A Robust, Enzyme-Free Glucose Sensor Based on Lysine-Assisted CuO Nanostructures

The production of a nanomaterial with enhanced and desirable electrocatalytic properties is of prime importance, and the commercialization of devices containing these materials is a challenging task. In this study, unique cupric oxide (CuO) nanostructures were synthesized using lysine as a soft template for the evolution of morphology via a rapid and boiled hydrothermal method. The morphology and structure of the synthesized CuO nanomaterial were characterized using scanning electron microscopy (SEM) and X-ray diffraction (XRD), respectively. The prepared CuO nanostructures showed high potential for use in the electrocatalytic oxidation of glucose in an alkaline medium. The proposed enzyme-free glucose sensor demonstrated a robust response to glucose with a wide linear range and high sensitivity, selectivity, stability, and reproducibility. To explore its practical feasibility, the glucose content of serum samples was successfully determined using the enzyme-free sensor. An analytical recovery method was used to measure the actual glucose from the serum samples, and the results were satisfactory. Moreover, the presented glucose sensor has high chemical stability and can be reused for repetitive measurements. This study introduces an enzyme-free glucose sensor as an alternative tool for clinical glucose quantification.


Introduction
Exploring the physicochemical features of nano-dimensional materials with controlled morphology, size, and specificity is a challenging and demanding task [1]. Controlling the shape hierarchy of nanomaterials is a new step towards tuning their properties [2]. Among the various transition metal oxides, cupric oxide nanostructures have received great attention from the scientific community for their wide range of applications, including uses in antimicrobials [3,4], chemical and biological sensors [5,6], optoelectronics [7], and photonic and electronic devices [8]. Cupric oxide nanostructures possess desirable properties such as high surface-to-volume ratios, conductivity, and cost effectiveness [3]. The controlled morphology of copper oxide at nanoscale dimensions may significantly affect catalytic, optical, and electrical characteristic and may do so at low cost [9]. CuO nanostructures exhibit a narrow band gap (1.2-1.6 eV) with enhanced catalytic performance and good chemical stability [10]. Different growth techniques have been used to prepare

The Synthesis of Lysine-Assisted CuO Nanostructures Using a Rapid Hydrothermal Treatment Method
Lysine-assisted CuO nanostructures were synthesized using low-temperature, aqueous chemical growth methodology. In this preparation method, 100 mL of 0.1 M CuCl 2 ·2H 2 O was first homogenized with 1 g lysine. Afterwards, 33% NH 3 , and the growth solution underwent a 2 h hydrothermal treatment in a pre-heated electric oven at 200 • C. The resulting CuO nanomaterial was rinsed with deionized water to remove surface impurities prior to its use in the modification of glassy carbon electrodes. In this study, lysine was used as a soft template for the CuO nanomaterial evolution of morphology.

Characterization and Electrochemical Cell Assembly
Scanning electron microscopy (SEM) (JEOL, Takyo, Japan) and X-ray diffraction (XRD, Bruker D-8, Fischers, New York, NY, USA) were used to study the morphological, structural, and compositional features of the prepared CuO nanostructures. The electrochemical cell assembly used a 760D model electrochemical work station with a calomel reference electrode and a platinum wire counter electrode. A CuO-nanostructure-modified GCE was used as the working electrode. All glucose measurements were performed in 0.1 M NaOH.

Preparation of Modified Glassy Carbon Electrodes (GCEs)
GCE surfaces were modified with CuO nanostructures using the methodology described in our previously published work [24]. Briefly, the GCE was gently polished with 1 µm alumina paste and ultrasonically cleaned in deionized water and ethanol. The drop-casting method was used to modify GCEs using a suspension of CuO nanostructures (0.5 g/mL ethanol). The deposited nanomaterial was coated with 1% Nafion to ensure that the CuO nanostructures firmly adhered. If the prepared CuO nanostructures are directly grown on a conductive substrate using similar growth conditions, this substrate can serve as a working electrode. If the growth of CuO nanostructures on a conductive substrate is successfully established, can be used for the non-enzymatic detection of glucose. . The prepared CuO nanomaterial was determined to be of high purity and excellent crystalline quality. Figure 2 shows the SEM images of the CuO nanostructures obtained using lysine as a soft template. The exhibited morphology was that of a cotton flower at low and high magnification (Figure 2A,B, respectively). The lysine played a crucial role in tuning the morphology of CuO nanostructures by controlling the dimensions and features.

The Synthesis of Lysine-Assisted CuO Nanostructures Using a Rapid Hydrothermal Treatment Method
Lysine-assisted CuO nanostructures were synthesized using low-temperature, aqueous chemical growth methodology. In this preparation method, 100 mL of 0.1 M CuCl2·2H2O was first homogenized with 1 g lysine. Afterwards, 33% NH3, and the growth solution underwent a 2 h hydrothermal treatment in a pre-heated electric oven at 200 °C. The resulting CuO nanomaterial was rinsed with deionized water to remove surface impurities prior to its use in the modification of glassy carbon electrodes. In this study, lysine was used as a soft template for the CuO nanomaterial evolution of morphology.

Characterization and Electrochemical Cell Assembly
Scanning electron microscopy (SEM) (JEOL, Takyo, Japan) and X-ray diffraction (XRD, Bruker D-8, Fischers, New York, NY, USA) were used to study the morphological, structural, and compositional features of the prepared CuO nanostructures. The electrochemical cell assembly used a 760D model electrochemical work station with a calomel reference electrode and a platinum wire counter electrode. A CuO-nanostructure-modified GCE was used as the working electrode. All glucose measurements were performed in 0.1 M NaOH.

Preparation of Modified Glassy Carbon Electrodes (GCEs)
GCE surfaces were modified with CuO nanostructures using the methodology described in our previously published work [24]. Briefly, the GCE was gently polished with 1 μm alumina paste and ultrasonically cleaned in deionized water and ethanol. The drop-casting method was used to modify GCEs using a suspension of CuO nanostructures (0.5 g/mL ethanol). The deposited nanomaterial was coated with 1% Nafion to ensure that the CuO nanostructures firmly adhered. If the prepared CuO nanostructures are directly grown on a conductive substrate using similar growth conditions, this substrate can serve as a working electrode. If the growth of CuO nanostructures on a conductive substrate is successfully established, can be used for the non-enzymatic detection of glucose.  Figure 2 shows the SEM images of the CuO nanostructures obtained using lysine as a soft template. The exhibited morphology was that of a cotton flower at low and high magnification (Figure 2A,B, respectively). The lysine played a crucial role in tuning the morphology of CuO nanostructures by controlling the dimensions and features.

Electrochemically Sensing Glucose Using Different Electrochemical Modes
The sensing mechanism of glucose on the surface of CuO nanostructures in alkaline medium was elucidated by modifying the GCE with CuO nanostructures as depicted in Figure 3. Glucose oxidation, over newly prepared CuO nanostructures in NaOH, generated gluconic acid or other intermediate products. The most suitable and possible mechanism for glucose oxidation on at CuO-nanostructure-modified electrodes in a basic medium is shown in the following Equations (1) and (2): CuOOH + e − + glucose > CuO + OH + gluconic acid (2) The production of electrons during glucose electrooxidation reactions is apparent in Figure 3, where the CV response of a modified electrode in the presence of 1 mM glucose produces a broader anodic peak around +0.5 V. No redox peak was found in the absence of glucose. The successive increase in current shows well-organized, inherited catalytic features of CuO nanostructures that serve to enhance the sensing performance of the modified electrode, such as a large surface area and rapid electron transfer of as-prepared CuO nanostructures in the current research findings. The electrode response in the presence of 1 mM glucose at various scan rates showed that the reaction at the modified electrode surface was diffusion-controlled ( Figure 4).

Electrochemically Sensing Glucose Using Different Electrochemical Modes
The sensing mechanism of glucose on the surface of CuO nanostructures in alkaline medium was elucidated by modifying the GCE with CuO nanostructures as depicted in Figure 3. Glucose oxidation, over newly prepared CuO nanostructures in NaOH, generated gluconic acid or other intermediate products. The most suitable and possible mechanism for glucose oxidation on at CuO-nanostructure-modified electrodes in a basic medium is shown in the following Equations (1) and (2): CuOOH + e − + glucose > CuO + OH + gluconic acid (2) The production of electrons during glucose electrooxidation reactions is apparent in Figure 3, where the CV response of a modified electrode in the presence of 1 mM glucose produces a broader anodic peak around +0.5 V. No redox peak was found in the absence of glucose. The successive increase in current shows well-organized, inherited catalytic features of CuO nanostructures that serve to enhance the sensing performance of the modified electrode, such as a large surface area and rapid electron transfer of as-prepared CuO nanostructures in the current research findings. The electrode response in the presence of 1 mM glucose at various scan rates showed that the reaction at the modified electrode surface was diffusion-controlled ( Figure 4).

Electrochemically Sensing Glucose Using Different Electrochemical Modes
The sensing mechanism of glucose on the surface of CuO nanostructures in alkaline medium was elucidated by modifying the GCE with CuO nanostructures as depicted in Figure 3. Glucose oxidation, over newly prepared CuO nanostructures in NaOH, generated gluconic acid or other intermediate products. The most suitable and possible mechanism for glucose oxidation on at CuO-nanostructure-modified electrodes in a basic medium is shown in the following Equations (1) and (2): CuOOH + e − + glucose > CuO + OH + gluconic acid (2) The production of electrons during glucose electrooxidation reactions is apparent in Figure 3, where the CV response of a modified electrode in the presence of 1 mM glucose produces a broader anodic peak around +0.5 V. No redox peak was found in the absence of glucose. The successive increase in current shows well-organized, inherited catalytic features of CuO nanostructures that serve to enhance the sensing performance of the modified electrode, such as a large surface area and rapid electron transfer of as-prepared CuO nanostructures in the current research findings. The electrode response in the presence of 1 mM glucose at various scan rates showed that the reaction at the modified electrode surface was diffusion-controlled ( Figure 4).   Amperometry was used to estimate the sensing potential of the electrode modified with newly prepared CuO nanostructures with successive glucose additions in 0.1 M NaOH at an applied potential of +0.5 V ( Figure 5A). The solution was stirred continuously. With the addition of glucose, the modified electrode showed rapid and sensitive responses, achieving 90% of the steady-state current within a short interval of time (5 s). The amperometric responses were repeated in triplicate, and the average response was used for the linear range calibration curve ( Figure 5B). Calibration curve currents increased with each successive addition of higher glucose concentrations in the linear range of 1 to 10 mM. Greater glucose concentrations saturated the active sites of the CuO nanostructures and thus saturated the current response. The modified electrode sensitivity was found to be 464,285.7 μA·mM −1 ·cm −2 , which was estimated from the calibration curve to be in the range of 0.25 mM to 13.25 mM (R 2 = 0.99) and the lower limit of detection was determined (0.0159 mM) for glucose sensing (S/N = 3). The sensitivity of the glucose sensor was calculated by dividing the slope of the calibration curve by the sensing area of the electrode. The high sensitivity and wide linear range was attributed to the high surface-to-volume ratio and the excellent efficiency with which the synthesized CuO nanostructures promoted electron transfer between glucose and the working electrode. Compared to reported enzyme-free sensors based on CuO nanostructures modified electrode, our glucose sensor showed excellent performance in a wide linear detection range (Table 1) [25][26][27][28].
Selectivity against other endogenous species was assessed to examine any possible glucose sensor signal interference that these species may introduce. The amperometric response of the enzyme-free glucose sensor in 0.1 M NaOH at an applied potential of +0.5 V is shown in Figure 6. The addition of 1 mM glucose to the stirred NaOH solution produced a drastic increase in recorded current. However, the addition of interfering substances such as uric acid, ascorbic acid, and dopamine (0.1 mM each) did not produce a significant amount of current from the fabricated glucose sensor. The lack of interference at the sensor was attributed to the selective property of the synthesized CuO nanostructures. Additionally, the presence of a Nafion membrane layer made it possible for the sensor to exclude interference from these species during glucose sensing [29]. This study confirmed that the fabricated electrode can determine the presence of glucose successfully and with high chemical selectivity, even in samples with dopamine, ascorbic acid, and uric acid interferents. Experiments using different electrochemical modes, such as square wave voltammetry and differential pulse voltammetry, were used to strengthen the results obtained by CV. Amperometry was used to estimate the sensing potential of the electrode modified with newly prepared CuO nanostructures with successive glucose additions in 0.1 M NaOH at an applied potential of +0.5 V ( Figure 5A). The solution was stirred continuously. With the addition of glucose, the modified electrode showed rapid and sensitive responses, achieving 90% of the steady-state current within a short interval of time (5 s). The amperometric responses were repeated in triplicate, and the average response was used for the linear range calibration curve ( Figure 5B). Calibration curve currents increased with each successive addition of higher glucose concentrations in the linear range of 1 to 10 mM. Greater glucose concentrations saturated the active sites of the CuO nanostructures and thus saturated the current response. The modified electrode sensitivity was found to be 464,285.7 µA·mM −1 ·cm −2 , which was estimated from the calibration curve to be in the range of 0.25 mM to 13.25 mM (R 2 = 0.99) and the lower limit of detection was determined (0.0159 mM) for glucose sensing (S/N = 3). The sensitivity of the glucose sensor was calculated by dividing the slope of the calibration curve by the sensing area of the electrode. The high sensitivity and wide linear range was attributed to the high surface-to-volume ratio and the excellent efficiency with which the synthesized CuO nanostructures promoted electron transfer between glucose and the working electrode. Compared to reported enzyme-free sensors based on CuO nanostructures modified electrode, our glucose sensor showed excellent performance in a wide linear detection range (Table 1) [25][26][27][28].
Selectivity against other endogenous species was assessed to examine any possible glucose sensor signal interference that these species may introduce. The amperometric response of the enzyme-free glucose sensor in 0.1 M NaOH at an applied potential of +0.5 V is shown in Figure 6. The addition of 1 mM glucose to the stirred NaOH solution produced a drastic increase in recorded current. However, the addition of interfering substances such as uric acid, ascorbic acid, and dopamine (0.1 mM each) did not produce a significant amount of current from the fabricated glucose sensor. The lack of interference at the sensor was attributed to the selective property of the synthesized CuO nanostructures. Additionally, the presence of a Nafion membrane layer made it possible for the sensor to exclude interference from these species during glucose sensing [29]. This study confirmed that the fabricated electrode can determine the presence of glucose successfully and with high chemical selectivity, even in samples with dopamine, ascorbic acid, and uric acid interferents. Experiments using different electrochemical modes, such as square wave voltammetry and differential pulse voltammetry, were used to strengthen the results obtained by CV.   Figure 7A shows the square wave voltammograms for different glucose concentrations (0.01 mM, 0.1 mM, 0.5 mM, 0.8 mM, 1 mM, and 1.5 mM). The peak currents increased at the same potential, as discussed with CV measurements. The calibration plot of Ip versus glucose concentration, as obtained from square wave voltammetry, is shown in Figure 7B. The response was clearly linear with different glucose concentrations. Figure 8A shows the differential pulse voltammograms for different glucose concentrations (0.1 mM, 0.5 mM, 1 mM, 2 mM, and 2.5 mM). A slight shift in glucose oxidation potential was observed, which could be attributed to a less sensitive differential pulse voltammetry response. The calibration plot of Ip versus various glucose concentrations is linear, shown in Figure 8B. These results strongly supported both CV and square wave voltammetry experiments.   Figure 7A shows the square wave voltammograms for different glucose concentrations (0.01 mM, 0.1 mM, 0.5 mM, 0.8 mM, 1 mM, and 1.5 mM). The peak currents increased at the same potential, as discussed with CV measurements. The calibration plot of Ip versus glucose concentration, as obtained from square wave voltammetry, is shown in Figure 7B. The response was clearly linear with different glucose concentrations. Figure 8A shows the differential pulse voltammograms for different glucose concentrations (0.1 mM, 0.5 mM, 1 mM, 2 mM, and 2.5 mM). A slight shift in glucose oxidation potential was observed, which could be attributed to a less sensitive differential pulse voltammetry response. The calibration plot of Ip versus various glucose concentrations is linear, shown in Figure 8B. These results strongly supported both CV and square wave voltammetry experiments.  Figure 7A shows the square wave voltammograms for different glucose concentrations (0.01 mM, 0.1 mM, 0.5 mM, 0.8 mM, 1 mM, and 1.5 mM). The peak currents increased at the same potential, as discussed with CV measurements. The calibration plot of Ip versus glucose concentration, as obtained from square wave voltammetry, is shown in Figure 7B. The response was clearly linear with different glucose concentrations. Figure 8A shows the differential pulse voltammograms for different glucose concentrations (0.1 mM, 0.5 mM, 1 mM, 2 mM, and 2.5 mM). A slight shift in glucose oxidation potential was observed, which could be attributed to a less sensitive differential pulse voltammetry response. The calibration plot of Ip versus various glucose concentrations is linear, shown in Figure 8B. These results strongly supported both CV and square wave voltammetry experiments.  The lifetime usability of our developed glucose sensor was monitored by storing the modified electrodes in air under ambient environmental conditions and intermittently measuring the current response during glucose oxidation. The modified electrode was found to retain approximately 98% of the initial current response after a 2-month storage period. Additionally, six modified electrodes were scanned using CV (50 mV/s) in the presence of 0.5 mM glucose to evaluate the glucose sensor reproducibility under similar conditions (Figure 9). The peak currents from CV calibration plot responses from all electrodes were of similar amplitudes, with a low standard deviation (RSD; 3%), indicating that the fabricated glucose sensors were highly reproducible. The potential stability and reproducibility of the modified electrode were indexed to the high chemical stability of the CuO nanostructures synthesized in this study.  The lifetime usability of our developed glucose sensor was monitored by storing the modified electrodes in air under ambient environmental conditions and intermittently measuring the current response during glucose oxidation. The modified electrode was found to retain approximately 98% of the initial current response after a 2-month storage period. Additionally, six modified electrodes were scanned using CV (50 mV/s) in the presence of 0.5 mM glucose to evaluate the glucose sensor reproducibility under similar conditions ( Figure 9). The peak currents from CV calibration plot responses from all electrodes were of similar amplitudes, with a low standard deviation (RSD; 3%), indicating that the fabricated glucose sensors were highly reproducible. The potential stability and reproducibility of the modified electrode were indexed to the high chemical stability of the CuO nanostructures synthesized in this study. The lifetime usability of our developed glucose sensor was monitored by storing the modified electrodes in air under ambient environmental conditions and intermittently measuring the current response during glucose oxidation. The modified electrode was found to retain approximately 98% of the initial current response after a 2-month storage period. Additionally, six modified electrodes were scanned using CV (50 mV/s) in the presence of 0.5 mM glucose to evaluate the glucose sensor reproducibility under similar conditions ( Figure 9). The peak currents from CV calibration plot responses from all electrodes were of similar amplitudes, with a low standard deviation (RSD; 3%), indicating that the fabricated glucose sensors were highly reproducible. The potential stability and reproducibility of the modified electrode were indexed to the high chemical stability of the CuO nanostructures synthesized in this study.  The lifetime usability of our developed glucose sensor was monitored by storing the modified electrodes in air under ambient environmental conditions and intermittently measuring the current response during glucose oxidation. The modified electrode was found to retain approximately 98% of the initial current response after a 2-month storage period. Additionally, six modified electrodes were scanned using CV (50 mV/s) in the presence of 0.5 mM glucose to evaluate the glucose sensor reproducibility under similar conditions ( Figure 9). The peak currents from CV calibration plot responses from all electrodes were of similar amplitudes, with a low standard deviation (RSD; 3%), indicating that the fabricated glucose sensors were highly reproducible. The potential stability and reproducibility of the modified electrode were indexed to the high chemical stability of the CuO nanostructures synthesized in this study. To evaluate a practical, routine analysis application for the presented enzyme-free glucose sensor, modified electrodes were utilized to detect the glucose levels in fresh serum samples. Furthermore, The quantified values of glucose in the serum samples obtained using the fabricated glucose sensor using an analytical recovery method were satisfactory, as shown in Table 2. This indicated that the enzyme-free glucose sensor has a practical application in clinical glucose determination. When the modified electrodes were rinsed with deionized water and reused in the serum samples, the sensor replicated approximately 99% of its original response, indicating high sensor reproducibility through repetitive use. The results of the presented CuO-nanostructure-modified GCE were compared with other non-enzymatic glucose sensors reported in the literature, and the performance of our proposed sensor was found to be superior (Table 1). This superiority may be attributed to the unique CuO nanostructure features that were obtained in the presence of lysine as a soft template.

Conclusions
In this study, a facile approach was adapted in the synthesis of new CuO nanostructures using a hydrothermal method. The synthesized CuO nanomaterial was cost effective and could be used in the development of a robust, enzyme-free glucose sensor. The analytical features of the glucose sensor were highly attractive and included a wide linear range, high sensitivity, quick response time, and low limit of detection. The presented enzyme-free glucose sensor showed high selectivity, stability, and reproducibility. Furthermore, the modified electrodes were used to quantify the glucose concentrations in fresh serum samples. The measured glucose concentrations were found to be similar to those values obtained using analytical quantification. Thus, the presented enzyme-free glucose sensor can be used in a practical application as a tool to determine clinical glucose levels.
Author Contributions: Qurrat-ul-Ain performed the some experiments, Aneela Tahira did the rest experiments, Arfana Begum Mallah provided the facilities to carry out this research work, Muhammad Ishaque Abro did SEM and XRD measurements, Siraj supervise the work, Zafar Hussain Ibupoto wrote the most parts of manuscript and Magnus Willander did the editing and finalize the manuscript for publication in the presented research work.

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