Eclet. Quim. 49 | e-1497, 2024 https://doi.org/10.26850/1678-4618.eq.v49.2024.e1497 ISSN 1678-4618 page 1/9 1Cape Peninsula University of Technology, Faculty of Applied Sciences, Cape Town, South Africa. 2Federal University of Goiás, Faculty of Pharmacy, Goiás, Brazil. +Corresponding author: Vernon Somerset, Phone: +2721959 6116, Email address: vsomerset@gmail.com Original Article Electrochemical sensing of uric acid using bismuth- silver bimetallic nanoparticles modified sensor Charlton Van der Horst1 , Eric de Souza Gil2 , Vernon Somerset1+ Abstract We showcase in this investigation a GCE/Bi–Ag electrochemical nanosensor for uric acid (UA) detection in commercial fruit juice samples. These GCE/Bi–Ag nanosensor electrochemical performances were studied using cyclic voltammetry (CV) and differential pulse voltammetry (DPV) modes showing excellent electrochemical properties toward UA detection in contrast with the clean GCE. Using the fabricated nanosensor, we exploited DPV measurements to detect UA at a meager limit of detection (0.6 μmol/L, S/N = 3) and linearity between 5.0 and 80 μmol/L UA. Furthermore, the GCE/Bi–Ag nanosensor illustrates good repeatability and reproducibility with 3.80% and RSDs of 3.22%, respectively. The GCE/Bi–Ag nanosensor was effectively exploited to determine UA in actual fruit juice samples showing excellent recoveries, indicating that it can be a promising alternative sensor for food analytical applications. Article History Received June 04, 2023 Accepted August 23, 2024 Published December 24, 2024 Keywords 1. GCE/Bi–AgNPs; 2. electrochemical sensor; 3. uric acid; 4. fruit juice samples. Section Editors Paulo Clairmont Feitosa Lima Gomes Patricia Hatsue Suegama Highlights Novel GCE/Bi–Ag nanosensor constructed for the individual detection of uric acid. Sensor successfully applied for electroanalysis of fruit juices. Nanomaterials of Bi–AgNPs have highly dispersed active sites with high surface area. The nanosensor obtained a detection limit of 0.6 µmol/L (S/N = 3). GCE/Bi–Ag nanosensor illustrates good repeatability and reproducibility. https://doi.org/10.26850/1678-4618.eq.v49.2024.e1497 https://ror.org/056e9h402 https://ror.org/0039d5757 mailto:vsomerset@gmail.com mailto:cvanderhorst01@gmail.com mailto:ericsgil@gmail.com mailto:vsomerset@gmail.com https://orcid.org/0000-0001-9229-1957 https://orcid.org/0000-0001-9161-0127 https://orcid.org/0000-0001-8643-1853 Original Article https://doi.org/10.26850/1678-4618.eq.v49.2024.e1497 Eclet. Quim. 49 | e-1497, 2024 ISSN 1678-4618 page 2/9 1. Introduction Uric acid (UA) or (2,6,8–trihydroxypurine) is in the human body the vital end product for the metabolism of purine and is present in blood serum and urine (Erden and Kilic, 2013; Lakshmi et al., 2011). The correct levels of UA in blood samples are between 0.13 to 0.46 mM and in urine between 2.49 to 4.46 mM (Huang et al., 2004; Raj and Ohsaka, 2001). An excess of UA in blood serum causes hypertension, gout, renal disease, and cardiovascular disease (Choi et al., 2005; Kanbay et al., 2016; Papavasileiou et al., 2016; Riches et al., 2009; Wan et al., 2015), whereas low levels can cause Parkinson's disease, optic disease, and Alzheimer's disease (Lakshmi et al., 2011; Misra et al., 2013). So, the rapid determination of uric acid (UA) with high accuracy and sensitivity using low–cost sensors in serum, urine, fruit juices, and other food products with abnormal levels of UA. It will alert concerned persons to the abnormal levels of UA and take immediate action (therapy). Medical check-ups always involve laboratory setup, bulky instrumentation, trained technicians, pre–treatment, and time do not meet this requirement. Many analytical methods detect UA in different samples, such as chromatography (Li et al., 2015; Luo et al., 2013) and spectroscopy (Boroumand et al., 2017). However, those methods require bulky instrumentation, harmful solvent, sample pre– treatment, skilled technicians, time, and cost. To overcome these drawbacks of conventional analytical methods, biosensors and electrochemical sensors have received much attention due to the advantages of high selectivity, sensitivity, and rapid response (Raj and Ohsaka, 2001). Many reports have applied various types of modified electrodes in to analyse UA samples. These various types of modified electrodes include graphene nanocomposites (Bai et al., 2017; Yue et al., 2015; Zhang et al., 2016), modified carbon paste electrodes (Beitollahi and Sheikhshoaie, 2011; Ganesh et al., 2015), multi–walled carbon nanotubes (Wayu et al., 2016), quantum dots (Abbas et al., 2019), polymers (Sadikoglu et al., 2012), and gold nanoparticles (Ali et al., 2017). Bai et al. (2017) described the fabrication of a biosensor for UA detection in urine samples that includes cationic poly(diallyldimethylammonium chloride) functionalized reduced graphene oxide and polyoxometalates clusters combined with anionic Au nanoparticles. This biosensor has provided acceptable analytical features such as excellent linearity with a low detection limit. Mahmoudian et al. (2019) synthesized α–Fe2O3/polyaniline nanotube (PAnNTs) composite to construct an electrochemical nanosensor for the determination of UA in urine samples. This sensor also showed good linearity with a low detection limit. The anti–interference of the nanosensor was good by adding interfering acids such as citric acid and ascorbic acid (AA). Recently, Fukuda et al. (2020) have exploited a thin film biosensor that consists of carboxymethylcellulose/ uricase dispersed gold/carbon nanotube for UA detection in blood and urine samples. The constructed biosensor exhibited a low limit of detection, wide linear range, and excellent sensitivity. This report is the first individual determination of UA with other biomolecules as interferences in commercial fruit juice samples by the electrochemical measurement with GCE/Bi–Ag nanosensor. In literature, a research group synthesized novel bismuth– silver bimetallic nanoparticles and successfully applied them in the construction of an electrochemical nanosensor and a biosensor for the detection of platinum group metals (PGMs) (Van der Horst, 2015; Van der Horst et al., 2015a; 2015b; 2016a; 2017a; 2018), AA (Van der Horst et al., 2016b; Van der Horst and Somerset, 2022), and hydrogen peroxide (Van der Horst et al., 2017b), respectively. Recently, they also used the GCE/Bi–AgNPs nanosensor in the individual and simultaneous detection of caffeine, AA, and paracetamol in pharmaceutical formulae (Van der Horst et al., 2020). These studies make the GCE/Bi–AgNPs nanosensor attractive for the individual determination of UA in commercial fruit juice samples. To date, there's no investigation reported for detecting UA in commercial fruit juice samples by the electrochemical method using Bi–AgNPs drop coated onto a glassy carbon electrode. Only AA detection in commercial fruit juice samples was reported in the literature (Brainina et al., 2020; Das and Sharma, 2020). This investigation showcases that the GCE/Bi–AgNPs nanosensor exhibited good electrocatalytic activity towards UA detection in model solutions. This GCE/Bi–AgNPs nanosensor obtained a low detection limit, excellent selectivity, wide linearity range, and high sensitivity for the detection of UA. Further, this fabricated nanosensor was utilized for UA determination with satisfactory results using commercial fruit juice samples. 2. Experimental 2.1. Materials This investigation used analytical–grade chemicals, and we didn't purify them further. Bismuth–silver nanoparticles were prepared by adding (Bi(NO3)3) and AgNO3 to HNO3 solution. Citric acid was added to reduce the two salts to Bi–AgNPs. We prepared phosphate buffer (PB) solutions by adding NaH2PO4 to Na2HPO4, and we adjusted the pH with NaOH and H3PO4. UA's stock solutions were prepared by weakly dissolving UA in a freshly PB solution. Throughout this investigation, the diluting of stock solutions in freshly PB (pH = 5.0) to prepare diluted standard solutions. 2.2. Instrumentation We performed voltammetric measurements with an Epsilon electrochemical analyzer (BASi Instruments, USA). The instrument was equipped with a conventional system of three electrodes, including a GCE/Bi–AgNPs fabricated by drop coating the Bi–AgNPs on a 1.6 mm diameter BASi disc GCE, a platinum wire that acts as the auxiliary electrode, and an Ag/AgCl/KClsat. reference electrode, respectively. All experiments were performed at conditioned room temperature and in an electrochemical cell (20 mL). 2.3. Working electrode preparation The bimetallic nanoparticles of Bi–Ag were synthesized based on the experimental procedure of our previous work (Van der Horst et al., 2015a). We fabricated the GCE/Bi–AgNPs nanosensor by polishing a bare GCE in a water surrey consisting of alumina (Al2O3) (1.0, 0.3, and 0.05 μm) using a polishing pad. We used deionized water to rinse the clean GCE and ethanol with double distilled water for sonication. The bare GCE was further cleaned using deoxygenated aqueous H2SO4 (0.5 mol/L) in an electrochemical cell by applying cyclic voltammetry (CV) for 11 cycles at 100 mV/s scan rates to obtain a stable CV profile (Silwana et al., 2016). Ultrasonic vibrations were used to form a suspension by dispersed bimetallic bismuth–silver nanoparticles (Bi–AgNPs) in deionized water. A small amount of Bi–AgNPs was dropped onto a clean GCE, resulting in an even Bi–AgNPs film by drying it at ambient temperature. The dried modified GCE/Bi– AgNPs sensor was slightly rinsed with deionized water, and submerged in PB (pH = 5.0), and its reproducibility was increased by scanning it for 13 cycles (Van der Horst et al., 2016b). https://doi.org/10.26850/1678-4618.eq.v49.2024.e1497 Original Article https://doi.org/10.26850/1678-4618.eq.v49.2024.e1497 Eclet. Quim. 49 | e-1497, 2024 ISSN 1678-4618 page 3/9 2.4. Preparation of commercial samples Two commercial fruit juice samples (apple and orange) were obtained at a local supermarket and the preparation was done by filtering 100 mL of the fruit juice samples in a 250 mL Erlenmeyer flask. The filtered fruit juice samples were diluted by taking 1 mL of filtered fruit juice samples in 9 mL 0.1 mol/L PB solution (pH = 5.0) in a 20 mL electrochemical cell. The diluted fruit juice samples were used for UA analysis using DPVs as the analysis mode (Benjamin et al., 2015). 2.5. Determination procedure of uric acid Phosphate buffer solution aliquots (0.1 mol/L, pH 5.0) were transferred into an electrochemical cell. Different differential pulse voltammograms were recorded by increasing concentrations from 5 to 80 µmol/L of UA in the aliquots. The cyclic voltammograms were obtained using a scan rate of 100 mV/s from −0.4 to +1.0 V (vs. Ag/AgCl) ranges. The parameters for the DPV analysis were 4 s pulse width and 50 mV pulse amplitude (Benjamin et al., 2015; Van der Horst et al., 2016b). 3. Results and discussion 3.1. Electrochemical characterization of constructed sensor The electrochemical property studies of the GCE/Bi– AgNPs nanosensor were performed by using cyclic voltammetry (CV) and scan rates studies with [Fe(CN)6]3–/4– solution as the electrochemistry probe. A transmission electron microscope was employed to determine the particle size of the Bi–AgNPs with diameters between 10 and 25 nanometers in Fig. 1a. The particle size distribution indicates that most nanoparticles were 10 and 15 nanometers (Van der Horst et al., 2015a). Figure 1b illustrates that the modification with Bi–AgNPs increases the peak currents of the clean GCE. These phenomena may result from a large surface area and thus increase the electronic conductivity. These results illustrate that Bi–AgNPs were deposited onto the clean GCE surface by drop coating (Fukuda et al., 2020; Mahmoudian et al., 2019). Curve (a) (in Fig. 1b) of the clean GCE demonstrates a pair of redox peaks with a 142 mV peak separation. Figure 1. (a) TEM image for Bi–AgNPs; (b) curve a: CV curves of clean GCE; curve b: GCE/Bi–AgNPs. Furthermore, curve (b) (in Fig. 1b) of the GCE/Bi–AgNPs showcases a very intense redox peak with an approximately 207 mV ΔEp (∆Ep = Epa – Epc; where Epc and Epa stands for cathodic and anodic peak potentials) value greater than the clean GCE. These cathodic, anodic and separation peak potentials are illustrated in Table 1. The more excellent ΔEp value with more significant redox peak currents at the GCE/Bi–AgNPs nanosensor showcases the superior electron transfer kinetics and sizeable active area of the Bi–AgNPs nanosensor surface. Table 1. Illustration of the Epa, Epc and ∆Ep for clean GCE and GCE/Bi–AgNPs. Electrode Epa (mV) Epc (mV) ∆Ep Clean GCE 368 226 142 GCE/Bi–AgNPs 318 111 207 The scan rate studies (Fig. 2a) were employed to study the electron transfer kinetics of the modified GCE/Bi–AgNPs electrode and the clean GCE (Makombe et al., 2016). It is observed that with an increase in scan rate, the peak currents also increase along with the shifting of peak potential to greater values which is a result of the transfer of electrons between [Fe(CN)6]3–/4– and the GCE/Bi–AgNPs nanosensor surface. This phenomenon results in better sensing behavior for the GCE/Bi–AgNPs nanosensor. In the calculation of the active surface area of the fabricated nanosensor, we used the Randles–Sevcik equation (Eq. 1), 𝐼𝑝𝑎 = (2.69 𝑥 105)𝑛3/2𝐷1/2𝐶𝐴𝑣1/2 (1) where n stands for the number of electrons (n = 1), A represents the surface area of the GCE/Bi–AgNPs nanosensor, and C is the concentration of the redox probe (1 mmol/L), D stands for the diffusion coefficient, Ipa stands for oxidation peak current, and ν is the scan rate (V s–1). We construct a profile of Ipa versus the square root of the scan rate (ν1/2) in Fig. 2b, the determined active surface area of the fabricated nanosensor was 0.150 cm2. This active surface area of the fabricated nanosensor is much greater than the surface area of the clean GCE (0.070 cm2). The calculated result showcase that the nanoparticles of Bi–Ag result in a vast surface area of the working electrode. https://doi.org/10.26850/1678-4618.eq.v49.2024.e1497 Original Article https://doi.org/10.26850/1678-4618.eq.v49.2024.e1497 Eclet. Quim. 49 | e-1497, 2024 ISSN 1678-4618 page 4/9 Figure 2. The study of scan rates of GCE/Bi–AgNPs in 0.1 M KCl containing 5.0 mmol/L [Fe(CN)6]3–/4– in (a) The profile of Ipa vs. square root of scan rates in (b). 3.2. Effect of various pHs on UA detection The pH value is significant in detecting UA and was optimized by measuring the DPV responses of the constructed nanosensor in 80 μmol/L UA concentration. This study exploited different pH ranges of PBS to investigate the influences of the oxidation of UA peak currents. We studied the effect of pH (0.1 mol/L PB) on the DPV determination of UA in the range of pH 4.0 to pH 8.0 (N = 3). Figure 3a illustrates that the pH increases linearly between pH 4.0 and 5.0 and sharply declines from 5.0 to 8.0. The pH 5.0 has the highest anodic peak current responses, according to Fig. 3a. In this study, pH 5.0 was chosen as the optimum pH and was exploited as the supporting electrolyte in all DPV measurements. Figure 4 illustrates the solution dependence on UA electrooxidation on the Bi–Ag/GCE nanosensor. The electrons and protons in this mechanism equally play their part in the oxidation of UA. Figure 3. (a) pH optimization of 0.1 mol/L PBS; (b) curve a: CV curves for 80 µmol/L UA at clean GCE; curve b: constructed nanosensor; (c) Cyclic voltammograms for 80 µmol/L UA at GCE/Bi–AgNPs nanosensor in a 0.1 mol/L PBS (pH = 5.0) at scan rates of 20 to 160 mV s–1; (d) Profile for peak current versus square root of scan rates. https://doi.org/10.26850/1678-4618.eq.v49.2024.e1497 Original Article https://doi.org/10.26850/1678-4618.eq.v49.2024.e1497 Eclet. Quim. 49 | e-1497, 2024 ISSN 1678-4618 page 5/9 Figure 4. A Mechanism for the electrochemical oxidation of UA. Figure 3b, we compared the CV of the constructed nanosensor with the CV of clean GCE using an 80 µmol/L UA solution. The constructed GCE/Bi–AgNPs nanosensor had a higher current response, showing that the electrochemical performance is excellent for UA sensing. The values of the anodic peak potential of UA at the GCE/Bi–AgNPs nanosensor are at about 440 mV. The chemically modified electrodes used to determine UA concentration also showed similar oxidation peak values (Liu et al., 2019; Makombe et al., 2016). 3.3 Effect of scan rates on UA detection Cyclic voltammetry was used for scan rate studies of 80 µmol/L UA at the fabricated nanosensor in a 0.1 mol/L PBS (pH = 5.0) using increasing scan rates. As showcased in Fig. 3c, the anodic peak currents increase and shift to positive peak potentials with increasing scans of 20 to 160 mV s–1. The oxidation and reduction peak currents for UA at GCE/Bi–AgNPs nanosensor generated linear profiles with linear equations are shown in Fig. 3d. We found that the oxidation peak currents versus the square root of the scan rate (√𝑣) obey linearity. The profile equation was expressed as Ipa = 2.01 × 10–8 v1/2 (mV s–1) – 7.0 × 10–7 (R2 = 0.994) and Ipc = 7.1 × 10–9 v1/2 (mV s–1) –3.62 × 10– 8 (R2 = 0.998). These equations suggest a diffusion–controlled process at the surface of the GCE/Bi–AgNPs sensor (Sangamithirai et al., 2018). The profile of Epa and Epc versus ln v also showcase linearity with profile equations as Epa = –5.09 × 10– 5 ln v +1.14 × 10–4 (R2 = 0.993) and Epc = 4.63 × 10–5 ln v –4.13 × 10–5 (R2 = 0.996). We used Laviron’s Equations to calculate the electrochemical parameters such as n, α, and ks, which refer to the number of electrons transferred, the electron transfer coefficient, and the standard electron transfer rate constant (Laviron, 1979). 𝐸𝑝𝑎 = 𝐸0′+2.3𝑅𝑇 (1−𝛼)𝑛𝐹 𝑙𝑜𝑔𝑣 (2) 𝐸𝑝𝑐 = 𝐸0′−2.3𝑅𝑇 𝛼𝑛𝐹 𝑙𝑜𝑔𝑣 (3) 𝑙𝑜𝑔𝑘𝑠 = 𝛼 log(1 − 𝛼) + (1 − 𝛼) log 𝛼 − 𝑙𝑜𝑔( 𝑅𝑇 𝑛𝐹𝑣 ) − (1−𝛼)𝛼𝑛𝐹∆𝐸𝑝 2.3𝑅𝑇 (4) we were applying Eqs. 2 and 3, and the calculated values of n and α were reported as 2.1 and 0.87. Then, from Eq. 4, we calculated the value for ks to be 0.61 s–1. 3.4. DPV analysis of UA Electrochemical measurements were recorded for UA in 80 µmol/L of UA model solutions at a GCE/Bi–AgNPs nanosensor, and clean GCE using DPV are demonstrated in Fig. 5a. Oxidation peak currents that are well–defined were recorded for UA in both cases. For the GCE/Bi–AgNPs electrode higher peak current value was produced and observed in the voltammogram. As followed at the clean GCE, the anodic peak potential of UA is recorded at +0.35 V (vs. Ag/AgCl), and at the fabricated nanosensor, the oxidation peak potential shifted to +0.39 V (vs. Ag/AgCl). The individual determination of UA at the fabricated nanosensor surface was investigated in a 0.1 mol/L PBS (pH 5.0) using DPV as the analytical mode. The UA oxidation peak currents in Fig. 5b increase linearly with increasing concentrations of UA under optimal experimental conditions. The constructed profile showcases that UA's linear detection range is 5 to 80 µmol/L. The profile equation is illustrated by Ipa (µA) = –2.63 × 10–8 CUA (µmol/L) –1.59 × 10–6 with R2 of 0.9964 and showcases the linear relationship. The detection limit measured for UA using the GCE/Bi–AgNPs nanosensor is down to 0.6 µmol/L at S/N = 3 (LOD = 3Sb/q; where Sb refers to the standard deviation of the blank and q is the slope of the linear plot). Additionally, Table 1 compares the linear range and the detection limit for the GCE/Bi–AgNPs nanosensor with other similar electrode materials. In Table 2, we concluded that the GCE/Bi– AgNPs nanosensor performance is comparable to sensors modified by other electrode materials, including linear ranges and the detection limits (LODs). 3.5 Interference studies Possible substances in samples of natural juices that might interfere in the determination of UA at the fabricated nanosensor surface were studied by adding different ions to a 0.1 mol/L PBS (pH = 5.0). For this study, ions that might interfere, such as AA, K+, Na+, SO4 2–, and CAF, were added to an equal amount of 40 µmol/L UA, and the sensor was immersed in the mixed solution. According to the results in Fig. 6a, AA and CAF did not show interference in the determination of UA in the presence of these interfering ions. In contrast, K+ and Na+ showed interference in the determination of UA in the presence of these two positive interfering ions. The anodic peak current for K+ and Na+ was significantly lower than that of AA and CAF. The same trend was observed for SO4 2– anodic peak currents, showing that these ions interfere in UA's determination, indicating that this electrochemical sensor has reasonable specificity towards UA. https://doi.org/10.26850/1678-4618.eq.v49.2024.e1497 Original Article https://doi.org/10.26850/1678-4618.eq.v49.2024.e1497 Eclet. Quim. 49 | e-1497, 2024 ISSN 1678-4618 page 6/9 Figure 5. (a) curve a: DPV results of the clean GCE; curve b: versus the fabricated nanosensor, both in 80 µmol/L UA solution were illustrated; (b) the DPV results of 0.1 mol/L PBS (pH = 5.0) containing increasing concentrations of UA and (inset) the corresponding profile for UA analysis. Figure 6. (a) Interference test of UA in the presence of AA, CAF, K+, Na+, and SO4 2– that might interfere at a GCE/Bi–AgNPs nanosensor surface; (b) Stability tests of GCE/Bi–AgNPs nanosensor. 3.6. Effect of repeatability and stability The repeatability, storage stability, and reproducibility of the GCE/Bi–AgNPs nanosensor were studied using the DPV measurements in 0.1 mol/L PB (pH = 5.0) containing 40 µmol/L of UA. For the storage stability study (Fig. 6b), the sensitivity of the fabricated sensor was measured over eight days under ambient temperature. After eight days, the nanosensor produced an anodic peak current with a slight decrease in the current response. A response current of 80% was observed after eight days. Therefore, the stability results in Fig. 6b of the fabricated nanosensor were good enough and resulted in continual operation. In the case of repeatability in Fig. 7a, ten repetitive measurements were recorded using the same electrode with a relative standard deviation (RSD) of 3.22%. The reproducibility was also studied using six independent measurements with six different sensors constructed under similar conditions. The results obtained for the reproducibility test display a good RSD of 3.80% and are shown in Fig. 7b. The results (Fig. 6b and 7) indicate that the fabricated nanosensor has excellent reproducibility, repeatability, and storage stability for UA detection. Figure 7. (a) illustrates the repeatability analysis of GCE/Bi– AgNPs nanosensor for ten repeated measurements; (b) the reproducibility analysis of GCE/Bi–AgNPs nanosensor for six separate electrodes. https://doi.org/10.26850/1678-4618.eq.v49.2024.e1497 Original Article https://doi.org/10.26850/1678-4618.eq.v49.2024.e1497 Eclet. Quim. 49 | e-1497, 2024 ISSN 1678-4618 page 7/9 Table 2. Illustration of the various sensors used that contain different nanomaterials in the determination of UA. Materials Linear ranges (µmol/L) LOD (µmol/L) References PEDOT/Au NPs 1.5–150 0.08 Ali et al., 2017 CNCo 2.0–110 0.83 Liu et al., 2019 PtNi@MoS2 0.5–600 0.1 Ma et al., 2019 Ta/Ni 1.0–1400 0.1 Zhao et al., 2019 a–Fe2O3/PAn (NTs) 0.01–5.0 0.038 Mahmoudian et al., 2019 Au1Pt2NPs/S–NS–GR 1–1000 0.038 Zhang et al., 2018 HNP–AuAg 5–425 1.0 Hou et al., 2016 ErGO/PEDOT:PSS 10–100 1.08 Wang et al., 2022 2D g–C3N4/WO3 0.01–900 0.0022 Rajesh et al., 2022 Bi–AgNPs 5–80 µM 0.6 This study 3.7. Actual samples analysis The developed GCE/Bi–Ag nanosensor was practically exploited for the electrochemical analysis of UA in some natural fruit juice samples by using a standard addition method. Firstly, the actual samples of fruit juices were diluted ten times with 0.1 mol/L PBS (pH 5.0). This procedure was applied before the detection of UA to decrease the matrix effect without any other treatment. After diluting, we added known quantities of standard UA to the natural fruit juice samples, and recoveries were determined. We also used Eq. 5 for the estimated recovery values of the spiked UA samples. % recoveries = Ci × Co/Cx × 100 (5) where Ci refers to the UA concentration experimentally obtained, Co stands for the unspoked fruit juice samples, and Cx refers to the spiked concentration of UA in the fruit juice samples. In Table 3, the DPV results are illustrated, showing good recoveries ranging from 98.9% to 105.1% (n = 3) and the RSDs ranging from 2.1% to 3.2% for apple juice. In the case of orange juice, the spiked UA sample recoveries ranged from 102% to 109%, with RSDs of 1.89% to 2.76%. The good recoveries for UA indicated the potential usefulness of the GCE/Bi–Ag nanosensor for the practical determination of UA in actual samples. These recovery results suggest that the electrochemical procedure has great potential for accurate, sensitive, easy, and fast detection of UA in natural fruit juice samples. Table 3. Analysis of UA in actual fruit juice samples (n = 3) using GCE/Bi–Ag nanosensor. Sample Added (µmol/L) Found (µmol/L) Recovery (%) RSD (%) Apple Juice 10 10.4 104 2.1 20 19.78 98.9 2.5 30 31.53 105.1 3.2 Orange Juice 10 10.9 109 1.89 20 20.7 103.5 2.76 30 30.6 102 2.03 4. Conclusions In summary, we have constructed an electrochemical procedure using for the first time a GCE/Bi–Ag nanosensor for the individual detection of UA in actual samples of fruit juices. The results obtained in this investigation conclude that the Bi–AgNPs have highly dispersed active sites with high surface area. These properties displayed higher peak currents for the fabricated nanosensor in contrast with the clean GCE. This phenomenon is due to enhanced electrocatalytic activity toward the oxidation of UA in model standard solutions. At the surface of the fabricated nanosensor well, distinct peaks for UA analysis were recorded with good linear regression responses of the currents for the oxidation peak. The nanosensor obtained a detection limit of 0.6 µmol/L with an R² = 0.999 for UA detection. Moreover, the GCE/Bi–Ag nanosensor brought good reproducibility, repeatability and stability, excellent anti–interference ability, and satisfied recoveries for the UA detection in actual samples. Authors’ contributions Conceptualization: Charlton Van der Horst; Vernon Somerset; Data curation: Charlton Van der Horst; Vernon Somerset; Formal Analysis: Charlton Van der Horst; Vernon Somerset; Funding acquisition: Vernon Somerset; Investigation: Charlton Van der Horst; Vernon Somerset; Methodology: Charlton Van der Horst; Vernon Somerset; Eric de Souza Gil; Project administration: Vernon Somerset; Resources: Vernon Somerset; Software: Not applicable; Supervision: Vernon Somerset; Validation: Eric de Souza Gil; Visualization: Charlton Van der Horst; Vernon Somerset; Eric de Souza Gil; Writing – original draft: Charlton Van der Horst; Vernon Somerset; Writing – review & editing: Charlton Van der Horst; Vernon Somerset; Eric de Souza Gil. Data availability statement All data sets were generated or analyzed in the current study. Funding Not applicable. Acknowledgments The authors acknowledge the laboratory infrastructure and administrative support provided by the Cape Peninsula University of Technology (CPUT). The collaboration with the Universidade Federal de Goiás, Brazil research laboratories is greatly acknowledged. Conflict of interest The authors declare that there is no conflict of interest. https://doi.org/10.26850/1678-4618.eq.v49.2024.e1497 Original Article https://doi.org/10.26850/1678-4618.eq.v49.2024.e1497 Eclet. Quim. 49 | e-1497, 2024 ISSN 1678-4618 page 8/9 References Abbas, M. W.; Soomro, R. A.; Kalwar, N. H.; Zahoor, M.; Avci, A.; Pehlivan, E.; Hallam, K. R.; Willander, M. Carbon quantum dot coated Fe3O4 hybrid composites for sensitive electrochemical detection of uric acid. Microchem. J. 2019, 146, 517. https://doi.org/10.1016/j.microc.2019.01.034 Ali, A.; Jamal, R.; Abdiryim, T.; Huang, X. 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