A Non–Enzymatic Electrochemical Sensor of Cu@Co–MOF Composite for Glucose Detection with High Sensitivity and Selectivity

Abstract

A 3D cobalt metal–organic framework (Co–MOF), [Co₃(BDC)₃(DMU)₂], was utilized to prepare Cu@Co–MOF composite in a deposition–reduction process. Cu@Co–MOF/GCE (GCE = glassy carbon electrode) electrode was prepared by “drop–coating” method. Cu@Co–MOF/GCE shows excellent electrocatalytic activity for Glu detection. The chronoamperometric response of Cu@Co–MOF/GCE to Glu concentration (C_Glu) displays linear relationships in two C_Glu sections with calculated sensitivities of 282.89 μA mM⁻¹ cm⁻² within 0.005–0.4 mM Glu and 113.15 μA mM⁻¹ cm⁻² within 0.4–1.8 mM Glu. The detection limit is calculated as 1.6 μM at S/N = 3. Cu@Co–MOF/GCE also exhibits a rapid current response, high anti–interference, stability, and repeatability to Glu detection. Cu@Co–MOF/GCE was applied to detect Glu in human serum and orange juice. All found C_Glu are very close to those added C_Glu with low RSDs and high recoveries. Cu@Co–MOF/GCE as a non–enzymatic electrochemical sensor of Glu has high sensitivity, selectivity, accuracy, and reliability.

1. Introduction

As the most important monosaccharide, glucose (Glu) plays a crucial role in bodily functions. Glu provides the main energy source of the body, which hydrolyzes in the body and is stored as glycogen. Glu can protect and detoxify the liver, and also promotes the metabolism of poisons. Glu is the most important and basic substance in medicine. It can be adsorbed fast by human tissues [1]. However, the fluctuation of blood Glu hazards the health. For example, hypoglycemia leads to brain dysfunction, induces cardiovascular diseases of arrhythmia, myocardial infarction and stroke, and causes nervous diseases; hyperglycemia will result in dehydration, metabolic dysfunction, water electrolyte disorder, fatigue, decreased resistance, and especially, diabetes. Diabetes is a major predisposition to other serious illnesses of kidney failure, stroke, and blindness, causing a huge financial burden [2]. Thus, an accurate, low–cost, and easy measurement method for sensing Glu in the human body is greatly needed [3,4]. The measurement methods of Glu mainly include chromatography, spectroscopy, and electrochemistry [5,6]. The electrochemical Glu sensors have the advantages of high reliability, low–cost, and outstanding operability, which attract a lot of interest [7,8]. Electrochemical Glu sensors are divided into enzymatic and non–enzymatic sensors. The enzymatic Glu sensors occupy the main part in the market of Glu sensor industry, but the enzymatic Glu sensors show enzyme activity–dependent sensitivities [9]. Their detection performances are seriously influenced by some environmental factors such as room temperature, humidity, pH value, etc. [10]. Some limitations are related with enzymes, such as enzyme payload, enzyme activity, poor reproducibility, and poor stability during process [11]. Overall, enzymes have become a difficulty to some degree in the development and application of enzymatic Glu sensors.

Compared with enzymatic Glu sensors, non–enzymatic sensors are easy to realize, long–term, and stable Glu detection, whose detection performances are not influenced by environmental factors, providing a support for high–performance continuous monitoring of Glu [12]. Non–enzymatic Glu sensors have much more choices in material platforms to achieve larger surface area rather than the stacking of enzymes. For example, metal–organic frameworks (MOFs) are a kind of porous materials constructed by the self–assembly of metal ions with organic ligands into highly ordered structures [13,14]. Their poor conductivity blocks raw MOFs as electrocatalysts for sensing Glu. Metal nanoparticles (NPs), such as nano gold and silver, have high specific surface areas, catalytic activity, and electrical conductivity [15]. Doping metal NPs into the electrochemical Glu sensors can greatly improve the conductivities and the detection performances of the MOF–based electrochemical Glu sensors [16,17]. Furthermore, MOFs and metal NPs integrate into modified electrodes as Glu sensors with the effective reaction areas and the interface electron migration rates. It shows the advantages of high catalysis and high sensitivity for the oxidation of Glu. Without limitations in biological enzymes, the working electrodes of NPs@MOFs composites are of great significance as non–enzymatic Glu sensors with high sensitivities and anti–interference [18,19,20]. Due to the high cost of nano novel metal–based electrochemical sensors, the application of nano transition metals in electrochemical sensors is expected to reduce the cost but not sacrifice the advantages of doping nano novel metal. The preparation and large–scale application of low–cost and high–performance transition metal–based electrochemical devices are a support for Glu detection [21,22,23]. There are a lot of explorations on transition metal NPs@MOF as electrochemical Glu sensors. For example, as a nonenzymatic electrochemical analytical chip, a cobalt MOF/carbon cloth/paper button–sensor quantitatively determines Glu. The sensor was applied in complex biosystems of human serum, urine, and saliva, showing high selectivity and durability [24].

Based on the aforementioned discussions, we deposit Cu NPs in a cobalt MOF (Co–MOF), aiming at the integrated advantages: porous structure in Co–MOF with active sites can host Cu NPs in a restricted area, and thus control Cu NPs growing in a small size and prevent Cu NPs from migration and agglomeration in preparation and electrochemical measurements. Co–MOF integrating with Cu NPs can effectively improve the electrocatalytic activity. Herein, our work presents a Co–MOF, [Co₃(BDC)₃(DMU)₂], as a non–enzymatic Glu sensor, which was prepared under ionothermal conditions. The Co–MOF was characterized in detail by single crystal X–ray diffraction (SCXRD), powder X–ray diffraction (XRD), Fourier transform infrared spectroscopy (FT–IR), thermogravimetric analysis (TGA), energy dispersive X–ray spectrometry (EDS), and X–ray photoelectron spectroscopy (XPS). Cu@Co–MOF and its composite electrode Cu@Co–MOF/GCE (GCE = glassy carbon electrode) were prepared through a sequential deposition–reduction process. Cu@Co–MOF/GCE electrode exhibits a high electrocatalytic performance to Glu detection, which returns accurate Glu concentrations in human serum and orange juice. Cu@Co–MOF/GCE can be regarded as a non–enzymatic electrochemical Glu sensor with high sensitivity, anti–interference, reproducibility, stability, and rapid current response.

2. Materials and Methods

2.1. Materials and Instruments

All chemicals are in analytical grade and obtained from commercial sources without purification. Co(NO₃)₂·6H₂O, CuSO₄, terephthalic acid (H₂BDC), ethanol, methanol, N,N–dimethylformamide (DMF), NaBH₄, Al₂O₃ (0.5 μm and 50 nm) powder, HNO₃, H₂SO₄, KCl, K₃Fe(CN)₆ NaOH, Glu were bought from Sinopharm Chemical (Shanghai, China). Interferents of D–Mannose (D–Man), D–fructose (D–Fru), aspartic acid (AA), dopamine (DA) urea, and uric acid (UA) were obtained from Aladdin (Shanghai, China). Choline chloride (ChCl) and 1,3–dimethylurea (DMU) were purchased from Tokyo Chemical (Tokyo, Japan). Nafion solution of 5 wt% was bought from Sigma–Aldrich (Shanghai, China). KBr pellets of FT–IR grade was bought from Aldrich. Minutemaid orange juice was bought from a local supermarket.

XRD were measured on a Rigaku MiniFlex 600 (Japan) diffractometer under 40 kV and 15 mA at room temperature. FT–IR spectra were collected on a Bruker Tensor 27 FT–IR spectrometer in the wave number range of 4000–400 cm⁻¹. TGA was performed on a SDT Q600 V8.3 Build 101 instrument with a heating rate of 10 °C·min⁻¹ and in a N₂ atmosphere with a flow rate of 20 cm³·min⁻¹. The surface elemental contents were determined by EDS on a Philips–FEI Quanta 200 scanning electron microscope. XPS was used to investigate the chemical states of the surface elements in Co–MOF on an Axis Ultra (Kratos Analytical Ltd., Manchester, UK). A CHI 660E (CH Instruments, Inc. Shanghai, China) electrochemical workstation from CH Instruments, Inc. (Shanghai, China) inspected all electrochemical measurements at room temperature.

2.2. Preparation

Co–MOF. Co(NO₃)₂·6H₂O (0.40 mmol, 0.1164 g) and H₂BDC (0.20 mmol, 0.0332 g) were mixed with a deep eutectic solvent (DES)–type ionic liquid of ChCl (1 mmol, 0.1396 g) and DMU (2 mmol, 0.1762 g) as in a crystallization vial. The mixture was heated at 100 °C for 3 days, and naturally cooled to room temperature. The as–synthesized purple crystals of Co–MOF were washed with DMF and ethanol and collected for the further characterizations. FT–IR data (in KBr, cm⁻¹): 3475 (w), 3411 (m), 3352 (m), 2927 (w), 2370 (w), 2073 (w), 1595 (s), 1388 (s), 1142 (w), 1013 (m), 886 (m), 822 (s), 748 (s), 543 (s).

Cu²⁺/Co–MOF. Three groups of ca. 0.1238 g Co–MOF were added into 4 mL CuSO₄ methanol solution with concentrations of 5, 10, and 15 mmol∙L⁻¹ (mM), respectively. After 6 h of continuous stirring, the suspensions were centrifuged and dried in a vacuum oven at 60 °C for 12 h to obtain Cu²⁺@Co–MOF.

Cu@Co–MOF. Three groups of 10, 20, and 30 mg NaBH₄ were dissolved in 4 mL methanol, and then mixed with the above Cu²⁺/Co–MOF with a 30 min strong agitation. The mixture turned to black immediately, the suspensions were filtered, washed with methanol and dried at 60 °C to obtain Cu@Co–MOF.

Cu@Co–MOF/GCE electrode. Amounts of 0.5 μm and 50 nm alumina slurry on a polishing cloth were continuously used to polish a GCE with a 5 mm diameter to a mirror surface, then washed with HNO₃ solution of V_water:V_HNO3 = 1:1, anhydrous ethanol and ultrapure water by sonication. GCE was further activated by 0.5 M H₂SO₄ and 0.1 M KCl/5 mM K₃Fe(CN)₆, respectively. A total of 5 mg ground Cu@Co–MOF powder was dispersed in 1 mL anhydrous ethanol with 20 min sonication to form a uniform Cu@Co–MOF suspension of 5 mg∙mL⁻¹. Cu@Co–MOF/GCE electrode was obtained by a 10 μL Cu@Co–MOF suspension and a 5 μL nafion solution of 5 wt% was dropped on the GCE surface, then dried at room temperature.

2.3. Electrochemical Measurements

Three–electrode system was used in the electrochemical measurements: The as–prepared Cu@Co–MOF/GCE is as the working electrode, a platinum wire as the counter electrode and KCl saturated Ag/AgCl as the reference electrode. The electrochemical performance of Cu@Co–MOF/GCE for sensing Glu was estimated by cyclic voltammetry (CV) and amperometric I–t curve methods.

2.4. Crystal Structure Determination

A suitable single crystal was mounted and collected the crystal data on a Bruker D8 Quest CCD diffractometer with a Cu–Kα radiation with λ = 1.54184 Å at 120 K. The crystal data was reduced via the ω scan technique by Bruker XSCANS program, and the direct method was used to solve the crystal structure of Co–MOF with SHELXL–2014/7 crystallographic software package. All non–hydrogen atoms were refined anisotropically. The positions of all hydrogen atoms were calculated according to their carriers and then were refined isotropically in the final refinement stage.

Crystal data (excluding structure factors) of Co–MOF has been deposited in the Cambridge Crystallographic Data Centre (CCDC) with No. of 2195853. The data can be obtained for free from CCDC via www.ccdc.cam.ac.uk/data_request/cif (accessed on 8 October 2022).

3. Results

3.1. Structure Description

[Co₃(BDC)₃(DMU)₂] (Co–MOF) crystalizes in the triclinic Pī space group, whose asymmetric unit contains one and a half Co(II) centers, three separate BDC²⁻ ligands of 0.5 occupancy and a DMU molecule. BDC²⁻ ligand adopts two coordination modes of μ₄−bis–bidentate bridging and μ₄–bis–monodentate bridging/chelating (Supplementary Information (SI), Figure S1). Six–coordinated Co1 locates in an octahedron constructed by six carboxylate O atoms from six separate BDC²⁻ ligands. Five–coordinated Co2 is in a square pyramidal geometry, in which four carboxylate O atoms from two BDC²⁻ ligands shape the basal plane, and an O atom from DMU is in the apex. Central Co2 connects two symmetric terminal Co1 by two pairs of μ₂–bidentate COO⁻ groups and one pair of μ₂–monodentate bridging/chelating COO⁻ groups, respectively, and one DMU ligand binds to each terminal Co1 into a linear trinuclear [Co₃(COO)₆(DMU)₂] secondary building unit (SBU) (SI, Figure S2). Neighboring [Co₃(COO)₆(DMU)₂] SBUs are connected by the three separate BDC²⁻ ligands with O11/O12 and O31/O32 (μ₄–bis–bidentate bridging), or O21/O22 (μ₄–bis–monodentate bridging/chelating) into three 1D chains along the [110], [011] and b–directions, respectively (SI, Figure S3a–c). The chains along the [110] and b–directions weave a 2D layer, which topologizes a [4,4] network. The 2D layers further stack into a 3D framework with the fabrication of the chains along the [011] direction (Figure 1). With the rest phenyl rings of the three separate BDC²⁻ ligands dummied as the 2–connected sticks and the [Co₃(COO)₆(DMU)₂] SBUs as the six–connected nodes, the point symbols of the rest phenyl rings are {8}, and the one of [Co₃(COO)₆(DMU)₂] is {8¹².12³}. Therefore, the 3D framework is topologized as a 2,6–connected {8¹².12³}{8}₃ network.

3.2. Characterizations

XRD. The experimental and simulated XRD patterns of Co–MOF, and those of Co–MOF and Cu@Co–MOF were compared (Figure 2). The experimental XRD pattern of Co–MOF is in good agreement with the one simulated from the single crystal data, indicating that the bulk sample of Co–MOF is in high crystallinity and purity for the following characterizations. In the synthetical process of Cu@Co–MOF, metal precursors contained in organic solvents were used, a part of which will deposit on the surface of Co–MOF after drying, and then tend to aggregate into nanosheets, while high concentration NaBH₄ solution reduces Cu²⁺, thus avoiding Cu NPs unevenly aggregating on the surface of Co–MOF [25]. The XRD diffraction peaks of Co–MOF can be easily identified from those of Cu@Co–MOFs, indicating that Co–MOF stays the structural stability after Cu NPs are loaded. Comparing all Cu@Co–MOFs with Cu²⁺ ranging 5, 10, and 15 mM, the same XRD patterns demonstrate the isomorphism and the independence of Co–MOF on Cu²⁺ concentrations.

FT–IR. The characteristic absorption peaks of Co–MOF, Cu@Co–MOF and free H₂BDC ligand are analyzed by FT–IR (SI, Figure S4). The peaks within 3410–3310 cm⁻¹ and 1650–1550 cm⁻¹ are related with the symmetric and asymmetric stretching vibration peaks of –NH from the secondary amine DMU in Co–MOF and Cu@Co–MOF, which do not appear in H₂BDC. Those in 3100–3000 cm⁻¹ are attributed to very weak v_C–H from phenyl rings in Co–MOF, Cu@Co–MOF and H₂BDC. Compared to 1682 cm⁻¹ of carbonyl in free H₂BDC, the peaks, respectively move to 1720–1550 cm⁻¹ and 1450–1250 cm⁻¹, attributed to the asymmetric and symmetric stretching vibrations (v_as(–COO) and v_s(–COO)) of the carboxyl groups in Co–MOF and Cu@Co–MOF. The wavelength differences are larger than 200 cm⁻¹, supporting the carboxyl groups are in coordination [26,27], agreeing with the structural analysis. Comparing Cu@Co–MOF with Co–MOF, the peaks at 3348 and 3388 cm⁻¹ become weak, concerning with the interactions between Cu NPs and –NH groups after Cu²⁺ deposing–reducing on Cu–MOF; similarly, the peaks at 1552 and 1626 cm⁻¹ are weakened, but the one at 1594 cm⁻¹ concerning with the in–plane bending vibration of –NH group is strengthened. All changes support that Cu²⁺ loads on Co–MOF through the interaction between Cu²⁺ and –NH groups during the composite process [28,29].

TGA. The TGA curve shows there are three steps in the thermal decomposition of Co–MOF (Figure S5). There is a weight loss of only ca. 1.85% before 340 °C, coming from the loss of absorbed water or organic solvents. The second weigh loss of 20.68% is attributed to the removal of DMU as the temperature rises to 400 °C, very close to the calculated value of 20.85%. Followed with the collapse of the MOF skeleton, the third decomposition ends at 570 °C with 44.75% weight loss, relating with the decomposition of BDC²⁻ ligands.

EDS. Surface elemental contents of Co–MOF and Cu@Co–MOF were analyzed by EDS. C, N, O and Co elements can be observed on the surface of Co–MOF with the contents of 65.10, 7.47, 21.57 and 5.85 at%, respectively (Figure S6a), basically in accord with the formula C₃₀H₂₈Co₃N₄O₁₄. Besides C, N, O, and Co elements with closed contents (64.10, 6.13, 25.23, and 4.40 at% for C, N, O, and Co, respectively) in Cu@Co–MOF, there is Cu element of 0.22 at%, demonstrating the load of Cu NPs on the surface of Co–MOF (Figure S6b).

XPS. Surface electronic states and the compositions of Co–MOF and Cu@Co–MOF were inspected by XPS. XPS of Co 2p in Co–MOF, Cu²⁺/Co–MOF and Cu@Co–MOF are listed in Figure 3, which mainly includes Co 2p_3/2 and Co 2p_1/2 characteristic regions. The Co 2p_3/2 region in Co–MOF contains the main peak at 781.29 eV and the accompanying one at 786.22 eV (Figure 3a). Similarly, the main peak at 797.15 eV and its accompanying peak at 802.70 eV can be found in the Co 2p_1/2 region in Co–MOF; in Cu²⁺/Co–MOF, the main and accompanying peaks in Co 2p_3/2 region are at 781.48 and 786.13 eV, respectively, those in Co 2p_1/2 region are at 797.32 and 802.60 eV (Figure 3b); the corresponding main and accompanying peaks of Cu@Co–MOF are at 781.59 and 786.20 eV in Co 2p_3/2 region, and at 797.39 and 802.69 eV in Co 2p_1/2 region, respectively (Figure 3c). By comparing the above peaks, Co–MOF, Cu²⁺/Co–MOF and Cu@Co–MOF show the same main and the accompanying peaks both in Co 2p_3/2 and Co 2p_1/2 characteristic regions, indicating the incorporation with Cu²⁺ or Cu NPs does not change the valence state of Co(II) cation.

XPS of Cu 2p_3/2 and Cu 2p_1/2 characteristic regions in Cu²⁺/Co–MOF and Cu@Co–MOF are also compared (Figure 4). In Cu²⁺/Co–MOF, the peaks at 933.26 eV in Cu 2p_3/2 and at 953.78 eV in Cu 2p_1/2 correspond to Cu(II) (Figure 4a). Differently, there exists four peaks in Cu 2p_3/2 and Cu 2p_1/2 regions of Cu@Co–MOF: those at 932.80 eV in Cu 2p_3/2 and 952.55 eV in Cu 2p_1/2 are attributed to Cu(0); those are at 935.27 eV in Cu 2p_3/2 and 954.82 eV in Cu 2p_1/2 related with Cu(II) (Figure 4b) [30,31,32]. It indicates that Cu²⁺ deposits in the Co–MOF to form Cu²⁺/Co–MOF, but only a part of deposited Cu²⁺ were reduced to Cu(0). Cu²⁺ and Cu(0) co–exist in Cu@Co–MOF.

3.3. Electrochemically Sensing Glu by Non–Enzymatic Cu@Co–MOF

CV test. Cu@Co–MOF was modified on the surface of GCE to prepare Cu@Co–MOF/GCE as working electrode. CV tests were carried out in 0.01 M NaOH at working potential of +0.6 V (Figure 5). The redox peaks of Co^II/Co^III can be obviously observed in all the CV curves of Cu@Co–MOF with feeding Cu²⁺ concentrations (C_Cu2+) within 5–15 mM. With C_Cu2+ increasing, the redox peaks weaken, indicating C_Cu2+ of 5 mM shows the most sensitive current response (Figure 5a); 5 mM Cu²⁺ undertakes the synergistic role with Co–MOF. Higher Cu²⁺ concentration will occupy more active sites and prevent the electron transfer. After the reduction of Cu²⁺, high Cu²⁺ concentration easily leads to the aggregation of Cu NPs, decreasing electrocatalytic performance. It supports the decreased trend of electrocatalysis with Cu²⁺ concentration. However, lower Cu²⁺ concentration has a difficulty in generating appropriate Cu NPs to form sufficient electron transfer path. Therefore, 5 mM is selected as the feeding Cu²⁺ concentration for the subsequent tests. By comparing Cu@Co–MOF/GCE and Co–MOF/GCE in the potential vs. current response, Cu@Co–MOF/GCE shows a much stronger redox peak, indicating the conductivity of Co–MOF improved by Cu NPs. After 1 mM Glu is added, the redox peak of Co–MOF/GCE slightly weaken, suggesting an insensitivity of Co–MOF/GCE to Glu. Differently, Cu@Co–MOF/GCE causes the anode and cathode currents increased greatly at the initial potential of +0.4 V as 1 mM Glu is added (Figure 5b). It suggests that Cu@Co–MOF/GCE has a better catalytic oxidation effect on Glu with the improved conductivity.

The detection mechanism of Cu@Co–MOF sensing Glu is illustrated in Scheme 1, which concerns a Glu oxidizing process explained by Reactions 1 and 2. Blank Co–MOF/GCE compared with blank Cu@Co–MOF/GCE, an obvious improved electroactivity is found, showing Cu NPs effectively increase conductivity of Co–MOF/GCE. When 1 mM Glu is added into 0.01 mM NaOH, Co–MOF/GCE exhibits a negligible electroactivity. This concerns the poor electroconductivity of Co–MOF, resulting in Co–MOF/GCE’s weak electrocatalysis to Glu, while as Glu contacts with Cu@Co–MOF/GCE, a significant enhancement occurs. The above comparisons demonstrate the improvement of Cu NPs on the electrocatalytical performance of Co–MOF/GCE. The sensing mechanism is related with a synergistic effect between Co–MOF and Cu NPs. Cu is oxidized to CuO and CuOOH in an alkaline medium, and therefore, Cu reaches the high oxidation state of Cu^Ⅲ [33]. An intermediate enediol from the deprotonation of Glu in alkaline medium can be oxidized into gluconolactone when contacting with CuOOH [25,34]. The improved electrocatalysis of Cu@Co–MOF/GCE mainly benefits from the porous structure of Co–MOF. Porous structure in Co–MOF can host Cu NPs in a restricted area, and thus control Cu NPs growing in a small size and prevent Cu NPs from agglomeration, migration and electrochemical dissolution in preparation and electrocatalytic processes. The full use of pores in Co–MOF provides large active surface area and active sites to encapsulate Cu NPs on the –NH groups. Co–MOF with encapsulated Cu NPs can effectively improve the electrocatalytic activity. Furthermore, the comparison of Cu@Co–MOF before and after the electrochemical detection indicates Cu@Co–MOF can keep enough stability to preserve the crystallinity from the suffering of NaOH and current (Figure S7).

Co^II–MOF + OH⁻ − e⁻ → Co^III–MOF(1)

Co^III–MOF + glucose → Co^II–MOF + gluconolactone(2)

Amperometric I–t curve test. The chronoamperometric response of Cu@Co–MOF/GCE to Glu concentrations (C_Glu) ranging from 0.005 to 1.8 mM was recorded in 0.01 M NaOH at working potential of +0.6 V [35]. With Glu added, the current response gradually increases with increased C_Glu (Figure 6a). By depicting the plot of detected current vs. C_Glu, the linear relationships can be figured out in the C_Glu sections of 0.005–0.4 mM and 0.4–1.8 mM (Figure 6b). The linear equations are as follows with high correlation coefficient R²:

C_Glu = 0.005–0.4 mM:

${\mathrm{j}}_{\mathrm{Cu}@\mathrm{Co}–\mathrm{MOF}/\mathrm{GCE}}\left({\mathrm{mA}\mathrm{cm}}^{-2}\right)=0.020{\mathrm{C}}_{\mathrm{Glu}}\left(\mathsf{\mu }\mathrm{M}\right)+8.266\left({\mathrm{R}}^2=0.9802\right)$

C_Glu = 0.4–1.8 mM:

${\mathrm{j}}_{\mathrm{Cu}@\mathrm{Co}–\mathrm{MOF}/\mathrm{GCE}}\left({\mathrm{mA}\mathrm{cm}}^{-2}\right)=0.012{\mathrm{C}}_{\mathrm{Glu}}\left(\mathsf{\mu }\mathrm{M}\right)+6.096\left({\mathrm{R}}^2=0.9800\right)$

EDS analysis shows only 0.22 at% Cu deposits on Co–MOF, meaning ca. one Cu corresponding to 30 Co^II. It hints a saturation effect in Cu@Co–MOF/GCE sensing Glu. It comes from the fact that all active sites of Cu NPs loading on Co–MOF are occupied by Glu molecules. The sensitivities of Cu@Co–MOF/GCE are calculated as 282.89 μA mM⁻¹ cm⁻² within C_Glu = 0.005–0.4 mM, and 113.15 μA mM⁻¹ cm⁻² within C_Glu = 0.4–1.8 mM. The detection limit was dived to 1.6 μM at a signal–to–noise (S/N) ratio of 3 [36].

Cu@Co–MOF/GCE is compared with other reported non–enzymatic electrochemical Glu sensors in Table 1 [37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58]. Its detection limit of 1.6 μM is lower than a lot of non–enzymatic electrochemical Glu sensors, and comparable to Cu@HHNs (1.97 μM) [39], Au@Ni–BTC (1.5 μM) [46], CPO–27–Ni^II (1.46 μM) [47], and Co^II–MOF/Acb (1.7 μM) [56], but higher than Ni/Co(HHTP)MOF/CC (0.1 μM) [37], NiCo–LDH/CC (0.12 μM) [40], Co–MOF/EG (0.58 μM) [44], Cu(OH)₂@CoNi–LDH NT–NSs/GSPE (0.6 μM) [45], SiCNPs–ENFM (0.56 μM) [3], NiCo–MOF (0.29 μM) [49], UiO–67@Ni–MOF (0.98 μM) [50] and Ag@TiO₂@ZIF–67 (0.99 μM) [55]. Similarly, the sensitivity of 282.89 μA mM⁻¹ cm⁻² within C_Glu = 0.005–0.4 mM is more sensitive than most of the reported electrochemical Glu sensors, but lower than some sensors, such as Ni/Co(HHTP)MOF/CC (3250 μA mM⁻¹ cm⁻²) [37], CoZn–BTC/GCE (1218 μA mM⁻¹ cm⁻²) [22], Cu@HHNs (1594.2 μA mM⁻¹ cm⁻²) [39] and Ni_0.7Co_0.3(OH)₂ (1541 μA mM⁻¹ cm⁻²) [42]. Overall, Cu@Co–MOF/GCE shows a low detection limit and a high sensitivity to Glu electrochemical detection.

Response time and anti–interference. Cu@Co–MOF/GCE exhibits a rapid current response of less than 7 s to C_Glu change (Figure S8). The anti–interference performance was evaluated by amperometric method. In the human body, the normal blood Glu concentration locates in 3–8 mM and the one in diabetes higher than 11.1 mM; while compared to the concentrations of UA, AA, and DA are around 0.13–0.46 mM, 0.23 μM, and 0.1 mM, respectively, in physiological conditions. Therefore, we carried out the anti–interference test in the presence of 0.1 mM Glu and 0.01 mM of each interferent. The current responses were measured by continuous dropping method when 2 μM, 0.1 mM Glu was dropped into 0.01 M NaOH comparing with those of 0.01 mM interferents including D–Fru, D–Man, urea, AA, UA, and DA. As 0.1 mM Glu is added every injection, remarkable current signals always immediately appear (Figure 7). Because of the dilution effect, the current responses raised by Glu become weak, while when the interferents are added one by one into the system, the current responses of oxidizing interferents are observed to be very faint. If setting the percentage amperometric response of the first adding of Glu as 100%, those amperometric responses of the interferents are 3.17, 6.35, 1.59, 9.52, 4.76, and 11.11%. Therefore, the high anti–interference of Cu@Co–MOF is expectable in electrochemically sensing Glu.

Stability and repeatability. Stored at 4 °C for 3–15 days, Cu@Co–MOF/GCE as non–enzymatic electrochemical sensor detects 1.0 mM Glu in 0.01 M NaOH every three days by amperometric method, whose current changes were recorded in Figure 8a. The current of the fresh Cu@Co–MOF/GCE is set as 100%. In the first three days, the current remains 96.50%, then 85.78%, 77.06%, 72.39%, and 69.25% for the following three–day sections. The current downward trend becomes slow. Even after the 15 days, Cu@Co–MOF/GCE still remains nearly 70% current response to Glu, indicating Cu@Co–MOF/GCE stays enough sensitivity and stability to Glu within 15 days. Five parallel measurements of sensing Glu were carried out with five groups of fresh Cu@Co–MOF/GCE sensors to evaluate the repeatability of Cu@Co–MOF/GCE (Figure 8b). The relative standard deviation (RSD) of the five parallel measurements is 5.84%, indicating the high repeatability of Cu@Co–MOF/GCE.

3.4. Sensing Glu in Human Serum and Orange Juice

Standard addition method was used to evaluate the application performance of Cu@Co–MOF/GCE sensing Glu in human serum and orange juice. A total of 50 μL human serum was diluted by 50 mL, 0.01 M NaOH, then 1.0 mM Glu followed to prepare 50, 100, and 200 μM Glu standard solutions. The current responses of each C_Glu were recorded for five times by CV method (Table 2). Through the linear equation of ${\mathrm{j}}_{\mathrm{Cu}@\mathrm{Co}–\mathrm{MOF}/\mathrm{GCE}}\left({\mathrm{mA}\mathrm{cm}}^{-2}\right)=0.020{\mathrm{C}}_{\mathrm{Glu}}\left(\mathsf{\mu }\mathrm{M}\right)+8.266$, the found C_Glu were calculated as 50.01, 94.93, and 188.97 μM based on the found currents. The recoveries (defined as the found C_Glu/added C_Glu) were calculated as 100.02%, 94.93%, and 94.49%. The RSDs (n = 5) range from 2.27% to 4.30%, all less than 5%.

The supernatant of minutemaid organic juice was obtained by 8000–rpm centrifugation for 5 min; 50 mL, 0.01 M NaOH diluted 50 μL extracted supernatants. Similar sensing Glu processes were carried out in a high–sugar orange juice. The found C_Glu are 49.04, 93.27, and 189.54 μM, whose recoveries correspond to 98.08%, 93.27%, and 94.77% with small RSDs ranging 1.61% to 3.08%. In total, the found C_Glu in human serum and orange juice are close to the added C_Glu, confirming that non–enzymatic Glu sensor of Cu@Co–MOF/GCE can detect Glu with high accuracy and reliability in the environments of rich endogenous biomolecules and high sugar content.

4. Conclusions

A cobalt metal–organic framework (Co–MOF), [Co₃(BDC)₃(DMU)₂], was prepared via an ionothermal reaction, which features three 1D chains along the [110], [011] and b–directions. The chains along the [110] and b–directions interconnect into a 2D [4,4] topological network, and finally shape a 3D 2,6–connected {8¹².12³}{8}₃ network by the connection of the [011] chains with the 2D layers. Co–MOF was further synthesized into a Cu@Co–MOF composite material through a sequential deposition–reduction process. Cu@Co–MOF/GCE composite electrode acts as a non–enzymatic electrochemical sensor to detect Glu in 0.01 M NaOH. Cu@Co–MOF/GCE shows excellent electrocatalytic activity for Glu detection. The chronoamperometric response of Cu@Co–MOF/GCE to C_Glu displays two linear relationships of j = 0.020·C_Glu + 8.266 (within 0.005–0.4 mM Glu) and j = 0.012·C_Glu + 6.096 (within 0.4–1.8 mM Glu) at a +0.6 V working potential. The sensitivities of Cu@Co–MOF/GCE are calculated as 282.89 and 113.15 μA mM⁻¹ cm⁻², respectively, for the two C_Glu ranges. The detection limit is calculated as 1.6 μM at S/N = 3. The low detection limit and high sensitivities of Cu@Co–MOF/GCE to Glu detection are better than or comparable with the other reported MOF–based non–enzymatic electrochemical Glu sensors. Furthermore, Cu@Co–MOF/GCE exhibits a rapid current response of less than 7 s to C_Glu change, and a high anti–interference with 0.01 mM D–Man, D–Fru, AA, DA, urea and UA as the interferents. Within the storage time of 15 d, Cu@Co–MOF/GCE shows a gradually decreased current trend of 96.50%, 85.78%, 77.06%, 72.39% and 69.25% for every three days’ Glu electrochemical detection. The nearly 70% current response to Glu indicates an enough sensitivity and stability of Cu@Co–MOF/GCE within 15 days. Five parallel measurements with RSD of 5.84% also demonstrate the high repeatability of Cu@Co–MOF/GCE. Glu detection were carried out in human serum and orange juice. All found C_Glu are very close to those added C_Glu with low RSDs and high recoveries. It indicates Cu@Co–MOF/GCE as a non–enzymatic electrochemical sensor has a high accuracy and a reliability for Glu detection in real samples with rich endogenous biomolecules and sugars.

Author Contributions

Conceptualization, L.X. and H.J.; data curation, Z.-Z.M. and Y.-S.W.; formal analysis, Z.-Z.M. and Y.-S.W.; funding acquisition, L.X. and H.J.; investigation, B.L. and Z.-Z.M.; methodology, L.X. and H.J.; project administration, L.X.; software, B.L., Y.-S.W. and Z.-Z.M.; validation, B.L.; writing—original draft, Z.-Z.M.; writing—review and editing, L.X. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article. Further inquiries can be directed to the corresponding authors.

Conflicts of Interest

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures, Scheme and Tables

Figure 1. The structure construction of Co–MOF.

Figure 2. The experimental XRD patterns of Co–MOF and Cu@Co–MOF.

Figure 3. XPS of Co 2p in (a) Co–MOF, (b) Cu2+/Co–MOF, and (c) Cu@Co–MOF.

Figure 4. XPS of Cu 2p in (a) Cu2+/Co–MOF and (b) Cu@Co–MOF.

Figure 5. (a) CV curves of Cu@Co–MOF/GCE with Cu2+ concentration within 5–15 mM; (b) CV curves of Cu@Co–MOF/GCE and Co–MOF/GCE in 0.01 M NaOH with (solid line) or without (dash line) 1 mM Glu added.

Scheme 1. The mechanism of Cu@Co–MOF/GCE sensing Glu.

Figure 6. (a) The chronoamperometric curve of Cu@Co–MOF/GCE to CGlu ranging from 0.005 to 1.8 mM in 0.01 M NaOH at working potential of +0.6 V; (b) the calibration curves of current vs. CGlu.

Figure 7. The anti–interference of Cu@Co–MOF/GCE sensing 0.1 mM Glu with 0.01 mM D–Man, D–Fru, AA, DA, urea and UA as the interferents in 0.01 M NaOH at a working potential of +0.6 V.

Figure 8. (a) The histogram of current vs. storage time of Cu@Co–MOF/GCE sensing 1.0 mM Glu in 0.01 M NaOH with Cu@Co–MOF/GCE stored at 4 °C for 3–15 days; (b) the histogram of five parallel Glu detections by fresh Cu@Co–MOF/GCE sensing Glu.

Table 1

Comparison of detection performances of reported non–enzymatic electrochemical Glu sensors with Cu@Co–MOF.

Electrodes	Detection Limit (μM)	Detection Range (mM)	Sensitivity (μA·mM−1·cm−2)	Refs.
Cu@Co–MOF	1.6	0.005–0.4	282.89	This work
		0.4–1.8	113.15
Ni/Co(HHTP)MOF/CC a	0.1	0.3–2.312	3250	[37]
CoZn–BTC/GCE b	4.7	0.001–0.255	1218	[22]
		0.255–2.53	510
Co0.33Ni0.67–HLDH c	3.1	0.01–2	242.9	[38]
Cu@HHNs d	1.97	0.005–3	1594.2	[39]
NiCo–LDH/CC e	0.12	0.001–1.5	5.12	[40]
Ni(TPA)–SWCNTf	4.6	0.02–4.4	−	[41]
Ni0.7Co0.3(OH)2	3.42	0.5–2.5	1541	[42]
CuTiPNPs g	7	0.25–2	7.81	[43]
Co–MOF/EG h	0.58	0.001–3.3	330	[44]
Cu(OH)2@CoNi–LDH NT–NSs/GSPE i	0.6	0.002–3.2	1895	[45]
		3.2–7.7	1322
Au@Ni–BTC	1.5	0.005–7.4	1447.1	[46]
CPO–27–NiII j	1.46	0.04–6	40.95	[47]
SiCNPs–ENFM k	0.56	0.5–20	30.75	[3]
Cu–in–ZIF–8/SPCE l	2.76	0–0.7	412	[20]
Cu–Ni/NF m	2	0.001–0.6	11340	[48]
MWCNTs–PB n	4.95	0.01–1	105.93	[21]
NiCo–MOF	0.29	0.001–3.8	684.4	[49]
UiO–67@Ni–MOF	0.98	0.005–3.9	203.4	[50]
CoPO MA/NF o	1	0.001–1.16	3.55	[51]
Cu2O@ZIF–67	6.5	0.01–10	307.02	[52]
		10–16.3	181.34
AgNPs/MOF–74 p	4.7	0.01–4	1.29	[53]
Ag@TiO2@ZIF–67	0.99	0.048–1	78.8	[54]
CoII–MOF/Acb q	1.7	0.005–1	255	[55]
Cu–hemin MOFs r	2.73	0.009–36	22.77	[56]
Tb@mesoMOFs–CNT s	8	0.025–17	−	[57]
Co NP/Porous C	5.69	0.1–1.1	227	[58]

Notes: ^a HHTP: triphenylene–2,3,6,7,10,11–hexaol; CC: carbon cloth; ^b H₃BTC: 1,3,5–benzene tricarboxylic acid; GCE: glassy carbon electrode; ^c HLDH: hollow LDHs; ^d HHNs = hydrophilic hierarchically porous nanoflowers; ^e LDHs = layered double hydroxides; ^f TPA = terephthalic acid; SWCNT = single–walled carbon nanotubes; ^g CuTiPNPs = copper–modified titanium phosphate nanoparticles; ^h EG = exfoliated graphene; ⁱ NT: nanotube; NSs = Nanosheets; GSPE = graphite screen–printed electrode; ^j CPO–27–Ni^II: Ni₂(dihydroxyterephthalic acid); ^k SiCNPs = silicon carbide nanoparticles; ENFM = electrospun–nanofibrous–membrane; ^l ZIF–8 = zeolitic imidazolate framework 8; SPCE = screen–printed carbon electrodes; ^m NF = nickel foam; ⁿ MWCNTs–PB: multi–walled carbon nanotubes and Prussian blue; ^o CoPO MA/NF = Cobalt phosphate microsheet arrays supported on Ni foam; ^p NP = nano particles; ^q Acb = acetylene black; ^r mesoMOFs = mesoporous metal–organic frameworks; ^s CNTs = carbon nanotubes.

Table 2

The Glu sensing in human serum and orange juice by Cu@Co–MOF/GCE.

Samples	Added (μM)	Found ± SD (μM)	Recovery (%)	RSD
Serum	50	50.01 ± 2.15	100.02	4.30%
	100	94.93 ± 2.61	94.93	2.75%
	200	188.97 ± 4.23	94.49	2.24%
Orange juice	50	49.04 ± 1.60	98.08	1.61%
	100	93.27 ± 2.87	93.27	3.08%
	200	189.54 ± 4.46	94.77	2.35%

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/chemosensors10100416/s1, Figure S1: The coordination modes of BDC²⁻ ligand in Co–MOF; Figure S2: The structure motif of the linear trinuclear [Co₃(COO)₆(DMU)₂] SBU; Figure S3: [Co₃(COO)₆(DMU)₂] SBUs connect BDC²⁻ ligands with O11/O12 (a), O21/O22 (b), and O31/O32 (c) into three 1D chains along the [110], b– and [011] directions, respectively; Figure S4: FT–IR spectra of Co–MOF, Cu@Co–MOF and free H₂BDC ligand; Figure S5: TGA curve of Co–MOF; Figure S6: EDS of Co–MOF (a) and Cu@Co–MOF (b); Figure S7: The comparison of XRD patterns of Co-MOF, Cu@Co-MOF, Cu@Co-MOF/Nifion and Cu@Co-MOF/Nifion after the electrochemical detection; Figure S8: The current response of Cu@Co–MOF/GCE to Glu.

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