biosensors Article Green-Mediated Synthesis of NiCo2O4 Nanostructures Using Radish White Peel Extract for the Sensitive and Selective Enzyme-Free Detection of Uric Acid Abdul Ghaffar Solangi 1 , Aneela Tahira 1 , Baradi Waryani 2 , Abdul Sattar Chang 3 , Tajnees Pirzada 1 , Ayman Nafady 4 , Elmuez A. Dawi 5 , Lama M. A. Saleem 6 , Mohsen Padervand 7 , Abd Al Karim Haj Ismail 5 , Kangle Lv 8 , Brigitte Vigolo 9 and Zafar Hussain Ibupoto 3, * 1 2 3 4 5 6 7 8 9 * Citation: Solangi, A.G.; Tahira, A.; Waryani, B.; Chang, A.S.; Pirzada, T.; Nafady, A.; Dawi, E.A.; Saleem, L.M.A.; Padervand, M.; Haj Ismail, A.A.K.; et al. Green-Mediated Synthesis of NiCo2 O4 Nanostructures Using Radish White Peel Extract for the Sensitive and Selective Enzyme-Free Detection of Uric Acid. Biosensors 2023, 13, 780. https:// doi.org/10.3390/bios13080780 Received: 27 June 2023 Revised: 25 July 2023 Accepted: 30 July 2023 Published: 1 August 2023 Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// Institute of Chemistry, Shah Abdul Latif University Khairpur Mirs, Khairpur Mirs 66111, Pakistan; ghaffarchemistry786@gmail.com (A.G.S.); aneela.tahira@salu.edu.pk (A.T.); tajnees@salu.edu.pk (T.P.) Department of Fresh Water Biology and Fisheries, University of Sindh, Jamshoro 76080, Pakistan; baradiw@usindh.edu.pk Institute of Chemistry, University of Sindh, Jamshoro 76080, Pakistan; asattar.chang@usindh.edu.pk Department of Chemistry, College of Science, King Saud University, Riyadh 11451, Saudi Arabia; anafady@ksu.edu.sa Nonlinear Dynamics Research Centre (NDRC), Ajman University, Ajman P.O. Box 346, United Arab Emirates; e.dawi@ajman.ac.ae (E.A.D.); a.hajismail@ajman.ac.ae (A.A.K.H.I.) Biomolecular Science, Earth and Life Science, Amsterdam University, 1081 HV Amsterdam, The Netherlands; lamysaleem@gmail.com Department of Chemistry, Faculty of Science, University of Maragheh, Maragheh P.O. Box. 55181-83111, Iran; padervand@maragheh.ac.ir College of Resource and Environment, South-Central Minzu University, Wuhan 430074, China; lvkangle@mail.scuec.edu.cn Institut Jean Lamour, Université de Lorraine, CNRS, IJL, F-54000 Nancy, France; brigitte.vigolo@univ-lorraine.fr Correspondence: zaffar.ibhupoto@usindh.edu.pk Abstract: The ability to measure uric acid (UA) non-enzymatically in human blood has been demonstrated through the use of a simple and efficient electrochemical method. A phytochemical extract from radish white peel extract improved the electrocatalytic performance of nickel–cobalt bimetallic oxide (NiCo2 O4 ) during a hydrothermal process through abundant surface holes of oxides, an alteration of morphology, an excellent crystal quality, and increased Co(III) and Ni(II) chemical states. The surface structure, morphology, crystalline quality, and chemical composition were determined using a variety of analytical techniques, including powder X-ray diffraction (XRD), scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HR-TEM), and X-ray photoelectron spectroscopy (XPS). The electrochemical characterization by CV revealed a linear range of UA from 0.1 mM to 8 mM, with a detection limit of 0.005 mM and a limit of quantification (LOQ) of 0.008 mM. A study of the sensitivity of NiCo2 O4 nanostructures modified on the surface to UA detection with amperometry has revealed a linear range from 0.1 mM to 4 mM for detection. High stability, repeatability, and selectivity were associated with the enhanced electrochemical performance of non-enzymatic UA sensing. A significant contribution to the full outperforming sensing characterization can be attributed to the tailoring of surface properties of NiCo2 O4 nanostructures. EIS analysis revealed a low charge-transfer resistance of 114,970 Ohms that offered NiCo2 O4 nanostructures prepared with 5 mL of radish white peel extract, confirming an enhanced performance of the presented non-enzymatic UA sensor. As well as testing the practicality of the UA sensor, blood samples from human beings were also tested for UA. Due to its high sensitivity, stability, selectivity, repeatability, and simplicity, the developed non-enzymatic UA sensor is ideal for monitoring UA for a wide range of concentrations in biological matrixes. Keywords: non-enzymatic uric acid sensor; phytochemicals; radish white peel extract; biological matrix creativecommons.org/licenses/by/ 4.0/). Biosensors 2023, 13, 780. https://doi.org/10.3390/bios13080780 https://www.mdpi.com/journal/biosensors Biosensors 2023, 13, 780 2 of 21 1. Introduction A purine-based compound called alkaloids is used by our bodies to produce uric acid (UA) [1,2]. UA concentrations in serum samples range between 0.13 and 0.46 mM, whereas UA concentrations in urine samples range between 1.49 and 4.50 mM [3]. An abnormal level of UA in the human body is associated with several chronic and life-threatening diseases, including preeclampsia, arthritis, renal dysfunction, cardiovascular disease, obesity, high blood pressure, and kidney disease [4–7]. An increase in UA levels in blood serum has been identified as a major cause of cardiac disease [8]. For this reason, it is essential to measure and monitor UA in order to prevent the onset of dangerous conditions and to reduce the risk of premature death. Several analytical methods have been developed to measure UA as a result of this high importance, including colorimetric enzymatic tests [9]. Capillary electrophoresis method [10], surface-enhanced Raman scattering [11], liquid chromatography [12], electrochemical method [13], fluorescence spectroscopy [14], and chemiluminescence [15] are among the methods used. It is common for these analytical methods to be extremely expensive, time-consuming, and complex to operate. However, electrochemical methods are inexpensive, sensitive, and selective, thus they have been extensively studied [16–21]. A number of electrochemical approaches have been used to quantify UA’s high electrooxidation properties, including enzyme-based and enzymefree methods [22–26]. Due to the high costs associated with enzyme immobilization and denatured issues with uricase enzyme during storage, non-enzymatic approaches have become increasingly popular as alternatives to enzyme-based approaches [27]. In nonenzymatic approaches, highly electrocatalytic materials are always desirable [16,18]. To realize non-enzymatic UA sensors quickly, it will be increasingly necessary to develop new materials with tailored surfaces that outperform electrocatalytic properties. This task, however, appears to be challenging because novel materials with tailored surfaces do not possess electrocatalytic properties. For the development of highly catalytic materials for non-enzymatic UA sensors, several challenges must be overcome, such as poor electrical conductivity, a limited number of catalytic sites, and chemical stability concerns. Therefore, numerous electrocatalytic materials have been developed and investigated for the development of non-enzymatic sensors [28–31]. A significant electrochemical activity of metal oxides makes them potentially suitable for this application [32–34]. As a result of its high electrical conductivity and favorable redox properties, a bimetallic oxide, particularly nickel–cobalt oxide (NiCo2 O4 ), has been identified as a potential candidate for the development of non-enzymatic sensors. As NiCo2 O4 nanostructures exhibit poor electrochemical performance due to their limited surface properties, they have been utilized in composites with other nanostructured materials, such as Fe2 O3 @ NiCo2 O4 [35], MnO2 /NiCo2 O4 [36], Co3 O4 /NiCo2 O4 [37,38], and NiCo2 O4 @ graphene [39]. It has been observed that composite NiCo2 O4 systems exhibit enhanced charge transfer between electrode and analyte. Several morphologies of NiCo2 O4 have been prepared, including nanotubes [37], nanorods [36], nanospheres [35], and nanosheets [33]. In spite of NiCo2 O4 ’s diverse architecture, however, the material fails to perform as expected [35,36,38]. As a result, it is imperative to identify new strategies for improving the electrochemical performance of NiCo2 O4 in order to develop more sensitive non-enzymatic UA sensors. Recent years have seen a great deal of interest in green chemistry due to its simplicity, eco-friendliness, low cost, and environmental friendliness [39–42]. Several natural products obtained from biomass wastes can be used to tailor the surface properties of nanostructured materials, including catalytic sites and charge transfer properties [41,42]. Only a few studies have been conducted on the synthesis of NiCo2 O4 nanostructured materials from biomass wastes. The present study examines for the first time the effect of radish white peel extract (Raphanus sativus) on the morphology, crystal defect, and surface properties of NiCo2 O4 that will be used for fabricating a non-enzymatic UA sensor. Radish white peel extract contains a wide range of phytochemicals, including alkaloids, glucosinolates, phenolic compounds, organic acids, anthocyanins, and isothiocyanates. [40,41] (Scheme 1). Biosensors 2023, 13, x FOR PEER REVIEW 3 of 21 Biosensors 2023, 13, 780 3 of 21 extract contains a wide range of phytochemicals, including alkaloids, glucosinolates, phenolic compounds, organic acids, anthocyanins, and isothiocyanates. [40,41] (Scheme 1). S S S S C N Pungent principal isothiocyanates NH Phenylethanamine NH2 (III) (II) 2-Pyrrolidinethione (I) O HO O O OH N H HO N-Methylphenylethanamine HO Esculetin (V) (IV) 4-Hydroxycinnamic acid (VI) HO O O O O HO HO O OH OH O Caf f eic Acid (VII) Scopoletin (VIII) HO Ferulic acid (IX) O O OH O OH OH O Coumarinic acid (X) OH HO HO p-hydroxybenzoic acid, (XI) Vanillic acid (XII) Scheme1.1.The Thevarious variousphytochemicals phytochemicalspresent presentininthe theradish radish(Raphanus (Raphanussativus) sativus)peel peelextract. extract. Scheme Theradish radish white peel extract possesses major phytochemicals, like as 4-hyThe white peel extract possesses major phytochemicals, like as 4-hydroxycinnamic droxycinnamic caffeic acid, and which isothiocyanates, were used as acid, caffeic acid,acid, ferulic acid,acid, and ferulic isothiocyanates, were usedwhich as stabilizing, capping, and reducing agents, and played a significant role atoward enhanced electrochemical stabilizing, capping, and reducing agents, and played significant role toward enhanced properties of NiCo electrochemical properties of NiCo2O4 nanostructures. 2 O4 nanostructures. In Inthis thisstudy, study,we wehave haveused usedradish radishwhite whitepeel peelextracts extractsfor forthe thesurface surfaceengineering engineeringofof NiCo O nanostructures by hydrothermal methods. The volume of extracts from peels peels was NiCo2 2O44 nanostructures by hydrothermal methods. The volume of extracts from examined in order to determine the ideal at which NiCo2NiCo O4 nanostructures was examined in order to determine the concentration ideal concentration at which 2O4 nanostruccould scaled up forup high production. An extensive linearlinear rangerange of UAof tures be could be scaled forperformance high performance production. An extensive detection was detected using surface-modified NiCo2 O4 nanostructures ranging from 0.1 mM to 8 mM. Biosensors 2023, 13, x FOR PEER REVIEW Biosensors 2023, 13, 780 4 of 21 UA detection was detected using surface-modified NiCo2O4 nanostructures ranging from 0.1 mM to 8 mM. 4 of 21 2. Experimental Section 2.1. Chemicals Used 2. Experimental Section In this cobalt chloride hexahydrate (CoCl2·6H2O), nickel chloride hexahydrate 2.1.study, Chemicals Used (NiCl2·6H2O), glucose, lactic acid, uric acid, sodium chloride, potassium chloride, ascorbic In this study, cobalt chloride hexahydrate (CoCl2 ·6H2 O), nickel chloride hexahydrate acid, sodium hydroxide, urea, hydrochloric acid, disodium phosphate, and monopotas(NiCl2 ·6H2 O), glucose, lactic acid, uric acid, sodium chloride, potassium chloride, ascorbic sium phosphate were applied without pretreatment. We obtained all analytical grade acid, sodium hydroxide, urea, hydrochloric acid, disodium phosphate, and monopotassium chemical reagents from Sigma Aldrich, Karachi, and Sindh Pakistan. UA detection was phosphate were applied without pretreatment. We obtained all analytical grade chemical performed by preparing the desired solutions in deionized water, followed by preparing reagents from Sigma Aldrich, Karachi, and Sindh Pakistan. UA detection was performed by a buffer solution containing 0.1 M phosphate at pH 7.0 for UA detection. preparing the desired solutions in deionized water, followed by preparing a buffer solution containing 0.1 M phosphate at pH 7.0 for UA detection. 2.2. Green-Mediated Synthesis of NiCo2O4 Nanostructures Using Radish White Peel Extract A hydrothermal method was ofused phytochemicalUsing synthesis of NiCo 4 2.2. Green-Mediated Synthesis NiCo2for O4 Nanostructures Radish White Peel2OExtract nanostructures. The radish white was purchased, washed with deionized water, and alA hydrothermal method was used for phytochemical synthesis of NiCo 2 O4 nanoslowed totructures. dry at room to the growth process. pieceswater, of radish Thetemperature radish whiteprior was purchased, washed withSmall deionized and allowed white were chipped aftertemperature the peel hadprior been removed. An automatic then to dry at room to the growth process. juicer Small was pieces of used radish white to collectwere juice chipped from the after peel. the An peel extract of the peel was used in the subsequent synthesis had been removed. An automatic juicer was then used to of NiCo2collect O4 nanostructures. NiCo 2O4An nanostructures prepared using 0.1 M cobaltsynthesis juice from the peel. extract of the were peel was used in the subsequent chloride of hexahydrate, 0.1 M urea, andNiCo 0.0152 O M4 nickel chloride hexahydrate in 100 mL0.1 ofM cobalt NiCo2 O4 nanostructures. nanostructures were prepared using deionizedchloride water through a hydrothermal Various amounts of radish white peel hexahydrate, 0.1 M urea,process. and 0.015 M nickel chloride hexahydrate in 100 mL of extract were used towater synthesize NiCo 2O4 nanostructures. TheVarious pH of the precursor solution deionized through a hydrothermal process. amounts of radish white peel was 8.2 and 7.1, respectively. the growth solutions were sealed with aluminum extract were used to Afterward, synthesize NiCo O nanostructures. The pH of the precursor solution 2 4 sheets and grown at 95 °C for five hours. Filter paper was used to collect the bimetallic was 8.2 and 7.1, respectively. Afterward, the growth solutions were sealed with aluminum hydroxide phase, and deionized was hours. used toFilter washpaper it several times.toThe material sheets and grown at 95 ◦water C for five was used collect the bimetallic useddrying to wash times. The material was thenhydroxide thermally phase, roastedand for deionized five hours water at 500 was °C after forit12several h. With the same was then thermally for five were hoursobtained at 500 ◦ Cwithout after drying forradish 12 h. With procedure, pristine NiCo2O4 roasted nanostructures adding whitethe same procedure, pristineofNiCo obtained without adding peel extract. An illustration the synthesis of NiCo2O4were nanostructures as prepared canradish be white 2 O4 nanostructures extract. found in peel Scheme 2. An illustration of the synthesis of NiCo2 O4 nanostructures as prepared can be found in Scheme 2. Scheme 2. Stepwise synthesis of NiCo2 O4 nanostructures using radish white peel extract during method, UA detection, and real blood analysis. Scheme 2.hydrothermal Stepwise synthesis of NiCo 2O4 nanostructures usingsample radish white peel extract during hydrothermal method, UA detection, and real blood sample analysis. 2.3. Physical Investigations on the Surface-Modified NiCo2 O4 Nanostructures An assessment of the morphology of NiCo2 O4 nanostructures was carried out by scanning electron microscopy (SEM: Auto Fine Coater: JEC-3000FC, No. JSM-IT 100, JEOL Japan Model, Tokyo, Japan; the coating performed at 20 mA current for 60 s) using an accelerating voltage of 10 kV. We assessed the crystal quality of radish white peel extract- Biosensors 2023, 13, 780 5 of 21 assisted NiCo2 O4 nanostructures using powder X-ray diffraction (XRD) at 45 kV and 45 mA using CuK radiation (λ = 1.5418 Å) as an X-ray source. The localized nanoscale structure was studied using high-resolution transmission electron microscopy (HRTEM) at a voltage of 200 kV. Utilizing energy dispersive spectroscopy, we were able to quantify the elemental mapping. The chemical composition of the surface was determined using X-ray photoelectron spectroscopy (XPS) in high vacuum. As a reference binding energy, we calibrated the XPS data using C1s at 284.6 eV and deconvolved the XPS features using a Shirley-type background and Voigt curves. 2.4. Non-Enzymatic Sensing of UA onto Surface-Modified NiCo2 O4 Nanostructures A variety of electrochemical methods have been used to characterize the non-enzymatic UA sensor, including cyclic voltammetry, amperometry, electrochemical impedance spectroscopy, and linear sweeping voltammetry. The electrochemical evaluation of NiCo2 O4 nanostructures was conducted using a three-electrode setup. Three electrodes were used: silver–silver chloride (Ag/AgCl, 3.0 M KCl) as a reference electrode, platinum sheet as a counter electrode, and glassy carbon electrode (GCE) as a working electrode. Prior to modification of the GCE, it was polished with an alumina paste of (0.3 µM) and silicon paper and then cleaned with deionized water. The material ink was prepared by dispersing 10 mg of NiCo2 O4 nanostructures in 2.5 m of deionized water and 0.5 mL of Nafion (5%) in 2.5 m of deionized water. We achieved homogeneous material ink after 15 min of an ultrasonic bath. NiCo2 O4 nanostructures were applied to the surface of GCE using a dropcast method. A 10 mM stock solution of UA was prepared in a 0.1 M phosphate buffer solution of pH 7.0. Prior to dissolving the phosphate buffer solution, UA was dissolved in propanol. The selectivity of the non-enzymatic UA sensor was determined with 0.1 mM interfering species, like urea, lactic acid, glucose, ascorbic acid, potassium ions, and sodium ions, in the presence of the same concentration of UA. The linear range of the UA sensor was determined by CV and chronoamperometry methods using various UA concentrations dissolved in 0.1 M phosphate buffer solution (PBS) at pH 7.0. Using this method, it was possible to estimate the low limit of detection of the non-enzymatic sensor [43]. 3. Results and Discussion 3.1. Structural and Morphological Investigations of Radish White Peel Extract-Assisted Synthesis of NiCo2 O4 Nanostructures In Figure 1a, we show diffraction patterns measured by powder XRD on NiCo2 O4 nanostructures that reveal their crystal quality. Furthermore, we investigated the effects of phytochemicals present in the white peel extract of radish on the crystal quality of NiCo2 O4 nanostructures. The reference card number 00-020-0781 confirms that the typical reflections of NiCo2 O4 nanostructures are well matched with the cubic phase of NiCo2 O4 . The diffraction patterns of NiCo2 O4 nanostructures have been identified as (111), (220), (311), (222), (400), (511), and (440), respectively, at 19.40, 31.30, 36.880, 38.590, 44.850, 59.410, and 65.300. The morphology of NiCo2 O4 nanostructures prepared with radish peel extract was examined by SEM. This was performed to compare them with pristine NiCo2 O4 nanostructures, as shown in Figure 1b–f. NiCo2 O4 nanostructures with a high degree of heterogeneity exhibit a typical nanorod-like orientation as shown in Figure 1b. Figure 1c–f illustrates that radish white peel extract altered the morphology of NiCo2 O4 nanostructures toward short-range nanoparticles, confirming the influence of phytochemicals on surface modification. As well as being much smaller in size, nanostructures have a size range between 50 and 100 nm, which is characteristic of nanoparticles. Figure 1f illustrates that radish white peel extract significantly affects the size and morphology of NiCo2 O4 nanostructures. According to Figure 1f, these phytochemicals determined the morphology and allowed the formation of aggregated and irregularly oriented nanostructures with unfavorable surface properties when 10 mL of radish white peel extract was used during the growth process. A phytochemical from radish white peel extract, shown in Scheme 1, contains oxygenated groups that provide ample coordination with nickel and cobalt metallic Biosensors 2023, 13, 780 a size range between 50 and 100 nm, which is characteristic of nanoparticles. Figure 1f illustrates that radish white peel extract significantly affects the size and morphology of NiCo2O4 nanostructures. According to Figure 1f, these phytochemicals determined the 6 of 21 morphology and allowed the formation of aggregated and irregularly oriented nanostructures with unfavorable surface properties when 10 mL of radish white peel extract was used during the growth process. A phytochemical from radish white peel extract, shown in Scheme groups that in provide ample coordination withnanorods nickel ions during 1, thecontains growthoxygenated process, which results morphological changes from cobalt metallic ions duringNiCo the 2growth process, which results in morphological toand nanoparticles. As-prepared O4 nanostructures were examined with HRTEM changes from nanorods to nanoparticles. As-prepared 2O4 nanostructures were eximages and Fourier transform (FFT) patterns in order NiCo to analyze the deep morphological amined and withto HRTEM images and d-spacing. Fourier transform patterns inthat order to nanoparticles analyze the features calculate atomic Figure(FFT) 2a illustrates the deepassembled morphological features and atonanorod-like calculate atomic d-spacing. 2a illustrates that in were in order to form structure. TheFigure HRTEM image shown the nanoparticles in order to form a nanorod-like structure. The HRTEM Figure 2a confirmswere the assembled excellent crystallinity of NiCo O nanostructures. According to 2 4 image shown in Figure 2a confirms the excellent crystallinity of NiCo 2 O 4 nanostructures. Figure 2b, pristine NiCo2 O4 nanostructures have a d-spacing of 0.39 nanometers. Using Accordingmapping. to Figure 2b, pristine NiCo 2O4 nanostructures have a d-spacing of 0.39 nanomeelemental Figure 2b–d illustrates a uniform distribution of Ni, Co, and O. ters. Using elemental mapping. Figure 2b–d illustrates uniform of Ni, Co, Figure 2e illustrates the EDS spectrum, which shows Co,aNi, and Odistribution as the primary elements. and O. Figure 2e illustrates the EDS spectrum, which shows Co, Ni, and O as the primary A TEM and HRTEM examination of NiCo2 O4 nanostructures, as shown in Figure 3a, elements. A TEM and with HRTEM of d-spacing. NiCo2O4 nanostructures, as revealed shown in typical Figwas conducted along the examination calculation of A TEM image ure 3a, was conducted along with the calculation of d-spacing. A TEM image revealed nanoparticle morphologies, and HRTEM confirmed the high crystal quality of NiCo2 O4 typical nanoparticle morphologies, and HRTEM confirmed the high crystal quality of nanostructures (Figure 3). Figure 3a shows that NiCo2 O4 nanostructures exhibit a spinel NiCo2O4 nanostructures (Figure 3). Figure 3a shows that NiCo2O4 nanostructures exhibit crystal structure and a cubic phase as revealed by the FFT analysis. According to Figure 3b– a spinel crystal structure and a cubic phase as revealed by the FFT analysis. According to d, the d-spacing value of this sample was 0.36 nm, in agreement with results published for Figure 3b–d, the d-spacing value of this sample was 0.36 nm, in agreement with results NiCo2 O4 nanostructures. An elemental analysis of these nanostructures utilizing 5 mL of published for NiCo2O4 nanostructures. An elemental analysis of these nanostructures utiradish white peel extract revealed a homogeneous distribution of Co, Ni, and O elements. lizing 5 mL of radish white peel extract revealed a homogeneous distribution of Co, Ni, As shown in Figure 3e, the EDS spectrum indicates that the surface-modified NiCo2 O4 and O elements. As shown in Figure 3e, the EDS spectrum indicates that the surface-modnanostructures prepared using 5 mL of radish white peel extract contain quantified amounts ified NiCo2O4 nanostructures prepared using 5 mL of radish white peel extract contain ofquantified Ni, Co, and O. amounts of Ni, Co, and O. Figure 1. (a) Powder XRD diffraction patterns of pristine, 5 mL, and 10 mL of radish peel extractFigure 1. NiCo (a) Powder XRD diffraction patterns of pristine, 5 mL, and 10 mL of radish peel extractassisted 2O4 nanostructures, (b–f) Corresponding SEM images of (b) pristine, (c,d) 5 mL, and assisted (b–f) Corresponding SEM images of (b) pristine, (c,d) 5 mL, and respectively (e,f) 10 NiCo mL of2 O radish peel extract-assisted NiCo2O4 nanostructures 4 nanostructures, (e,f) 10 mL of radish peel extract-assisted NiCo2 O4 nanostructures respectively. Biosensors 2023, 13, x FOR PEER REVIEW Biosensors 2023, 13, x FOR PEER REVIEW Biosensors 2023, 13, 780 7 of 21 7 of 21 7 of 21 images of of pristine NiCo22O O44 nanostructures nanostructures and and FFT FFT conversion conversion at right Figure 2. (a) TEM/HRTEM TEM/HRTEM images Figure 2. (a) TEM/HRTEM images of pristine NiCo2O4 nanostructures and FFT conversion at right side with d-spacing value; (b–d) corresponding elemental mapping mapping of (e) EDS spectra of pristine side with d-spacing value; (b–d) corresponding elemental mapping of (e) EDS spectra of pristine NiCo NiCo22O O4 nanostructures. nanostructures. NiCo2O44 nanostructures. Figure 3. (a) TEM/HRTEM images of NiCo O nanostructures prepared with 5 mL of radish white Figure 3. (a) TEM/HRTEM images of NiCo22O44nanostructures prepared with 5 mL of radish white Figure 3. (a)and TEM/HRTEM images ofvalue NiCoon 2Oright-hand 4 nanostructures prepared with 5mapping mL of radish peel extract FFT side; (b–d) elemental mapping of (e) (e)white EDS peel extract and FFT with with d-spacing d-spacing value on right-hand side; (b–d) elemental of EDS peel extract and FFT with d-spacing value on right-hand side; (b–d) elemental mapping of (e) EDS spectrum of NiCo O nanostructures prepared with 5 mL of radish white peel extract. spectrum of NiCo22O44 nanostructures prepared with 5 mL of radish white peel extract. spectrum of NiCo2O4 nanostructures prepared with 5 mL of radish white peel extract. The presence presence of of green in the The green organic organic recuing, recuing, capping, capping, and and stabilizing stabilizing agents agents in the radish radish The presence of green organic recuing, capping, and stabilizing agents in the radish white peel extract have the capability to tailor the surface properties of nanostructured white peel extract have the capability to tailor the surface properties of nanostructured white peel[28,42]. extractUsing have XPS the capability to were tailorable the surface properties of nanostructured materials analysis, we to determine the chemical states and materials [28,42]. Using XPS analysis, we were able to determine the chemical states and surface species ofUsing NiCo2XPS O4 nanostructures both in to thedetermine absence and presence states of radish materials [28,42]. analysis, we were able the chemical and surface species of NiCo2O4 nanostructures both in the absence and presence of radish white peel extract, as shown in Figure 4. The XPSinstudy has demonstrated a significant surface species of NiCo 2O4 nanostructures both the absence and presence of radish white peel extract, as shown in Figure 4. The XPS study has demonstrated a significant role of peel a wide range greenin organic capping, anddemonstrated stabilizing agents on the white extract, asofshown Figurereducing, 4. The XPS study has a significant Biosensors 2023, 13, x FOR PEER REVIEW 8 of 21 Biosensors 2023, 13, 780 8 of 21 role of a wide range of green organic reducing, capping, and stabilizing agents on the surface chemical composition of NiCo2O4 nanostructures. To fit the XPS binding energies surface chemical composition of NiCo2 O4 nanostructures. To fit the XPS binding energies of each each element, element, aa standard standard carbon carbonbinding bindingenergy energywas wasused. used. Using Usingpristine pristineNiCo NiCo2O O4 of 2 4 nanostructures as an example, Figure 4a illustrates the Co 2p spectrum, which indicates nanostructures as an example, Figure 4a illustrates the Co 2p spectrum, which indicates that there CoCo chemical states. According to Figure 5a, the peaks that there are aretwo twotypes typesofof chemical states. According to Figure 5a,estimated the estimated 3+ and 3+ 2+, respecat 779.47 eV and 780.54 eV correspond to the oxidation states of Co Co peaks at 779.47 eV and 780.54 eV correspond to the oxidation states of Co and Co2+ , tively. It is illustrated in Figure 5b how thethe Ni Ni 2p2p spectrum respectively. It is illustrated in Figure 5b how spectrumcan canbebefitted fittedusing using Voigt’s Voigt’s method. The fitted data consist of two spin orbital doublet peaks, 853.88 eV and 855.60 method. The fitted data consist of two spin orbital doublet peaks, 853.88 eV and 855.60 eV, 2+ and 3+ chemical states. It should be noted that despite 2+ 3+ eV, corresponding to the Ni Ni corresponding to the Ni and Ni chemical states. It should be noted that despite these these limitations, the shakeup peaks have been identified, and of the of Nito2p fitted to limitations, the shakeup peaks have been identified, and the data Nidata 2p fitted XPS agree XPS agree reasonably well with the reported peaks [36,44]. Furthermore, Figure 4c disreasonably well with the reported peaks [36,44]. Furthermore, Figure 4c displays the O 1s plays the for O 1s spectrum for pristine NiCo2O4 nanostructures in addition to the metallic spectrum pristine NiCo 2 O4 nanostructures in addition to the metallic chemical states. chemical states. The material surface shows threeeV, peaks at 529.69 eV,532.68 531.10eV, eV, and 532.68 The material surface shows three peaks at 529.69 531.10 eV, and respectively, eV, respectively, correspondingchemical to metal–oxygen chemical oxygen ions, and corresponding to metal–oxygen bonds, oxygen ions, bonds, and physic/chemisorbed physic/chemisorbed water. Previous studies different [36,44] have detectedspecies different water. Previous studies [36,44] have detected oxygenated on oxygenated the surface − 1 species on the surface of pristine NiCo 2 O 4 nanostructures. The spectrum of O−1 s531.10 at 529.69 of pristine NiCo2 O4 nanostructures. The spectrum of O s at 529.69 eV and eV 2 − 2− eV and 531.10 eV was correlated withpresent the O on species on NiCo2O4 nanostructures. was correlated with the O species NiCopresent A similar XPS 2 O4 nanostructures. A similarwas XPSconducted analysis was on NiCo2O4 nanostructures prepared in the analysis on conducted NiCo2 O4 nanostructures prepared in the presence of 5presmL ence of 5 white mL of peel radish whiteaspeel extract as shown in A Figure large peak was obof radish extract shown in Figure 4d–f. large4d–f. peakAwas observed in the 3+ and 3+ and Co , at served in of theCo spectrum of Cowith 2p associated oxidation states, such as, Co spectrum 2p associated oxidation with states, such as Co Co2+ at 779.57 eV 2+and 781.12V, respectively. Byrespectively. contrast, Ni2+ Ni3+ were at 853.96 eV and 779.57 eV and 781.12V, Byand contrast, Ni2+ observed and Ni3+ were observed at 855.61 853.96 eV, eV respectively. Furthermore, three contributions were observed in the O1s spectrum at and 855.61 eV, respectively. Furthermore, three contributions were observed in the O1s 529.67 eV, 531.16 eV, and to the metal–oxygen oxygen ions spectrum at 529.67 eV, 533.42 531.16 eV, eV,corresponding and 533.42 eV, corresponding tobonds, the metal–oxygen (O physic/chemisorbed water on the surfacewater of theonmaterial. Theof XPS has bonds, oxygen ions (O2), and physic/chemisorbed the surface thestudy material. 2 ), and revealed green organic reducing, and stabilizing agents radish agents white The XPS that study has revealed that greencapping, organic reducing, capping, andfrom stabilizing peel a relatively high concentration oxygen ions (O− ) and Co3+ compared fromextract radishhave white peel extract have a relativelyofhigh concentration of oxygen ions (O−) 3+ to pristine NiCo O nanostructures. These surface properties are highly desirable a and Co compared are 2 4 to pristine NiCo2O4 nanostructures. These surface propertiesfor catalytic reaction [36,44]. Furthermore, the green organic reducing, capping, and stabilizing highly desirable for a catalytic reaction [36,44]. Furthermore, the green organic reducing, 3+ agents have a high abundance of Co3+ /Co2+ and Ni2+ /Ni positively capping, andinduced stabilizing agents have induced a high abundance of Co3+metallic /Co2+ and Ni2+/Ni3+ charged in the charged surface of NiCo O4 surface nanostructures. Consequently, theseConsequently, metallic ions metallic ions positively ions in 2the of NiCo2O 4 nanostructures. have highhave density of catalytic sites forof the favorable electrocatalytic reaction of theseoffered metallica ions offered a high density catalytic sites for the favorable electroUA. catalytic reaction of UA. Figure 4. XPS-resolved Co 2p, Ni 2p, O1s spectra for pristine (a–c) and (d–f) XPS-resolved Co 2p, Ni 2p, O1s of 5 mL of radish peel extract-assisted NiCo2 O4 nanostructures. Biosensors 2023, 13, x FOR PEER REVIEW 9 of 21 Biosensors 2023, 13, 780 9 of 21 Figure 4. XPS-resolved Co 2p, Ni 2p, O1s spectra for pristine (a–c) and (d–f) XPS-resolved Co 2p, Ni 2p, O1s of 5 mL of radish peel extract-assisted NiCo2O4 nanostructures. Figure 5. (a) Cyclic voltammograms at a scan rate of 50 mV/s of MGCE with 5 mL and 10 mL of Figure 5. (a) Cyclic voltammograms at a scan rate of 50 mV/s of MGCE with 5 mL and 10 mL of radish radish white peel extract-assisted NiCo2O4 and pristine NiCo2O4-modified GCE in the presence of white peel extract-assisted NiCo2 O4 and pristine NiCo2 O4 -modified GCE in the presence of 0.5 mM of 0.5 mM of UA in 0.1 M PBS pH 7.0. (b) Cyclic voltammograms at 50 mV/s of bare GCE and modified UA in5 0.1 pH 7.0. (b)2Cyclic voltammograms at 50inmV/s of bare GCE and modified with mL with mLMofPBS assisted NiCo O4 in electrolyte and equal the presence of 0.5 mM UA in 0.1 M5PBS of assisted NiCo O in electrolyte and equal in the presence of 0.5 mM UA in 0.1 M PBS pH 7.0. 2 4 pH 7.0. 3.2. Non-Enzymatic Uric Acid (UA) Oxidation on the Surface-Modified NiCo2 O4 Nanostructures with Radish White Peel Extract NiCo2 O4 nanostructures were characterized electrochemically using a three-electrode cell configuration in order to detect UA. Figure 5a illustrates preliminary studies conducted with cyclic voltammetry to identify the most efficient NiCo2 O4 nanostructures for the oxidation of UA. A CV curve was measured at 50 mV/s using both pristine NiCo2 O4 nanostructures and NiCo2 O4 nanostructures, which had been surface-modified with 5 mL and 10 mL of radish white peel extract in the absence or presence of UA. A CV curve, such as that shown in Figure 6a, is representative of electrochemical catalytic signals obtained from pristine and surface-modified NiCo2 O4 nanostructures placed in 0.5 mM UA in a phosphate buffer solution at pH 7.0. When comparing NiCo2 O4 nanostructures prepared with 5 mL of radish white peel extract with pristine and surface-modified NiCo2 O4 nanostructures soaked in 10 mL of radish white peel extract, it is evident that the electrocatalytic properties of these nanostructures are well described when compared to pristine and surface-modified NiCo2 O4 nanostructures soaked in 10 mL of radish white peel extract. This is due to the enhanced conductivity of the material and the enriched surface sites on the surface. Due to the poor catalytic properties and the electrical conductivity of NiCo2 O4 , the CV curve shows that the peak current is relatively low when UA is oxidized on pristine NiCo2 O4 nanostructures. However, the electrochemical performance of NiCo2 O4 nanostructures was strongly dependent on the volume of radish white peel extract, as evidenced by the limited electrochemical signal in Figure 5a for a sample containing 10 mL of radish white peel extract. For the large-scale synthesis of NiCo2 O4 nanostructures that are highly desirable for electrochemical applications, 5mL of radish white peel extract appears to provide the best conditions. Moreover, NiCo2 O4 nanostructures prepared using 5 mL of radish white peel extract and bare glassy carbon electrodes were tested in the presence of 0.5 mM UA and only in the presence of a phosphate buffer solution at pH 7.0, as shown in Figure 6b. UA is believed to cause the signal to originate primarily from NiCo2 O4 nanostructures; however, the bare glassy carbon electrode, as shown in Figure 5b, did not demonstrate any electrochemical signal for either the electrolyte or analyte. Based on the CV analysis, NiCo2 O4 nanostructures synthesized with radish white peel extract were only effective for driving UA oxidation in the phosphate buffer solution, thus full non-enzymatic UA sensor characterization was carried out. Biosensors 2023, 13, 780 tested in the presence of 0.5 mM UA and only in the presence of a phosphate buffer solution at pH 7.0, as shown in Figure 6b. UA is believed to cause the signal to originate primarily from NiCo2O4 nanostructures; however, the bare glassy carbon electrode, as shown in Figure 5b, did not demonstrate any electrochemical signal for either the electrolyte or analyte. Based on the CV analysis, NiCo2O4 nanostructures synthesized with radish 10 white of 21 peel extract were only effective for driving UA oxidation in the phosphate buffer solution, thus full non-enzymatic UA sensor characterization was carried out. Figure 6. (a) Cyclic voltammograms at a scan rate of 50 mV/s of MGCE with 5 mL of radish white Figure 6. (a) Cyclic voltammograms at a scan rate of 50 mV/s of MGCE with 5 mL of radish white peel extract-assisted NiCo2O4-modified GCE in the presence of 0.5 mM of UA in 0.1 M PBS pH 7.0. peel extract-assisted NiCo2 O4 -modified GCE in the presence of 0.5 mM of UA in 0.1 M PBS pH 7.0. (b) Linear plot of peak current against square root of scan rate. (b) Linear plot of peak current against square root of scan rate. When UA is oxidized on NiCo2 O4 nanostructures, electrons are transferred from UA to Co3+ and Ni3+ ions and reduced to Co2+ and Ni2+ . In addition to altering the size and surface properties of NiCo2 O4 nanostructures, phytochemicals in radish white peel extract enhanced the charge transfer between the electrode and analyte solution. Figure 6a shows the electrode kinetics at various scan rates using CV analysis in a solution containing 0.5 mM UA. It is evident from this example that increasing scan rates linearly increase peak current. This confirms the diffusion-controlled processing of the modified GCE with NiCo2 O4 . As shown in Figure 6b, a linear plot was obtained by plotting the peak current against the square root of the scan rate. The purpose of this was to simplify the understanding of electrode kinetics. NiCo2 O4 nanostructure-based electrodes have been found to have a high scan rate in recent studies. According to CV analysis, UA oxidation is accompanied by two electron and proton transfers [44–47]. Also, the observed regression coefficient value (R2 —0.99) supports the analytical aspects of an enzyme-free UA sensor for precise and accurate quantification of UA. Therefore, surface adsorption and electrochemistry were responsible for controlling the UA oxidation reaction. Our study examined the effect of pH on the oxidation process of NiCo2 O4 nanostructures prepared with 5 mL of radish white peel extract. As a result of the pH change of 0.5 mM of UA, CV curves for NiCo2 O4 nanostructures are illustrated in Figure 7a. We evaluated UA sensor performance at pH 7.0 based on the shape and current of the peak, which were more apparent at this pH level. A pH study indicated that NiCo2 O4 nanostructures are strongly regulated by the pH of the analyte solution when it comes to their activity. Such aspects have previously been examined in a study [48]. NiCo2 O4 nanostructures are limited in their ability to function under different pH conditions of analyte solutions. Consequently, the catalytic sites are diminishing, the material is unstable, and the surfaces are etched [49]. As a result of this experiment, the pH of the UA solution was varied between 6.0, 7.0, 8.0, and 9.0. As a result, CV displayed a stable response at pH 7.0, and all electrochemical measurements were made at this pH level. To facilitate interpretation of CV curves, a line plot was also made of the effect of pH on the UA solution. Figure 7b illustrates that pH 7.0 resulted in the highest peak current, which improved charge transfer and increased the NiCo2 O4 nanostructures’ electrochemical activity. UA oxidation occurs when two protons are lost and is suppressed by UA’s low pH of 7.0. However, at higher pH levels, NiCo2 O4 nanostructures are likely to be etched, resulting in poor performance. Biosensors 2023, 13, 780 6.0, 7.0, 8.0, and 9.0. As a result, CV displayed a stable response at pH 7.0, and all electrochemical measurements were made at this pH level. To facilitate interpretation of CV curves, a line plot was also made of the effect of pH on the UA solution. Figure 7b illustrates that pH 7.0 resulted in the highest peak current, which improved charge transfer and increased the NiCo2O4 nanostructures’ electrochemical activity. UA oxidation occurs 11 of 21 when two protons are lost and is suppressed by UA’s low pH of 7.0. However, at higher pH levels, NiCo2O4 nanostructures are likely to be etched, resulting in poor performance. Figure 7. (a) Cyclic voltammograms at a scan rate of 50 mV/s of MGCE with 5 mL of radish white Figure 7. (a) Cyclic voltammograms at a scan rate of 50 mV/s of MGCE with 5 mL of radish white peel extract-assisted NiCo2O4-modified GCE in the presence of different pH values of 0.5 mM of UA peel extract-assisted NiCo2 O4 -modified GCE in the presence of different pH values of 0.5 mM of UA in 0.1 M PBS. (b) Linear plot of peak current versus different pH values of 0.5 mM of UA in 0.1 M in 0.1 M PBS. (b) Linear plot of peak current versus different pH values of 0.5 mM of UA in 0.1 M PBS. PBS. 3.3. The Calibration Plots, Stability, Repeatability, and Selectivity Studies of a Newly Developed Non-Enzymatic UA Sensor Based on Surface-Modified NiCo2 O4 Nanostructures Analyses of the linear range and limit of detection of UA were conducted using NiCo2 O4 nanostructures prepared with 5 mL of radish white peel extract. The linear range of a non-enzymatic UA sensor was evaluated by varying electrochemical modes in order to maintain the sensing range of each electrochemical mode. The linear range of UA was first investigated by CV at 50 mV/s in a phosphate buffer solution at pH 7.0 at different concentrations of UA. The linear range of UA was determined to be between 0.1 mM and 8 mM, and the peak current for UA oxidation increased linearly with increasing UA concentration, as shown in Figure 8a. Based on this study, it can be concluded that UA non-enzymatic sensors have demonstrated a wide linear range to date [13,50–56] as well as the low detection limit of 0.005 mM, indicating a high degree of applicability for the monitoring of UA at either low or high concentrations in real samples. In addition, the linear plot shown in Figure 8b was calculated by selecting the oxidation peak current for each UA concentration against the UA concentration in order to determine the accuracy and precision of a newly developed non-enzymatic UA sensor. It appears that UA sensors have the ability to monitor a wide range of UA concentrations from practical samples based on the linear plot of the CV results. On the basis of the methods reported in the literature, a limit of detection (LOD) and a limit of quantification (LOQ) were estimated [56]. In this study, the LOD and LOQ were determined to be 0.005 mM and 0.008 mM, respectively. Table 1 compares the wide linear range of UA detection and the low LOD of the nonenzymatic UA sensors presented with the existing UA biosensors. Following the analysis of the comparisons, it became evident that the proposed method can be of great interest as an alternative method for the detection of UA in real samples, where a wide linear range and a low limit of detection are desired. Additionally, linear sweep voltammetry (LSV) mode was used to estimate the calibration of the newly developed non-enzymatic UA sensor, and Figure 9a illustrates the range of UA detection obtained. Figure 9a illustrates that the proposed UA sensor configuration is capable of detecting UA over a wide linear range from 0.1 mM to 7.0 mM and producing a significant amount of current. When UA concentration increases in LSV measurements, there is a higher current generated, which indicates that the newly developed UA sensor is highly sensitive. Besides the LSV measurements, we also made a linear plot of peak current and UA concentrations (Figure 9b). The linear fitting of LSV curves reveals that the proposed non-enzymatic UA sensor has excellent Biosensors 2023, 13, 780 12 of 21 analytical performance, as indicated by its regression coefficient value of 0.99. Based on full CV curves and half CV curves from LSV, the present UA sensor is capable of detecting a wide linear range of UA with precision and accuracy. Additionally, the linear range for another highly sensitive electrochemical mode of amperometry at 0.3 V was used to determine the linear range of the UA sensor. Figure 10a illustrates this range for various UA concentrations detected. UA concentrations between 0.1 and 6 mM were highly sensitive Biosensors 2023, 13, x FOR PEER REVIEW of 21 to the amperometric signal. Figure 10b illustrates a linear plot of the amperometric13signal for these different concentrations of UA. Figure 8. (a) Cyclic voltammograms at a scan rate of 50 mV/s of MGCE with 5 mL of radish white Figure 8. (a) Cyclic voltammograms at a scan rate of 50 mV/s of MGCE with 5 mL of radish white peel extract-assisted NiCo2O4 in the presence of various concentrations of UA in 0.1 M PBS pH 7.0. peel extract-assisted NiCo2 O4 in the presence of various concentrations of UA in 0.1 M PBS pH 7.0. (b) Linear plot of peak current versus successive increase in UA concentrations. (b) Linear plot of peak current versus successive increase in UA concentrations. Table 1. Performance comparison of the enzyme-free sensor based on NiCo2O4 nanostructures Table 1.with Performance comparison ofsativus) the enzyme-free sensorseveral based on NiCo2 O4 nanostructures grown 5 mL radish (Raphanus extract versus non-enzymatic UA sensors grown in the with 5 mL radish (Raphanus sativus) extract versus several non-enzymatic UA sensors in the literature. literature. SensingElectrode Electrode Material Material Sensing PCN PCN aa/MWCNT /MWCNT b c B-MWCNTS B-MWCNTS c d Pd/RGO Pd/RGO d Au/RGO dd Au/RGO PtNi@MoS2 e PtNi@MoS2 e Cysteic acid Cysteic Co3Oacid 4 O4 Fe2Co O33@Au NiCo2O4 (30%)/Nano-ZSM-5 Fe2 O3 @Au AuNPs@GO/PPy/CFP NiCo2 O4 (30%)/Nano-ZSM-5 MWNTs/MGF AuNPs@GO/PPy/CFP NiCo2O4 NPs Linear LinearRange Range (ụM) (ụM) 0.2–20 0.2–20 62–250 62–250 6–469.5 6–469.5 8.8–53 8.8–53 0.5–600 0.5–600 1.0–19 1.0–19 500–3500 500–3500 100–10,000 0.9–1000 100–10,000 2–360 0.9–1000 300–1000 2–360 100–8000 Detection Detection of of Limit Limit (ụM) (ụM) 0.139 0.139 0.65 0.65 1.6 1.6 1.8 1.8 0.1 0.1 0.36 0.36 100 100 0.087 0.7 0.087 1.68 0.7 0.93 1.68 0.005 References References [50] [50] [51] [51] [18] [18] [52] [52] [53] [53] [54] [54] [56] [56] [57] [58] [57] [59] [58] [60] [59] This work MWNTs/MGF 300–1000 0.93 [60] Porous g-C3N4. b Multi-walled carbon nanotubes. c Boron-dopped multi-walled carbon naotubes. d NiCo2 O4oxide, NPs e PtNi bimetallic 100–8000 This work Reduced graphene nanoparticles-loaded 0.005 nanosheets, Gold nanorod-decoa Porous g-C N . b Multi-walled carbon nanotubes. c Boron-dopped multi-walled carbon naotubes. d Reduced rated graphene oxide glassy carbon electrode 3 4 a graphene oxide, e PtNi bimetallic nanoparticles-loaded nanosheets, Gold nanorod-decorated graphene oxide glassy carbon electrode Biosensors 2023, 13, 780 x FOR PEER REVIEW 21 1413ofof 21 Biosensors 2023, 13, x FOR PEER REVIEW 14 of 21 Figure 9. (a) Linear sweep voltammetry at a scan rate of 10 mV/s of MGCE with 5 mL of radish Figure 9. (a) Linear sweep voltammetry at a scan rate of 10 mV/s of MGCE with 5 mL of radish white extract-assisted 2O4 in the of various concentrations of UA in 0.1 PBS Figurepeel 9. (a) Linear sweep NiCo voltammetry atpresence a scan rate of 10 mV/s of MGCE with 5 mL of M radish white peel extract-assisted NiCo2 O4 in the presence of various concentrations of UA in 0.1 M PBS pH pH 7.0. (b) Linear plot of peak current versus successive increase in UA concentrations. white peel extract-assisted NiCo2O4 in the presence of various concentrations of UA in 0.1 M PBS 7.0. (b) Linear plot of peak current versus successive increase in UA concentrations. pH 7.0. (b) Linear plot of peak current versus successive increase in UA concentrations. Figure 10. (a) Chronoamperometric response curves measured at an applied potential of 0.3 V of MGCE mL of radish white peel extract-assisted NiCo2O4 at in an theapplied presencepotential of various concenFigure with 10. (a)5 Chronoamperometric response curves measured of 0.3 V of Figure 10. (a) Chronoamperometric response curves measured at an applied potential of 0.3 V trations of UA in 0.1 PBS pH 7.0.peel (b) Linear plot of peak current successive increaseconcenin UA MGCE with 5 mL ofM radish white extract-assisted NiCo 2O4 inversus the presence of various of MGCE with 5 mL of radish white peel extract-assisted NiCo2 O4 in the presence of various concentrations. trations of UA in 0.1 M PBS pH 7.0. (b) Linear plot of peak current versus successive increase in UA concentrations of UA in 0.1 M PBS pH 7.0. (b) Linear plot of peak current versus successive increase concentrations. in UAAconcentrations. linear fitting of the UA detection resulted in excellent performance with strong A linear fittingThe of results the UAconfirm detection in excellent performance strong analytical features. theresulted algorithm’s promising performancewith for the deA linear fitting of the UA detection resulted in excellent performance with strong analytical features. results confirm the algorithm’s performance fordensity the detection of UAs and The its application in real-world samplepromising analysis. Due to the high analytical features. The results confirm the algorithm’s promising performance for the tection of UAs andenhanced its application in real-world sampleand analysis. Due to compatibility the high density of catalytic sites, electrical conductivity, biomimetic of detection of UAs and its application in real-world sample analysis. Due to the high of catalytic sites, enhanced electrical conductivity, and biomimetic compatibility of nanostructured material with the surface of GCE, UA detection on surface-modified density of catalytic sites, enhanced electrical conductivity, and biomimetic compatibility nanostructured material with withradish the surface GCE, UApresented detection outstanding on surface-modified NiCo 2O4 nanostructures white of peel extract linearity of nanostructured material with the surface of GCE, UA detection on surface-modified NiCo 2O4 nanostructures with radish white peel extract presented outstanding linearity and high sensitivity. The SEM, XRD, HRTEM, and XPS measurements demonstrated taiNiCo2 O4 nanostructures with radish white peel extract presented outstanding linearity and and high sensitivity. The SEM, XRD, HRTEM, and XPS measurements demonstrated tailored morphology, excellent crystal quality, a significant amount of surface vacancies, and high sensitivity. The SEM, XRD, HRTEM, and XPS measurements demonstrated tailored lored morphology, excellent crystal quality, a significant amount of surface vacancies, and an abundance of Co(III) and Ni(II) chemical states, which led to the superior performance morphology, excellent crystal quality, a significant amount of surface vacancies, and an an abundance Co(III) and Ni(II) chemical which led tothe the superior performance of NiCo 2O4 nanostructures prepared with states, 5states, mL of radish white peel extract.performance In order to abundance of of Co(III) and Ni(II) chemical which led to superior of NiCo 2O 4 nanostructures prepared with 5 mL of radish white peel extract. order evaluate the selectivity of a UA sensor before implementing it in actual sample of NiCo2 O4 nanostructures prepared with 5 mL of radish white peel extract. In Inanalysis, order to to evaluate a UA sensor before implementing in actual sample we testedthe theselectivity proposed of UA sensor in the presence of possibleit interfering speciesanalysis, during we tested the proposed UA sensor in the presence of possible interfering species during Biosensors 2023, 13, 780 14 of 21 Biosensors 2023, 13, x FOR PEER REVIEW 15 of 21 evaluate the selectivity of a UA sensor before implementing it in actual sample analysis, we tested the proposed UA sensor in the presence of possible interfering species during detection of of UA UAin inreal realblood bloodand andurine urinesamples. samples.It It was determined that selectivity detection was determined that thethe selectivity of of the interfering compoundscould couldbebemonitored monitoredby by preparing preparing NiCo22O44 nanostructures the interfering compounds with radish white peel extract extract containing containing glucose, glucose, ascorbic ascorbic acid, acid, urea, urea, lactic lactic acid, acid,mannose, mannose, sodium ions, chloride ions, potassium ions, and calcium calcium ions, as shown in Figure 11. CV ofof interfering species to atosolution curves were were measured measuredfollowing followingthe thesequential sequentialaddition addition interfering species a soluof 0.5ofmM UA. UA. Based on Figure 11a,11a, the interfering species hadhad the the same concentration tion 0.5 mM Based on Figure the interfering species same concentraas the As aAs result of the sequential addition of interfering species in the presence of tion asUA. the UA. a result of the sequential addition of interfering species in the presence UA, UA was not affected in terms of oxidation peak position, drift in oxidation potential, of UA, UA was not affected in terms of oxidation peak position, drift in oxidation potenand and peak current, suggesting that thethe proposed tial, peak current, suggesting that proposedUA UAsensor sensorconfiguration configuration has has excellent excellent selectivity and is suitable for the detection of UA in biological matrixes. In order to better better selectivity and is suitable for the detection of UA in biological matrixes. In order to visualize the variation in UA peak current after the addition of interfering species, bar visualize the variation in UA peak current after the addition of interfering species, aa bar graph of of the the peak peak current current was was plotted. The change change in in peak peak current current could could be be seen seen at at less less graph plotted. The than 4%, as shown in Figure 11b. The excellent selectivity of the proposed UA sensor can than 4%, as shown in Figure 11b. The excellent selectivity of the proposed UA sensor can be attributed to the surface modification of NiCo O nanostructures with phytochemicals 2 4 be attributed to the surface modification of NiCo2O4 nanostructures with phytochemicals from radish radish white white peel peel extract, extract, which which enabled enabled it it to to detect detect specific specific electroactive electroactive molecules. molecules. from Figure 11. (a) Cyclic voltammograms at a scan rate of 50 mV/s of MGCE with 5 mL of radish white Figure 11. (a) Cyclic voltammograms at a scan rate of 50 mV/s of MGCE with 5 mL of radish white peel extract-assisted NiCo2O4 in the presence of 0.5 mM UA and other competing interfering agents peel extract-assisted NiCo2 O4 in the presence of 0.5 mM UA and other competing interfering agents in in 0.1 M PBS pH 7.0; (b) bar graph of peak current with addition of interfering species for the illus0.1 M PBS pHvariation 7.0; (b) bar of peak current with addition of interfering species for the illustration tration of the ofgraph the peak current. of the variation of the peak current. We examined the repeatability of the modified UA sensor electrode by measuring 20 We examined the repeatability of the modified UA sensor electrode by measuring CV cycles at a scan rate of 50 mV/s in 0.5 mM. It was found that the device could be reused, 20 CV cycles at a scan rate of 50 mV/s in 0.5 mM. It was found that the device could as shown in Figure 12a. The long-term stability of UA biosensors is always a challenge, be reused, as shown in Figure 12a. The long-term stability of UA biosensors is always a especially for enzymatic biosensors, thus we have designed a non-enzymatic UA sensor challenge, especially for enzymatic biosensors, thus we have designed a non-enzymatic with potential application in real analysis. This is evident from the bar graph of peak curUA sensor with potential application in real analysis. This is evident from the bar graph of rent after several repeatable CV cycles as shown in Figure 12b. An error of less than 5% peak current after several repeatable CV cycles as shown in Figure 12b. An error of less indicates the excellent analytical features of the method. A non-enzymatic UA based on than 5% indicates the excellent analytical features of the method. A non-enzymatic UA surface-modified NiCo2O4 NiCo nanostructures can be used for long-term applications, since based on surface-modified 2 O4 nanostructures can be used for long-term applications, the material does not change surface features under ambient since the material does not change surface features under ambientconditions. conditions.However, However, we we examined the stability of NiCo 2O4 nanostructures in 0.5 mM UA solution by measuring examined the stability of NiCo2 O4 nanostructures in 0.5 mM UA solution by measuring the the amperometric response a period of 1000 s. This is depicted in Figure 13a. Accordamperometric response overover a period of 1000 s. This is depicted in Figure 13a. According ing to the response time, present sensor exhibit current fluctuation for to the response time, the the present UA UA sensor did did not not exhibit anyany current fluctuation for the the selected time. Therefore, it is suitable for long-term applications. selected time. Therefore, it is suitable for long-term applications. Biosensors Biosensors 2023, 2023, 13, 13, 780 x FOR PEER REVIEW of 21 21 1615of Biosensors 2023, 13, x FOR PEER REVIEW 16 of 21 Figure 12. (a) Cyclic voltammograms at a scan rate of 50 mV/s of MGCE with 5 mL of radish white Figure 12. (a) Cyclic voltammograms at a scan rate of 50 mV/s of MGCE with 5 mL of radish white peel extract-assisted 2O4 in the presence 0.5 of mM inof0.1MGCE M PBSwith pH 57.0; graph of Figure 12. (a) Cyclic NiCo voltammograms at a scanofrate 50 UA mV/s mL(b) of bar radish white peel extract-assisted NiCo2 O4 in the presence of 0.5 mM UA in 0.1 M PBS pH 7.0; (b) bar graph of peak current for the description change in the current with CV cycles. peel extract-assisted NiCo2O4 inofthe presence of peak 0.5 mM UA in 0.1increasing M PBS pHnumber 7.0; (b) of bar graph of peak current thecurrent description of successive change in the peak current with increasing number of CV cycles. Linear plot offor peak versus increase in UA concentrations. peak current for the description of change in the peak current with increasing number of CV cycles. Linear Linear plot plot of of peak peak current current versus versus successive successive increase increase in in UA UA concentrations. concentrations. Figure 13. (a) Chronoamperometric response of MGCE with 5 mL of radish white peel extract-assisted 2O4Chronoamperometric in 0.5 mM preparedresponse in 0.1 M of PBS pH 7.0 for of stability of modiFigureNiCo 13. (a) (a) response of MGCE with 5 demonstration mL of radish white peel extract-asFigure 13. Chronoamperometric MGCE with 5the mL of radish white peel extract-assisted fied electrode; EIS Nyquist plots collected for the MGCE with pristine, 5 mL, and 10 mL of sisted NiCo 2O4(b) in 0.5 mM prepared in 0.1 M PBS pH 7.0 for the demonstration of stability ofradish modiNiCo2 O4 in 0.5 mM prepared in 0.1 M PBS pH 7.0 for the demonstration of stability of modified 2O4 collected in 0.5 mM frequency range5 of 100 kHz Hz, amwhite peel extract-assisted NiCo fied electrode; (b) EIS Nyquist plots forUA theusing MGCE with pristine, mL, and 10 to mL1 of radish electrode; (b) EIS Nyquist plots collected for the MGCE with pristine, 5 mL, and 10 mL of radish white plitude of 10 mV, and biasing potential of 0.6 V.UA using frequency range of 100 kHz to 1 Hz, am2O4 in 0.5 mM white peel extract-assisted NiCo peel extract-assisted NiCo2 O4 in 0.5 mM UA using frequency range of 100 kHz to 1 Hz, amplitude of plitude of 10 mV, and biasing potential of 0.6 V. 10 mV, andresults biasingin potential ofwide 0.6 V. linear range, low limit of detection, excellent selectivity, Our terms of Our and results in terms of confirmed wide linearthe range, low limit of detection, excellent stability, repeatability superior performance compared toselectivity, other UA Our results in terms of wide linear range, low limit of detection, excellent selectivity, sensors/biosensors reported in the existing literature, as shown in Table 1. To support the stability, and repeatability confirmed the superior performance compared to other UA stability, and repeatability confirmed the superior performance compared to other UA sensors/biosensors reported existing literature, as4as shown in Table 1.electrochemical To the electrochemical performance ofthe the prepared NiCo2O nanostructures, sensors/biosensors reportedinin the existing literature, shown in Table 1. support To support electrochemical performance of the prepared NiCo 2a O 4 nanostructures, electrochemical impedance spectroscopy (EIS) was performed using sweeping frequency range of 100 the electrochemical performance of the prepared NiCo2 O4 nanostructures, electrochemical kHz to 1 Hz, amplitude of 10 was mV and biasingusing potential of 0.6 V. The Nyquist plots impedance spectroscopy (EIS) was performed using a sweeping frequency range ofwere 100 impedance spectroscopy (EIS) performed a sweeping frequency range of 100 kHz kHz to 1 Hz, amplitude of 10 mV and biasing potential of 0.6 V. The Nyquist plots were measured for the three samples of NiCo 2O4 nanostructures, including pristine sample 1 to 1 Hz, amplitude of 10 mV and biasing potential of 0.6 V. The Nyquist plots were measured and sample 2 in 0.5mM UA, and the EIS were fitted with Z-view software as illusmeasured for the three samples of NiCo 2data O 4 nanostructures, including pristine sample for the three samples of NiCo2 O4 nanostructures, including pristine sample 1 and sample 21 and 2 in 0.5mM and the EIS data were fitted withas Z-view as illustrated in Figure 13b. intercept of thewith semicircle ofsoftware Nyquist plots atsoftware high frequency in 0.5sample mM UA, and theThe EISUA, data were fitted Z-view illustrated in Figure 13b. trated in Figure 13b. The intercept of the semicircle of Nyquist plots at high frequency represents electrolyte resistance. The arc of the Nyquist plots indicates the charge The intercept of the semicircle of Nyquist plots at high frequency represents electrolyte transport working electrode NiCo 2O 4 nanostructures and the representsbetween electrolyte Theindicates arc based of the Nyquist plots indicates theworking charge resistance. The arc ofthe theresistance. Nyquist plots the on charge transport between the transport between the working onofNiCo 2O4 nanostructures the 0.5mM analyte solution [61]. Theelectrode estimatedbased values charge-transfer Rct for and pristine 0.5mM analyte solution [61]. The estimated values of charge-transfer Rct for pristine Biosensors 2023, 13, 780 Biosensors 2023, 13, x FOR PEER REVIEW 16 of 21 17 of 21 electrode based on NiCo2 O4 nanostructures and the 0.5 mM analyte solution [61]. The NiCo2O4 nanostructures, sample 1, and sample 2 in the presence of analyte were as 125,100 estimated values of charge-transfer Rct for pristine NiCo2 O4 nanostructures, sample 1, and Ohm, Ohm, and 181,270 Ohm, respectively. EIS study Ohm, has verified that sample sample114,970 2 in the presence of analyte were as 125,100 The Ohm, 114,970 and 181,270 Ohm, nanostructures prepared with 5 mL of radish white peel extract more 1respectively. of NiCo2O4The EIS study has verified that sample 1 of NiCo2 O4 nanostructures has prepared favorable charge transport over the pristine and sample 2-based NiCo 2O4 nanostructures; with 5 mL of radish white peel extract has more favorable charge transport over the pristine hence, we observed measurements of samplebetter 1 toward the quantiand sample 2-based better NiCo2electrochemical O4 nanostructures; hence, we observed electrochemical fication of a sensitive UA 1signal. measurements of sample toward the quantification of a sensitive UA signal. 3.4. Human Blood Sample Analytical Applications of Proposed Non-Enzymatic UA UA Sensor-Based SensorNiCo2NiCo O4 Nanostructures Based 2O4 Nanostructures non-enzymaticUA UAsensor sensor configuration presented in Figure has evalbeen The non-enzymatic configuration presented in Figure 14a,b14a,b has been evaluated onhuman real human samples. A healthy volunteer and a high UA patient uated on real bloodblood samples. A healthy volunteer and a high UA patient provided provided bloodwith samples ownThe consent. The samples were diluted 30 0.1 times blood samples their with own their consent. samples were diluted 30 times with M with 0.1 M phosphate buffer solution of pH 7.0 and used directly during the setup of phosphate buffer solution of pH 7.0 and used directly during the setup of three electrode three electrode cells for electrochemical quantification of UA. UA non-enzymatic sensor cells for electrochemical quantification of UA. UA non-enzymatic sensor performance performance confirms applicability its potential applicability andfor reliability for the quantification ofbioUA confirms its potential and reliability the quantification of UA from from biological fluids, and even food products with high probability, as shown in Table 2. logical fluids, and even food products with high probability, as shown in Table 2. A perA percent relative standard deviation RSD (%)calculated was calculated from theof sum of (standard cent relative standard deviation RSD (%) was from the sum (standard devideviation/mean of quantified UA concentration data using three repeated experiments for ation/mean of quantified UA concentration data using three repeated experiments for UA UA detection) × 100%. detection) × 100%. Figure 14. (a) Cyclic voltammograms at a scan rate of 50 mV/s of MGCE with 5 mL of radish white Figure 14. (a) Cyclic voltammograms at a scan rate of 50 mV/s of MGCE with 5 mL of radish white peel extract assisted NiCo2O4 for the quantitation of UA form diluted human blood real samples in peel extract assisted NiCo2 O4 for the quantitation of UA form diluted human blood real samples 0.1M PBS pH 7.0 and successive addition method; (b) Cyclic voltammograms at a scan rate of 50 in 0.1M pHwith 7.0 and successive method; Cyclic voltammograms at a scan rate of 2O4 for the quantitation of UA mV/s of PBS MGCE 5 mL of radish addition white peel extract (b) assisted NiCo 50 mV/s of MGCE with 5 mL of radish white peel extract assisted NiCo O for the of 2 4 form diluted human urine real samples in 0.1M PBS pH 7.0 and successive addition quantitation method. UA form diluted human urine real samples in 0.1M PBS pH 7.0 and successive addition method. Table 2. Real sample analysis of UA from various blood samples (Blood 1 = healthy blood sample; Blood 2 = high-level UA patient). Sample Blood 1 Blood 2 - Added (mM) 0.5 1 2 2.5 1.5 Found (mM) 0.1 0.612 ± 0.002 1.123 ± 0.0023 2.084 ± 0.0017 2.621 ± 0.0013 1.00 2.533 ± 0.0022 %Recovery 101.66 101.81 99 100.77 101.2 % RSD 0.52 0.53 0.49 0.54 0.48 Biosensors 2023, 13, 780 17 of 21 Table 2. Real sample analysis of UA from various blood samples (Blood 1 = healthy blood sample; Blood 2 = high-level UA patient). Sample Added (mM) Found (mM) %Recovery % RSD Blood 1 - 0.1 - - 0.5 0.612 ± 0.002 101.66 0.52 - 1 1.123 ± 0.0023 101.81 0.53 - 2 2.084 ± 0.0017 99 0.49 - 2.5 2.621 ± 0.0013 100.77 0.54 Blood 2 - 1.00 - - - 1.5 2.533 ± 0.0022 101.2 0.48 - 2 3.082 ± 0.0019 102.66 0.56 - 2.5 3.514 ± 0.0024 100.28 0.50 - 3 4.063 ± 0.0018 101.5 0.53 4. Conclusions An easy and rapid method has been developed for quantifying UA in human blood and urine samples by using surface-modified NiCo2 O4 nanostructures. It has been combined with phytochemicals derived from radish white peel. It was determined that a volume of 5 mL of radish white peel extract was optimal for the large-scale synthesis of NiCo2 O4 nanostructures. The CV exhibited a linear range from 0.1 mM to 8 mM, the LSV showed 0.1 mM to 7 mM, and the amperometric signal for the UA sensor showed a linear range from 0.1 mM to 4 mM. We found that the LOD and LOQ of the present non-enzymatic UA sensor were 0.005 mM and 0.008 mM, respectively. Furthermore, the present UA sensor was evaluated in terms of its selectivity, stability, repeatability, and sensitivity. Consequently, a wide linear range and a low limit of detection were achieved. Several factors contribute to the sensor’s performance, including large surface vacancies, abundant chemical states of Co(III), Ni(II), tailored surface morphology, fast charge-transfer rate, and outstanding crystal quality. It has been demonstrated that there is a satisfactory level of detection of UA in human blood samples (healthy and UA patients). Author Contributions: A.G.S. performed material synthesis and partial electrochemical measurements; A.T. performed XRD analysis and measurement; B.W. performed the real sample analysis; A.S.C. performed the partial electrochemical measurement and analyzed the obtained results; T.P. performed the partial supervisions and preview the obtained results; A.N. performed validation of results and proofread the paper; E.A.D. performed SEM analysis; L.M.A.S. performed EIS study; M.P. performed HRTEM analysis; A.A.K.H.I. performed overall review of the obtained results; K.L. performed XPS and HRTEM measurement; B.V. performed XPS analysis and proofread the structural results; Z.H.I. performed main supervision and wrote the first draft of manuscript. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Institutional Review Board Statement: Not Applicable. Informed Consent Statement: Not Applicable. Data Availability Statement: The authors declare that the data supporting the findings of this study are available within the paper. Acknowledgments: The authors would like to gratefully acknowledge the Higher Education Commission Pakistan for partial support under the project NRPU/8350. We also extend our sincere appreciation to the Researchers Supporting Project Number (RSP2023R79) at King Saud University, Riyadh, Saudi Arabia. Brigitte Vigolo would like to thank the platform “Microscopies, Microprobes and Metallography (3 M)” (Institut Jean Lamour, IJL, Nancy, France) for access to SEM facilities and Biosensors 2023, 13, 780 18 of 21 F. Alnjiman for his valuable help. Authors would also like to acknowledge partial funding of the Ajman University, Grant ID: DRGS ref. 2022-IRG-HBS-5. Conflicts of Interest: The authors declare no conflict of interest. References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. Martinon, F. Mechanisms of uric acid crystal-mediated autoinflammation. Immunol. Rev. 2010, 233, 218–232. [CrossRef] [PubMed] Hu, F.X.; Hu, T.; Chen, S.; Wang, D.; Rao, Q.; Liu, Y.; Dai, F.; Guo, C.; Yang, H.B.; Li, C.M. Single-atom cobalt-based electrochemical biomimetic uric acid sensor with wide linear range and ultralow detection limit. Nano-Micro Lett. 2021, 13, 1–13. [CrossRef] [PubMed] Qu, S.; Li, Z.; Jia, Q. Detection of purine metabolite uric acid with picolinic-acid-functionalized metal–organic frameworks. ACS Appl. Mater. Interfaces 2019, 11, 34196–34202. [CrossRef] Feig, D.I.; Kang, D.-H.; Johnson, R.J. Uric acid and cardiovascular risk. N. Engl. J. Med. 2008, 359, 1811–1821. [CrossRef] Palmer, I.; Schutte, A.; Huisman, H. Uric acid and the cardiovascular profile of African and Caucasian men. J. Hum. Hypertens. 2010, 24, 639–645. Roberts, J.M.; Gammill, H.S. Preeclampsia: Recent insights. Hypertension 2005, 46, 1243–1249. [CrossRef] Dey, N.; Bhattacharya, S. Nanomolar level detection of uric acid in blood serum and pest-infested grain samples by an amphiphilic probe. Anal. Chem. 2017, 89, 10376–10383. [CrossRef] Talaat, K.M.; El-Sheikh, A.R. The effect of mild hyperuricemia on urinary transforming growth factor beta and the progression of chronic kidney disease. Am. J. Nephrol. 2007, 27, 435–440. Chen, X.; Chen, J.; Wang, F.; Xiang, X.; Luo, M.; Ji, X.; He, Z. Determination of glucose and uric acid with bienzyme colorimetry on microfluidic paper-based analysis devices. Biosens. Bioelectron. 2012, 35, 363–368. [CrossRef] [PubMed] Pormsila, W.; Krähenbühl, S.; Hauser, P.C. Capillary electrophoresis with contactless conductivity detection for uric acid determination in biological fluids. Anal. Chim. Acta 2009, 636, 224–228. [CrossRef] [PubMed] Westley, C.; Xu, Y.; Thilaganathan, B.; Carnell, A.J.; Turner, N.J.; Goodacre, R. Absolute quantification of uric acid in human urine using surface enhanced Raman scattering with the standard addition method. Anal. Chem. 2017, 89, 2472–2477. [CrossRef] Rebelo, I.A.; Piedade, J.A.P.; Oliveira-Brett, A.M. Development of an HPLC method with electrochemical detection of femtomoles of 8-oxo-7, 8-dihydroguanine and 8-oxo-7, 8-dihydro-20 -deoxyguanosine in the presence of uric acid. Talanta 2004, 63, 323–331. [CrossRef] [PubMed] Wang, C.; Yuan, R.; Chai, Y.; Chen, S.; Hu, F.; Zhang, M. Simultaneous determination of ascorbic acid, dopamine, uric acid and tryptophan on gold nanoparticles/overoxidized-polyimidazole composite modified glassy carbon electrode. Anal. Chim. Acta 2012, 741, 15–20. [CrossRef] [PubMed] Lian, X.; Yan, B. Phosphonate MOFs composite as off–on fluorescent sensor for detecting purine metabolite uric acid and diagnosing hyperuricuria. Inorg. Chem. 2017, 56, 6802–6808. [CrossRef] [PubMed] Yao, D.; Vlessidis, A.G.; Evmiridis, N.P. Microdialysis sampling and monitoring of uric acid in vivo by a chemiluminescence reaction and an enzyme on immobilized chitosan support membrane. Anal. Chim. Acta 2003, 478, 23–30. [CrossRef] Yang, X.; Kirsch, J.; Simonian, A. Campylobacter spp. detection in the 21st century: A review of the recent achievements in biosensor development. J. Microbiol. Methods 2013, 95, 48–56. [CrossRef] Yang, X.; Kirsch, J.; Olsen, E.V.; Fergus, J.W.; Simonian, A.L. Anti-fouling PEDOT: PSS modification on glassy carbon electrodes for continuous monitoring of tricresyl phosphate. Sens. Actuators B Chem. 2013, 177, 659–667. [CrossRef] Wang, J.; Yang, B.; Zhong, J.; Yan, B.; Zhang, K.; Zhai, C.; Shiraishi, Y.; Du, Y.; Yang, P. Dopamine and uric acid electrochemical sensor based on a glassy carbon electrode modified with cubic Pd and reduced graphene oxide nanocomposite. J. Colloid Interface Sci. 2017, 497, 172–180. [PubMed] Sha, R.; Puttapati, S.K.; Srikanth, V.V.; Badhulika, S. Ultra-sensitive non-enzymatic ethanol sensor based on reduced graphene oxide-zinc oxide composite modified electrode. IEEE Sens. J. 2017, 18, 1844–1848. [CrossRef] Sha, R.; Badhulika, S. Facile green synthesis of reduced graphene oxide/tin oxide composite for highly selective and ultra-sensitive detection of ascorbic acid. J. Electroanal. Chem. 2018, 816, 30–37. [CrossRef] Sha, R.; Komori, K.; Badhulika, S. Graphene–Polyaniline composite based ultra-sensitive electrochemical sensor for non-enzymatic detection of urea. Electrochim. Acta 2017, 233, 44–51. [CrossRef] Ndamanisha, J.C.; Guo, L. Electrochemical determination of uric acid at ordered mesoporous carbon functionalized with ferrocenecarboxylic acid-modified electrode. Biosens. Bioelectron. 2008, 23, 1680–1685. [CrossRef] Wu, L.; Feng, L.; Ren, J.; Qu, X. Electrochemical detection of dopamine using porphyrin-functionalized graphene. Biosens. Bioelectron. 2012, 34, 57–62. [CrossRef] [PubMed] Wu, S.; Wang, T.; Gao, Z.; Xu, H.; Zhou, B.; Wang, C. Selective detection of uric acid in the presence of ascorbic acid at physiological pH by using a β-cyclodextrin modified copolymer of sulfanilic acid and N-acetylaniline. Biosens. Bioelectron. 2008, 23, 1776–1780. [CrossRef] [PubMed] Xiao, C.; Chu, X.; Yang, Y.; Li, X.; Zhang, X.; Chen, J. Hollow nitrogen-doped carbon microspheres pyrolyzed from self-polymerized dopamine and its application in simultaneous electrochemical determination of uric acid, ascorbic acid and dopamine. Biosens. Bioelectron. 2011, 26, 2934–2939. [CrossRef] [PubMed] Biosensors 2023, 13, 780 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. 47. 48. 49. 50. 51. 19 of 21 Özcan, A.; Şahin, Y. Preparation of selective and sensitive electrochemically treated pencil graphite electrodes for the determination of uric acid in urine and blood serum. Biosens. Bioelectron. 2010, 25, 2497–2502. [CrossRef] [PubMed] Wayu, M.B.; Schwarzmann, M.A.; Gillespie, S.D.; Leopold, M.C. Enzyme-free uric acid electrochemical sensors using βcyclodextrin-modified carboxylic acid-functionalized carbon nanotubes. J. Mater. Sci. 2017, 52, 6050–6062. [CrossRef] Solangi, A.G.; Pirzada, T.; Shah, A.A.; Halepoto, I.A.; Chang, A.S.; Solangi, Z.A.; Solangi, M.Y.; Aftab, U.; Tonezzer, M.; Tahira, A. Phytochemicals of mustard (Brassica Campestris) leaves tuned the nickel-cobalt bimetallic oxide properties for enzyme-free sensing of glucose. J. Chin. Chem. Soc. 2022, 69, 1608–1618. [CrossRef] Ding, R.; Qi, L.; Jia, M.; Wang, H. Facile synthesis of mesoporous spinel NiCo2 O4 nanostructures as highly efficient electrocatalysts for urea electro-oxidation. Nanoscale 2014, 6, 1369–1376. [CrossRef] Prathap, M.A.; Satpati, B.; Srivastava, R. Facile preparation of β-Ni(OH)2 -NiCo2 O4 hybrid nanostructure and its application in the electro-catalytic oxidation of methanol. Electrochim. Acta 2014, 130, 368–380. [CrossRef] Qian, L.; Gu, L.; Yang, L.; Yuan, H.; Xiao, D. Direct growth of NiCo2 O4 nanostructures on conductive substrates with enhanced electrocatalytic activity and stability for methanol oxidation. Nanoscale 2013, 5, 7388–7396. [CrossRef] [PubMed] Wu, X.; Han, Z.; Zheng, X.; Yao, S.; Yang, X.; Zhai, T. Core-shell structured Co3 O4 @NiCo2 O4 electrodes grown on flexible carbon fibers with superior electrochemical properties. Nano Energy 2017, 31, 410–417. [CrossRef] Xu, K.; Yang, X.; Yang, J.; Hu, J. Synthesis of hierarchical Co3 O4 @NiCo2 O4 core-shell nanosheets as electrode materials for supercapacitor application. J. Alloys Compd. 2017, 700, 247–251. Zhang, G.; Wang, T.; Yu, X.; Zhang, H.; Duan, H.; Lu, B. Nanoforest of hierarchical Co3 O4 @NiCo2 O4 nanowire arrays for high-performance supercapacitors. Nano Energy 2013, 2, 586–594. [CrossRef] Zhou, Y.; Ma, L.; Gan, M.; Ye, M.; Li, X.; Zhai, Y.; Yan, F.; Cao, F. Monodisperse MnO2 @NiCo2 O4 core/shell nanospheres with highly opened structures as electrode materials for good-performance supercapacitors. Appl. Surf. Sci. 2018, 444, 1–9. Jokar, E.; Zad, A.I.; Shahrokhian, S. Synthesis and characterization of NiCo2 O4 nanorods for preparation of supercapacitor electrodes. J. Solid State Electrochem. 2015, 19, 269–274. Chu, Q.; Yang, B.; Wang, W.; Tong, W.; Wang, X.; Liu, X.; Chen, J. Fabrication of a Stainless-Steel-Mesh-Supported Hierarchical Fe2 O3 @NiCo2 O4 Core-Shell Tubular Array Anode for Lithium-Ion Battery. ChemistrySelect 2016, 1, 5569–5573. Huang, G.; Zhang, L.; Zhang, F.; Wang, L. Metal–organic framework derived Fe2 O3 @NiCo2 O4 porous nanocages as anode materials for Li-ion batteries. Nanoscale 2014, 6, 5509–5515. [CrossRef] He, Q.; Liu, J.; Liu, X.; Li, G.; Chen, D.; Deng, P.; Liang, J. Fabrication of amine-modified magnetite-electrochemically reduced graphene oxide nanocomposite modified glassy carbon electrode for sensitive dopamine determination. Nanomaterials 2018, 8, 194. [CrossRef] Gutiérrez, R.M.P.; Perez, R.L. Raphanus sativus (Radish): Their chemistry and biology. Sci. World J. 2004, 4, 811. [CrossRef] Hanlon, P.R.; Barnes, D.M. Phytochemical composition and biological activity of 8 varieties of radish (Raphanus sativus L.) sprouts and mature taproots. J. Food Sci. 2011, 76, C185–C192. [PubMed] Nawaz, H.; Shad, M.A.; Rauf, A. Optimization of extraction yield and antioxidant properties of Brassica oleracea Convar Capitata Var L. leaf extracts. Food Chem. 2018, 242, 182–187. [CrossRef] Amin, S.; Tahira, A.; Solangi, A.R.; Mazzaro, R.; Ibupoto, Z.H.; Fatima, A.; Vomiero, A. Functional nickel oxide nanostructures for ethanol oxidation in alkaline media. Electroanalysis 2020, 32, 1052–1059. [CrossRef] Ibupoto, Z.H.; Tahira, A.; Shah, A.A.; Aftab, U.; Solangi, M.Y.; Leghari, J.A.; Samoon, A.H.; Bhatti, A.L.; Bhatti, M.A.; Mazzaro, R. NiCo2 O4 nanostructures loaded onto pencil graphite rod: An advanced composite material for oxygen evolution reaction. Int. J. Hydrog. Energy 2022, 47, 6650–6665. [CrossRef] Li, W.; Zhang, B.; Lin, R.; Ho-Kimura, S.; He, G.; Zhou, X.; Hu, J.; Parkin, I.P. A dendritic nickel cobalt sulfide nanostructure for alkaline battery electrodes. Adv. Funct. Mater. 2018, 28, 1705937. [CrossRef] Wang, N.; Hang, T.; Chu, D.; Li, M. Three-dimensional hierarchical nanostructured Cu/Ni–Co coating electrode for hydrogen evolution reaction in alkaline media. Nano-Micro Lett. 2015, 7, 347–352. López-Tinoco, J.; Mendoza-Cruz, R.; Bazán-Díaz, L.; Karuturi, S.C.; Martinelli, M.; Cronauer, D.C.; Kropf, A.J.; Marshall, C.L.; Jacobs, G. The preparation and characterization of Co–Ni nanoparticles and the testing of a heterogenized Co–Ni/alumina catalyst for CO hydrogenation. Catalysts 2019, 10, 18. Lei, Y.; Li, J.; Wang, Y.; Gu, L.; Chang, Y.; Yuan, H.; Xiao, D. Rapid microwave-assisted green synthesis of 3D hierarchical flower-shaped NiCo2 O4 microsphere for high-performance supercapacitor. ACS Appl. Mater. Interfaces 2014, 6, 1773–1780. [CrossRef] Marco, J.; Gancedo, J.; Gracia, M.; Gautier, J.; Ríos, E.; Berry, F. Characterization of the nickel cobaltite, NiCo2O4, prepared by several methods: An XRD, XANES, EXAFS, and XPS study. J. Solid State Chem. 2000, 153, 74–81. [CrossRef] Lv, J.; Li, C.; Feng, S.; Chen, S.-M.; Ding, Y.; Chen, C.; Hao, Q.; Yang, T.-H.; Lei, W. A novel electrochemical sensor for uric acid detection based on PCN/MWCNT. Ionics 2019, 25, 4437–4445. [CrossRef] Tsierkezos, N.G.; Ritter, U.; Thaha, Y.N.; Downing, C.; Szroeder, P.; Scharff, P. Multi-walled carbon nanotubes doped with boron as an electrode material for electrochemical studies on dopamine, uric acid, and ascorbic acid. Microchim. Acta 2016, 183, 35–47. [CrossRef] Biosensors 2023, 13, 780 52. 53. 54. 55. 56. 57. 58. 59. 60. 61. 20 of 21 Wang, C.; Du, J.; Wang, H.; Zou, C.e.; Jiang, F.; Yang, P.; Du, Y. A facile electrochemical sensor based on reduced graphene oxide and Au nanoplates modified glassy carbon electrode for simultaneous detection of ascorbic acid, dopamine and uric acid. Sens. Actuators B Chem. 2014, 204, 302–309. Ma, L.; Zhang, Q.; Wu, C.; Zhang, Y.; Zeng, L. PtNi bimetallic nanoparticles loaded MoS2 nanosheets: Preparation and electrochemical sensing application for the detection of dopamine and uric acid. Anal. Chim. Acta 2019, 1055, 17–25. [PubMed] Hassanvand, Z.; Jalali, F. Simultaneous determination of l-DOPA, l-tyrosine and uric acid by cysteic acid-modified glassy carbon electrode. Mater. Sci. Eng. C 2019, 98, 496–502. [CrossRef] [PubMed] Li, L.; Wang, Y.; Pan, L.; Shi, Y.; Cheng, W.; Shi, Y.; Yu, G. A nanostructured conductive hydrogels-based biosensor platform for human metabolite detection. Nano Lett. 2015, 15, 1146–1151. [CrossRef] Chang, A.S.; Tahira, A.; Chang, F.; Memon, N.N.; Nafady, A.; Kasry, A.; Ibupoto, Z.H. Silky Co3 O4 nanostructures for the selective and sensitive enzyme free sensing of uric acid. RSC Adv. 2021, 11, 5156–5162. [CrossRef] Guan, H.; Peng, B.; Gong, D.; Han, B.; Zhang, N. Electrochemical Enhanced Detection of Uric Acid Based on Peroxidase-like Activity of Fe3 O4 @Au. Electroanalysis 2021, 33, 1736–1745. Balwinder, K.; Biswarup, S.; Rajendra, S. Synthesis of NiCo2 O4 /Nano-ZSM-5 nanocomposite material with enhanced electrochemical properties for the simultaneous determination of ascorbic acid, dopamine, uric acid and tryptophan. New. J. Chem. 2015, 39, 1115–1124. Tan, C.; Zhao, J.; Sun, P.; Zheng, W.; Cui, G. Gold Nanoparticle Decorated Polypyrrole/Graphene Oxide Nanosheets as a Modified Electrode for Simultaneous Determination of Ascorbic Acid, Dopamine and Uric Acid. New. J. Chem. 2020, 12, 4916–4926. [CrossRef] Li, H.; Wang, Y.; Ye, D.; Luo, J.; Su, B.; Zhang, S.; Kong, J. An electrochemical sensor for simultaneous determination of ascorbic acid, dopamine, uric acid and tryptophan based on MWNTs bridged mesocellular graphene foam nanocomposite. Talanta 2014, 127, 255–261. Mobili, R.; Preda, G.; La Cognata, S.; Toma, L.; Pasini, D.; Amendola, V. Chiroptical sensing of perrhenate in aqueous media by a chiral organic cage. Chem. Commun. 2022, 58, 3897–3900. [CrossRef] [PubMed] Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.