons. For further studies, PBS with pH 7.4 was chosen as the suitable electrolyte for the analysis of NFT in biological samples [46].

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3.8. Effect of Scan Rate

CVs were recorded at different scan rates in 0.1 M PBS containing 200 µM NFT from 20 to 200 mV/s. A linear plot was prepared using the scan rate vs. cathodic peak currents, the peak currents were increased linearly against scan rate without much change in the potential. It indicated that the MnO₂ redox process followed a surface-controlled process. The effect of scan rate was also studied in the presence of 200 µM NFT. The linear graph made between the square root of scan rate and NFT reduction peak current revealed that it was a diffusion-controlled process [5].

3.9. Determination of NFT at GNR/MnO₂ Modified Electrode

Figure 7(a) shows CVs of the GNR/MnO₂ modified electrode in 0.1 M PBS with different concentrations of NFT. The reduction peak currents were linearly increased at the peak potential of −0.40 V with respect to concentration of NFT from 10 nM to 1,000 µM. At the higher concentration, the sensors response attained the steady state. The limit of detection (LOD) for NFT was calculated using Equation (1) as 7 nM [47]:

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3.9.1. Interference Analysis

The selectivity of the GNR/MnO₂ sensor toward NFT was also investigated in the presence of other nitro compounds, such as NB, NP, and sodium nitrate. The selectivity of GNR/MnO₂/GCE was tested with 500 µM NFT in the presence of higher concentration of 1 µM NB, NP, and NaNO₃ in 0.1 M PBS (Figure 8). From CV analysis, it was found these nitro compounds showed different reduction potential at −0.78, which was well separated from the NFT reduction potential found at −0.40 V. The corresponding reduction peak current of NFT was noted after the addition of each interfering nitro compounds. The sensor response (GNR/MnO₂/GCE) against NFT reduction peak was decreased about 13%. This observation indicated that NFT reduction signal was not affected in the presence of other nitro compounds (Figure 8). Finally, it confirmed that the GNR-MnO₂/GCE had shown good selectivity toward NFT in the presence of other nitro compounds.

3.9.2. Reproducibility, Repeatability, and Stability of the Modified Electrode

Figure 9(a) shows the repeatability data of the GNR/MnO₂ modified electrode which was recorded in 0.1 M PBS with the addition of 10 µM NFT. The same GNR/MnO₂ modified electrode was used to record the reduction peak current of (10 µM) NFT in five different samples with 0.1 M PBS. The observed data indicated that GNR/MnO₂ modified sensor retained the current response of about 99%. Furthermore, to analyze the long-term stability of the sensor, the GNR/MnO₂ modified electrode was used to detect NFT in 0.1 M PBS. After that, the GNR/MnO₂ modified electrode was gently rinsed with distilled H₂O and stored at room temperature for 37 hr. It was later used to measure the NFT in 0.1 M PBS, which indicated that sensors’ response was stable up to 92% compared to its initial response for the reduction peak of NFT (Figure 9(b)). Next, the sensor fabrication procedure was repeated to prepare three individual sensors independently (using the same GCE to modify with GNR/MnO₂). As-prepared each sensor was used to determine NFT concentration, which showed the relative standard deviation of 0.49%. This confirmed that our sensor fabrication process was highly reproducible for the fabrication of NFT sensors (Figure 9(c)).

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3.9.3. Real-World Sample Analysis

We have also tested our prepared sensor in the determination of NFT in the collected human urine sample. CVs were recorded in 0.1 M PBS with 10 µM NFT before and after spiking with 100 µL of urine sample using GNR-MnO₂ nanocomposite modified electrode (Figure 10(a)). GNR-MnO₂ nanocomposite modified electrode exhibited reduction peak of NFT. However, after spiked with urine, there is a broad peak that was observed between −0.6 and −0.8 V, and no any changes were found at −0.40 V (NFT reduction peak was not increased or decreased). It indicated the absence of NFT in the collected urine sample.

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Moreover, the amperometry (i–t curve) was performed to find out the recovery percentage of NFT in the urine sample after spiked with the standard (Std.) NFT solutions on GNR-MnO₂ nanocomposite modified electrode. Initially, 100 µL of prepared urine sample was added to the 0.1 M PBS, then spiked with standard NFT into the solution mixture (urine + PBS), followed by the addition of three variable concentrations of NFT (2.5, 5, and 10 µM). The amperogram was recorded using the GNR/MnO₂ modified electrode at the applied potential of −0.45 V. No significant current response was observed after the addition of 100 µL of urine. However, after the addition of NFT solutions, sharp reduction currents were observed. Table 2 shows the calculated NFT concentration in the human urine sample using amperometry data after the standard additions of NFT. This shows that the spiked NFT has recovered well in the urine sample (98.6%–99.6%). It was concluded that the GNR/MnO₂ modified electrode can be used for selective detection of NFT in biological samples.

4. Conclusion

We prepared and tested an electrochemical sensor based on GNR/MnO₂ nanocomposite. For this purpose, GNR/MnO₂ nanocomposite was synthesized by hydrothermal method. The synthesized GNR/MnO₂ nanocomposite was comprehensively characterized by UV–vis, EDX, FE-SEM, and XRD. The EDX and XRD data were successfully confirmed the formation of α-MnO₂, GNR, and the GNR-MnO₂ nanocomposite. Moreover, the prepared composite and the individual materials have been applied to prepare electrochemical sensors which were tested in the electroreduction of NFT. The GNR/MnO₂/GCE had reduced the overpotential of NFT reduction reaction and also increased the peak current for NFT, compared to other individual material modified electrodes. The GNR/MnO₂ nanocomposite-based sensor showed a linear response for NFT from 10 nM to 1,000 µM. The selectivity, stability, and repeatability of the GNR/MnO₂/GCE were also investigated which revealed that this sensor can be used for selective detection of NFT in the presence of other nitro compounds with high reliability.

Data Availability

Data will be provided upon request.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Authors’ Contributions

Ramila D. Nagarajan, Vasanth Magesh, and Raji Atchudan contributed equally to this work.

Acknowledgments

The project work was financially supported by the Science and Engineering Research Board (SERB) for funding through CRG/2021/001517. The authors thank the Department of Science and Technology (DST) (International Bilateral Cooperation Division), India, for financial support through “INDO-RUSSIA” project (File No. INT/RUS/RFBR/385). This work was funded by the Researchers Supporting Project Number (RSPD2023R764), King Saud University, Riyadh, Saudi Arabia.

References

R. D. Nagarajan and A. K. Sundramoorthy, “Recent trends in fabrication and applications of wearable bioelectronics for early-stage disease monitoring and diagnosis,” in Macro, Micro, and Nano-Biosensors, M. Rai, A. Reshetilov, Y. Plekhanova, and A. P. Ingle, Eds., pp. 357–381, Springer, Cham, 2021.
View at: Publisher Site | Google Scholar
K.-S. Ju and R. E. Parales, “Nitroaromatic compounds, from synthesis to biodegradation,” Microbiology and Molecular Biology Reviews, vol. 74, no. 2, pp. 250–272, 2010.
View at: Publisher Site | Google Scholar
U. P. Azad, S. Mahapatra, Divya, A. Srivastava, N. P. Shetti, and P. Chandra, “Electrochemical biosensors for monitoring of bioorganic and inorganic chemical pollutants in biological and environmental matrices,” in Microbial Biodegradation and Bioremediation (Second Edition), S. Das and H. R. Dash, Eds., pp. 509–531, Elsevier, 2022.
View at: Publisher Site | Google Scholar
K.-Y. Hwa and T. S. K. Sharma, “Nano assembly of NiFe spheres anchored on f-MWCNT for electrocatalytic reduction and sensing of nitrofurantoin in biological samples,” Scientific Reports, vol. 10, Article ID 12256, 2020.
View at: Publisher Site | Google Scholar
K. Sudha, A. Elangovan, S. Senthilkumar, A. Jeevika, and G. Arivazhagan, “Electrocatalytic reduction of nitrofurantoin in biological sample based on assembly of ScMo anchored f-MCNNcs modified GCE,” Microchemical Journal, vol. 172, Part B, Article ID 106943, 2022.
View at: Publisher Site | Google Scholar
B. Howard and B. Furman, “Nitrofurantoin,” in Reference Module in Biomedical Sciences, Elsevier, 2018.
View at: Publisher Site | Google Scholar
J. K. Aronson, Ed.“Nitrofurantoin,” in Meyler’s Side Effects of Drugs, pp. 210–218, Elsevier, Oxford, 16th edition, 2016.
View at: Publisher Site | Google Scholar
M. M. Radhi, Z. N. Hamad, M. S. Jabir, and S. S. Ezzaldeen, “Electrochemical study of nitrofurantoin at micro- and nanoparticles in blood medium using cyclic voltammetric technique,” Advanced Nano-Bio-Materials and Devices, vol. 1, no. 2, pp. 78–85, 2017.
View at: Google Scholar
B. J. Gardiner, A. J. Stewardson, I. J. Abbott, and A. Y. Peleg, “Nitrofurantoin and fosfomycin for resistant urinary tract infections: old drugs for emerging problems,” Australian Prescriber, vol. 42, no. 1, pp. 14–19, 2019.
View at: Publisher Site | Google Scholar
B. Howard, “Nitrofurantoin,” in xPharm: The Comprehensive Pharmacology Reference, S. J. Enna and D. B. Bylund, Eds., pp. 1–6, Elsevier, New York, 2007.
View at: Publisher Site | Google Scholar
H. Hadi and M. Mouayed, “Determination of nitrofurantoin in pharmaceutical preparations using flow injection-spectrophotometry,” Journal of the Association of Arab Universities for Basic and Applied Sciences, vol. 24, no. 1, pp. 74–80, 2017.
View at: Publisher Site | Google Scholar
D. S. Patel, N. Sharma, M. C. Patel, B. N. Patel, P. S. Shrivastav, and M. Sanyal, “Quantitation of nitrofurantoin in human plasma by liquid chromatography tandem mass spectrometry,” Acta Pharmaceutica, vol. 63, no. 2, pp. 141–158, 2013.
View at: Publisher Site | Google Scholar
Y. Wang, T. Chen, Q. Zhuang, and Y. Ni, “Label-free photoluminescence assay for nitrofurantoin detection in lake water samples using adenosine-stabilized copper nanoclusters as nanoprobes,” Talanta, vol. 179, pp. 409–413, 2018.
View at: Publisher Site | Google Scholar
L. R. Adil, R. Parui, M. N. Khatun et al., “Nanomaterials for sensors: synthesis and applications,” in Advanced Nanomaterials for Point of Care Diagnosis and Therapy, S. Dave, J. Das, and S. Ghosh, Eds., pp. 121–168, Elsevier, 2022.
View at: Publisher Site | Google Scholar
V. Magesh, A. K. Sundramoorthy, and D. Ganapathy, “Recent advances on synthesis and potential applications of carbon quantum dots,” Frontiers in Materials, vol. 9, 2022.
View at: Publisher Site | Google Scholar
R. Atchudan, P. Gangadaran, S. Perumal et al., “Green synthesis of multicolor emissive nitrogen-doped carbon dots for bioimaging of human cancer cells,” Journal of Cluster Science, 2022.
View at: Publisher Site | Google Scholar
N. Murugan, T. H. V. Kumar, N. R. Devi, and A. K. Sundramoorthy, “A flower-structured MoS₂-decorated f-MWCNTs/ZnO hybrid nanocomposite-modified sensor for the selective electrochemical detection of vitamin C,” New Journal of Chemistry, vol. 43, no. 38, pp. 15105–15114, 2019.
View at: Publisher Site | Google Scholar
T. H. V. Kumar, S. K. R. Pillai, M. B. Chan-Park, and A. K. Sundramoorthy, “Highly selective detection of an organophosphorus pesticide, methyl parathion, using Ag–ZnO–SWCNT based field-effect transistors,” Journal of Materials Chemistry C, vol. 8, no. 26, pp. 8864–8875, 2020.
View at: Publisher Site | Google Scholar
V. Magesh, A. K. Sundramoorthy, D. Ganapathy et al., “Palladium hydroxide (Pearlman’s catalyst) doped MXene (Ti₃C₂T_x) composite modified electrode for selective detection of nicotine in human sweat,” Biosensors, vol. 13, no. 1, Article ID 54, 2023.
View at: Publisher Site | Google Scholar
S. M. M. Raj, A. K. Sundramoorthy, R. Atchudan, D. Ganapathy, and A. Khosla, “Review—recent trends on the synthesis and different characterization tools for MXenes and their emerging applications,” Journal of the Electrochemical Society, vol. 169, no. 7, Article ID 077501, 2022.
View at: Publisher Site | Google Scholar
J. Rajendran, A. K. Sundramoorthy, D. Ganapathy, R. Atchudan, M. A. Habila, and D. Nallaswamy, “2D MXene/graphene nanocomposite preparation and its electrochemical performance towards the identification of nicotine level in human saliva,” Journal of Hazardous Materials, vol. 440, Article ID 129705, 2022.
View at: Publisher Site | Google Scholar
A. Ahmed, A. Singh, B. Padha, A. K. Sundramoorthy, A. Tomar, and S. Arya, “UV–vis spectroscopic method for detection and removal of heavy metal ions in water using Ag doped ZnO nanoparticles,” Chemosphere, vol. 303, Part 3, Article ID 135208, 2022.
View at: Publisher Site | Google Scholar
K. Gokulkumar, A. K. Sundramoorthy, S.-F. Wang, A. Harikrishnan, and R. A. Alshgari, “High-performance electrochemical sensor based on yttrium sulfide nanoparticles decorated carbon nitride heterostructure for highly sensitive detection of antimicrobial drug in biological samples,” Journal of the Electrochemical Society, vol. 168, no. 7, Article ID 077516, 2021.
View at: Publisher Site | Google Scholar
C. Murugan, N. Murugan, A. K. Sundramoorthy, and A. Sundaramurthy, “Gradient triple-layered ZnS/ZnO/Ta₂O₅–SiO₂ core–shell nanoparticles for enzyme-based electrochemical detection of cancer biomarkers,” ACS Applied Nano Materials, vol. 3, no. 8, pp. 8461–8471, 2020.
View at: Publisher Site | Google Scholar
B. S. He and J. W. Li, “A sensitive electrochemical sensor based on reduced graphene oxide/Fe₃O₄ nanorod composites for detection of nitrofurantoin and its metabolite,” Analytical Methods, vol. 11, no. 11, pp. 1427–1435, 2019.
View at: Publisher Site | Google Scholar
M. Balamurugan, K. Alagumalai, T.-W. Chen, S.-M. Chen, X. Liu, and M. Selvaganapathy, “Simultaneous electrochemical determination of nitrofurantoin and nifedipine with assistance of needle-shaped perovskite structure: barium stannate fabricated glassy carbon electrode,” Microchimica Acta, vol. 188, Article ID 19, 2021.
View at: Publisher Site | Google Scholar
T. Kokulnathan and T.-J. Wang, “Synthesis and characterization of 3D flower-like nickel oxide entrapped on boron doped carbon nitride nanocomposite: an efficient catalyst for the electrochemical detection of nitrofurantoin,” Composites Part B: Engineering, vol. 174, Article ID 106914, 2019.
View at: Publisher Site | Google Scholar
J. N. Baby, B. Sriram, S.-F. Wang, and M. George, “Effect of various deep eutectic solvents on the sustainable synthesis of MgFe₂O₄ nanoparticles for simultaneous electrochemical determination of nitrofurantoin and 4-nitrophenol,” ACS Sustainable Chemistry & Engineering, vol. 8, no. 3, pp. 1479–1486, 2020.
View at: Publisher Site | Google Scholar
N. G. Yasri, A. K. Sundramoorthy, W.-J. Chang, and S. Gunasekaran, “Highly selective mercury detection at partially oxidized graphene/poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) nanocomposite film-modified electrode,” Frontiers in Materials, vol. 1, Article ID 33, 2014.
View at: Publisher Site | Google Scholar
R. Jerome and A. K. Sundramoorthy, “Hydrothermal synthesis of boron nitride quantum dots/poly(luminol) nanocomposite for selective detection of ascorbic acid,” Journal of the Electrochemical Society, vol. 166, no. 9, pp. B3017–B3024, 2019.
View at: Publisher Site | Google Scholar
R. D. Nagarajan, A. Sundaramurthy, and A. K. Sundramoorthy, “Synthesis and characterization of MXene (Ti₃C₂T_x)/iron oxide composite for ultrasensitive electrochemical detection of hydrogen peroxide,” Chemosphere, vol. 286, Article ID 131478, 2022.
View at: Publisher Site | Google Scholar
R. Sainz, M. del Pozo, M. Vilas-Varela et al., “Chemically synthesized chevron-like graphene nanoribbons for electrochemical sensors development: determination of epinephrine,” Scientific Reports, vol. 10, Article ID 14614, 2020.
View at: Publisher Site | Google Scholar
P. Murugan, A. K. Sundramoorthy, R. D. Nagarajan et al., “Electrochemical detection of H₂O₂ on graphene nanoribbons/cobalt oxide nanorods-modified electrode,” Journal of Nanomaterials, vol. 2022, Article ID 9866111, 10 pages, 2022.
View at: Publisher Site | Google Scholar
T. Bhardwaj, A. Antic, B. Pavan, V. Barone, and B. D. Fahlman, “Enhanced electrochemical lithium storage by graphene nanoribbons,” Journal of the American Chemical Society, vol. 132, no. 36, pp. 12556–12558, 2010.
View at: Publisher Site | Google Scholar
K. M. Cho, S.-Y. Cho, S. Chong et al., “Edge-functionalized graphene nanoribbon chemical sensor: comparison with carbon nanotube and graphene,” ACS Applied Materials & Interfaces, vol. 10, no. 49, pp. 42905–42914, 2018.
View at: Publisher Site | Google Scholar
T. Mounika, S. L. Belagali, and K. T. Vadiraj, “Manganese oxide nanoparticles synthesis route, characterization and optical properties,” Materials Today: Proceedings, vol. 75, Suppl, pp. 72–76, 2023.
View at: Publisher Site | Google Scholar
E. Cunha, M. F. Proença, F. Costa et al., “Self-assembled functionalized graphene nanoribbons from carbon nanotubes,” ChemistryOpen, vol. 4, no. 2, pp. 115–119, 2015.
View at: Publisher Site | Google Scholar
X. Zhang and W. Yang, “Electrophoretic deposition of a thick film of layered manganese oxide,” Chemistry Letters, vol. 36, no. 10, pp. 1228-1229, 2007.
View at: Publisher Site | Google Scholar
J. Li, S. Ye, T. Li, X. Li, X. Yang, and S. Ding, “Preparation of graphene nanoribbons (GNRs) as an electronic component with the multi-walled carbon nanotubes (MWCNTs),” Procedia Engineering, vol. 102, pp. 492–498, 2015.
View at: Publisher Site | Google Scholar
L. Feng, Z. Xuan, H. Zhao et al., “MnO₂ prepared by hydrothermal method and electrochemical performance as anode for lithium-ion battery,” Nanoscale Research Letters, vol. 9, Article ID 290, 2014.
View at: Publisher Site | Google Scholar
R. D. Nagarajan, P. Murugan, and A. K. Sundramoorthy, “Selective electrochemical sensing of NADH and NAD⁺ using graphene/tungstate nanocomposite modified electrode,” ChemistrySelect, vol. 5, no. 46, pp. 14643–14651, 2020.
View at: Publisher Site | Google Scholar
P. Murugan, R. D. Nagarajan, A. K. Sundramoorthy et al., “Electrochemical detection of H₂O₂ using an activated glassy carbon electrode,” ECS Sensors Plus, vol. 1, no. 3, Article ID 034401, 2022.
View at: Publisher Site | Google Scholar
S. Thiagarajan, T. H. Tsai, and S. M. Chen, “Electrochemical fabrication of nano manganese oxide modified electrode for the detection of H₂O₂,” International Journal of Electrochemical Science, vol. 6, pp. 2235–2245, 2011.
View at: Google Scholar
N. Nataraj and S.-M. Chen, “An electrochemical assay for the detection of nitrofurantoin based on bismuth titanate enclosed carbon nanofiber in environmental and biological samples,” Journal of Electroanalytical Chemistry, vol. 887, Article ID 115152, 2021.
View at: Publisher Site | Google Scholar
S. Velmurugan, S. Palanisamy, T. C.-K. Yang, M. Gochoo, and S.-W. Chen, “Ultrasonic assisted functionalization of MWCNT and synergistic electrocatalytic effect of nano-hydroxyapatite incorporated MWCNT-chitosan scaffolds for sensing of nitrofurantoin,” Ultrasonics Sonochemistry, vol. 62, Article ID 104863, 2020.
View at: Publisher Site | Google Scholar
F. Ahmed, T. Kokulnathan, A. Umar et al., “Zinc oxide/phosphorus-doped carbon nitride composite as potential scaffold for electrochemical detection of nitrofurantoin,” Biosensors, vol. 12, no. 10, Article ID 856, 2022.
View at: Publisher Site | Google Scholar
E. D. Olsen, “Analytical chemistry, fourth edition (Christian, Gary D.),” Journal of Chemical Education, vol. 63, no. 11, Article ID A277, 1986.
View at: Publisher Site | Google Scholar

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Copyright © 2023 Ramila D. Nagarajan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Journal of Nanomaterials

Graphene Nanoribbons/Manganese Oxide Nanocomposite Modified Electrode for Detection of Antimicrobial Drug Nitrofurantoin

Abstract

1. Introduction

2. Experimental

2.1. Preparation of MnO2

2.2. Preparation of GNR/MnO2 Nanocomposite

2.3. Preparation of GNR/MnO2 Modified Electrode

2.4. Preparation of Real Sample

3. Results and Discussion

3.1. UV–Vis Analysis of GNR, MnO2, and GNR/MnO2 Nanocomposite

3.2. XRD Pattern Analysis

3.3. Surface Morphology Analysis

3.4. Cyclic Voltammetry (CV) and Electrochemical Impedance Spectroscopy (EIS)

3.5. Electrochemical Behavior of Modified Electrodes

3.6. Electrochemical Analysis of NFT

3.7. Effect of pH on NFT Reduction

3.8. Effect of Scan Rate

3.9. Determination of NFT at GNR/MnO2 Modified Electrode

3.9.1. Interference Analysis

3.9.2. Reproducibility, Repeatability, and Stability of the Modified Electrode

3.9.3. Real-World Sample Analysis

4. Conclusion

Data Availability

Conflicts of Interest

Authors’ Contributions

Acknowledgments

References

Copyright

2.1. Preparation of MnO₂

2.2. Preparation of GNR/MnO₂ Nanocomposite

2.3. Preparation of GNR/MnO₂ Modified Electrode

3.1. UV–Vis Analysis of GNR, MnO₂, and GNR/MnO₂ Nanocomposite

3.9. Determination of NFT at GNR/MnO₂ Modified Electrode