DOI:
10.1039/D4TB01729C
(Paper)
J. Mater. Chem. B, 2024, Advance Article
Facile stoichiometric interfacial surface bonded cerium oxide and graphene oxide heterostructure for efficient electrochemical non-enzymatic detection of dopamine†
Received
5th August 2024
, Accepted 21st August 2024
First published on 22nd August 2024
Abstract
Emerging technology in the new era of sensors to detect and quantify neurological reaction-based research has demanded the development of sensors for the neurotransmitter dopamine (DA). In recent decades, electrochemical sensors have offered rapid and sensitive detection of DA, but the presence of interfering compounds, such as uric acid (UA) and ascorbic acid (AA), poses a great threat to the development of DA sensors. Additionally, reusing traditional methods leads to challenges like prolonged preparation and expensive instruments. This research work offers a nanohybrid two-dimensional (2D) paper-like graphene oxide (GO) and three-dimensional (3D) cerium oxide nanosphere (CeONS) heterostructure composite (G-CeONS) created via stoichiometric synthesis for the non-enzymatic detection of DA oxidation in the presence of other complex biological compounds. The constructed G-CeONS nanohybrid composite enables enhanced selectivity and sensitivity towards DA detection through its interfacial engineering. The heterostructure formation of a 2D nanosheet draped over 3D nanospheres exhibits a wide linear concentration range of 100–30800 nM with a low detection limit of 20.98 nM. Further investigation of the real-time performance on human saliva and DA injections afforded prominent results. In addition, the synergetic effect of G-CeONS improves DA detection accuracy and reliability towards enabling transformational neurochemical and medicinal applications.
1. Introduction
There is a new generation of bio-medical applications focusing on developing rapid, easy-to-use, and low-cost methods to detect and quantify complex biological compounds.1,2 Human bodies comprise numerous complex chemicals to maintain and monitor the proper functions of all bodily organs.3,4 Among those complex compounds, neurotransmitters play an active role in maintaining and preserving normal brain function,5,6 specifically, the neurotransmitter dopamine (DA), known as the happy hormone, which belongs to the amine family of complex compounds. They help our brains’ significant functions, such as memory, emotions, and other neurological reactions, but slight variations or abnormalities in these levels result in various bodily disorders and significant health problems, such as depression, anxiety, and bipolar disorder, and in severe cases cause Parkinson's, Alzheimer's, and schizophrenia.7–11 By monitoring the levels of neurotransmitters, scientists and medical professionals can determine the required medication and treatments.12,13
Traditionally, several methods have been used to measure DA levels in the human body, but in vivo or in vitro studies often require long sample preparation methods as well as expensive instruments for analyses like fluorometry,14,15 high performance liquid chromatography (HPLC),16,17 colorimetric methods,18–20 capillary electrophoresis,21,22 and ultraviolet-visible spectrophotometry.23,24 Subsequently, the development of a new generation of detection methods is driving scientific communities to focus on enzymatic or non-enzymatic electrochemical detection of DA.25–27 However, enzymatic sensors of DA suffer from a few setbacks, such as humidity, temperature dependence, and presence of other chemicals in the system.28 Therefore, the development of non-enzymatic electrochemical detection of DA has attracted attention due to its rapid, easy-to-use, selective, and sensitive detection using low-cost materials or easy-to-make nanocomposites.29
For the past several decades, the development of metal-oxide-based electrochemical detectors has gained much importance, owing to their unique high electronegativity and good biocompatibility. Xia et al.30 prepared zinc oxide (ZnO) nanochains for the detection of DA with a detection limit of 60 nM. Emran et al.31 synthesized flower-like nickel oxide (NiO) for DA detection with a detection limit of 85 nM. Sundar et al.32 fabricated a copper oxide (CuO) based detector with a detection limit of 100 nM, and Krishnamoorthy et al.33 developed CuO nano-rice for a DA sensor with a detection limit of 420 nM. However, these reported materials have low selectivity towards the detection of DA levels in the presence of other complex biological molecules, namely uric acid (UA) and ascorbic acid (AA).34–36
Among rare earth metals, cerium-based oxides (CeO2) have attracted specific interest due to their face cubic structure with superior catalytic activity as the result of their oxygen vacancies.37,38 In recent years, CeO2 has attracted significant attention in numerous scientific fields due to its high iso-electric point,39 biocompatibility,39,40 inertness, and non-toxic nature,41 allowing its significant use in low-temperature oxidation,42,43 fuel cells,44,45 electrode materials for supercapacitors,46 reductions of aromatic nitrates,47 photocatalysts in dye decomposition,48 UV filters,49 and oxygen sensors.50
CeO2 nanomaterials have been employed in various types of biomolecule electrochemical detection because of their advantages, such as oxidase-active nanozymes,51 organo-pesticide decontaminant,52 anti-inflammatory capabilities,53,54 and oxidative stress properties.55 Furthermore, the electrocatalytic properties of CeO2 are enhanced because of its Ce3+ and Ce4+ stable redox behavior.56,57 Despite these advantages, the low electrical conductivity of CeO2 is considered a crucial issue that limits its applicability for low levels of biologically complex compounds. To overcome this insignificance level, a new generation of nanohybrid heterostructure nanocomposites have been constructed with high electrical conductivity.
Since 2004, the focus of scientific communities has been directed towards carbon nanomaterials due to their planar structures with hexagonal lattices.58 The ability to modify the graphene structure expanded their uses in the field of electrocatalytic applications.59 In recent years, graphene and graphene-based composites have been significantly utilized in the development of new DA detectors, due to their strong mechanical and electrical properties with large specific surface area, thermal stability, and chemical resistance.60,61 Among graphene-based composites, graphene oxide (GO) has a specific hydrophilicity, multiple oxygen molecules, and controllable electronic properties than conventional graphene materials.62,63 Additionally, its increased interfacial wettability delivers binding sites for interfacial engineering due to the abundant functional groups.64
There is a need for new hybrid materials with better conductivity and larger surface area. Our research successfully constructed a nanohybrid heterostructure consisting of two-dimensional (2D) paper-like graphene oxide (GO) and three-dimensional (3D) cerium oxide nanospheres (CeONS) via stoichiometric synthesis. The developed nanohybrid nanocomposite of GO and CeONS (G-CeONS) showed improved electrocatalytic activity, high selectivity, and sensitivity through interfacial bonding towards DA detection in the presence of other complex biological compounds. The synergetic effect of CeONS and GO offers a low background-current sensor with high conductivity and larger specific surface area of electroactivity, which greatly increases the amperometric detection of DA in real-time applications. Moreover, the prepared G-CeONS nanohybrid composite was used to detect real-time applications for human saliva and DA injections, showing the significant reliability of the developed G-CeONS sensor in biological applications.
2. Experimental section
2.1. Materials used
Cerium(III) nitrate hexahydrate (Ce(NO3)3·6H2O, 99%), sodium hydroxide (NaOH), hydrochloric acid (HCl, 36.5–38.0%), monosodium phosphate (NaH2PO4, 98%), disodium phosphate (Na2HPO4, 99%), potassium chloride (KCl, 99.0–100.5%), potassium ferricyanide (K3[Fe(CN)6]), potassium ferrocyanide (K4[Fe(CN)6]), and dopamine hydrochloride (DA) were acquired from Sigma-Aldrich and used for analysis without additional purification. 0.1 M phosphate buffer solution (PBS) was used as an electrolyte, which was prepared by utilizing 0.1 M NaH2PO4 and Na2HPO4 dissolved in de-ionized water (DI water). NaOH and HCl were used to adjust the pH of the electrolyte. DI water was used for analyte preparation without any further purification methods. All electrochemical studies were carried out in an ambient temperature with 0.1 M PBS, and electrochemical kinetics studies were carried out in 0.1 M KCl containing 5 mM [Fe(CN)6]3−/4− (FCS).
2.2. Material preparation
2.2.1. Co-precipitation synthesis of CeO2. To develop the 3D CeO2 nanospheres (CeONS), 21.706 g of Ce(NO3)3 and 0.4 g of NaOH were dissolved in 100 mL of DI water. The second solution was added dropwise into the first solution under vigorous stirring (rpm ∼ 1200) for 30 min. After precipitate formation, stirring was continued for a further 30 min. Then, the solution was centrifuged and washed with water and ethanol for three consecutive cycles to eliminate unreacted precursors. The precipitate was then dried at ambient temperature in a vacuum oven to avoid any contamination. The well-dried precipitate was then crushed and ground using a quartz crystal mortar and pestle to make a fine powder for further material characterization and for all experiments without any further purification.
2.2.2. Stoichiometric synthesis of G-CeONS composite. 2D paper-like graphene oxide (GO) layers previously prepared by a modified Hummers’ method65 and as-prepared CeONS were dispersed in DI water with a 1:1 ratio under ambient temperature magnetic stirring with varying time intervals: 1, 6, 12, 18, and 24 hour. All the magnetically stirred composites were subjected to scanning electron microscope (SEM) analysis to observe the uniform layer of paper-like GO draped on the CeONS (Fig. S1, ESI†). The composite with 24 h (Fig. 1(a)) of stirring shows a better draping effect on the CeONS; it was later used for all the characterization studies and used as an electrode-modifying material on a glassy carbon electrode (GCE) surface to detect DA. The overall G-CeONS composite preparation methodology is shown in Scheme 1.
|
| Fig. 1 Scanning electron microscopy (SEM) images of G-CeONS (a), elemental mapping survey of G-CeONS (b), cerium distribution (blue) (c), carbon distribution (red) (d), and oxygen distribution (green) (e). | |
|
| Scheme 1 Schematic illustration of stoichiometric preparation of G-CeONS and electrochemical detection of DA. | |
2.3. Electrode fabrication
Alumina slurry (50 nm) was used to polish the GCE surface and washed using DI water. Then, 8 μL of a homogenous dispersed solution of G-CeONS was coated on the GCE specific surface by drop casting and allowed to dry at room temperature for further electrochemical studies. To compare the performances for DA detection, CeONS/GCE and GO/GCE were constructed following the same process.
2.4. Materials characterization
The elemental analysis and morphology of the nanocomposite were examined with a scanning electron microscope (SEM) from NOVA, NANO SEM 450, a field-emission scanning electron microscope (Fe-SEM) from Hitachi S-4800 with an energy dispersive X-ray spectrometer (EDS) QUANTAX Annular XFlash® QUAD FQ5060, and a high-resolution transmission electron microscope (HR-TEM) from JEOL JEM-2100F. Structural analysis was performed by X-ray diffraction (XRD) using a PANalytical X’Pert Pro with Cu-kα (λ = 1.543 Å) as the radiation source. X-ray photoelectron spectroscopy (XPS) was conducted using a Thermo Scientific Multi-Lab 2000 to confirm the existence of the elements and the output of the substance. All electrochemical studies used a three-electrode system comprising a working electrode (glassy carbon electrode (GCE)) with specific surface area of 0.07 cm2, which was later modified with the prepared nanocomposite, an Ag/AgCl electrode as a reference electrode with standard potential of 0.197 V from ALS Co., Ltd, Japan, and platinum wire used as a counter electrode. Additionally, electron impedance spectroscopy (EIS) studies were carried out using a Squidstat™ Plus from Admiral Instruments, USA in the frequency range 0.1–10 KHz. A CHI-1205C Potentiostat workstation from CH Instruments, USA, was used for all the electrochemical studies, and an analytical rotator AFMSRX from PINE instruments, USA, was used for amperometric measurements.
3. Results and discussion
3.1. Morphological analysis
The prepared spherical CeO2 with an average particle size of 476 nm (Fig. S1, ESI†) was used to develop nanohybrid G-CeONS composites, and their surface morphology was investigated using Fe-SEM. Fig. 1(a) reveals a layered paper-like elongated structure covering CeONS, which confirms G-CeONS heterostructure formation. The approach of utilizing a magnetic stirrer for stoichiometric preparation offered interfacial bonding between CeONS and the GO nanolayer in 24 h. A gradual increase in the stirring time offered a draping effect through interfacial surface bonding, while a shorter time reveals random scattering of CeONS on wrinkled GO structures. Fig. S2 (ESI†) shows the various time intervals used to prepare G-CeONS composites. As presented in Fig. 1(a), the draped GO prevents further agglomeration in CeONS structures. Fig. 1(b) presents the elemental mapping survey of G-CeONS composite with uniform distributions of cerium (Ce) (Fig. 1(c)), carbon (C) (Fig. 1(d)), and oxygen (O) (Fig. 1(e)), which confirms the presence of a paper-like GO layer on CeONS. These results show that the constructed G-CeONS was hierarchically interconnected with high electrocatalytic activity.
To further confirm the nanohybrid formation of a GO layer draped over CeO2 nano-spherical structures, TEM analysis was carried out (Fig. 2(a)). Furthermore, Fig. 2(b) shows an enlarged view of the spherical structures of CeONS with a paper-like GO layer. The elemental mapping of Ce (Fig. 2(c)), O (Fig. 2(d)), and C (Fig. 2(e)) reveals the presence of the GO layer and confirms its uniform draping over CeONS. Fig. 2(f) provides the EDS spectra of G-CeONS, confirming the homogenous distribution of Ce, C, and O elements in the composite structure. The successful heterostructure formation of G-CeONS was confirmed by these Fe-SEM and TEM findings. These results also prove the better charging transfer capability of the developed G-CeONS to be efficient due to the uniform and well-draped structures. As a functional material for the detection of DA, such a nanohybrid G-CeONS composite support with larger surface area promises excellent potential.
|
| Fig. 2 Transmission electron microscopy (TEM) images of G-CeONS (a), magnified view of CeONS (scale bar, 200 nm) (b), elemental mapping of cerium distribution (red) (c), oxygen distribution (green) (d), carbon distribution (teal) (e), and EDS spectra of the surveyed region of G-CeONS (f) (scale bar, 250 nm). | |
XRD patterns of the developed G-CeONS are shown in Fig. 3, which were indexed using JCPDS card number 34-0394. The XRD patterns for as-prepared CeONS and GO nanolayer XRD patterns are presented in Fig. S3 (ESI†). Both results for CeONS confirm a face centered cubic (FCC) structure with lattice parameters α = β = γ = 90° and a = b = c = 5.411 Å. The diffraction peaks found at 28.43°, 32.95°, 47.36°, and 56.20° suggest the formation of nanosized CeONS. The diffraction peak at 10.91° confirms the successful draping of a paper-like GO layer on the CeONS surface. Synthesized CeONS and G-CeONS composites lack any other impurities, which highlights the significance of using co-precipitation and stoichiometric synthesis to form a nanocomposite. The average crystallite sizes (D) of G-CeONS and CeONS were calculated using the Scherrer equation,66 eqn (1):
|
| (1) |
where
K is a Scherrer constant (0.9),
β is the full-width at half maximum (FWHM),
λ is the wavelength of the Cu-Kα radiation, and
θ is the diffraction angle. The average crystallite size of the as-prepared CeONS is 9.34 nm, which is lower than that previously reported for CeO
2 prepared by a different method, which signifies the importance of using the room-temperature co-precipitation method.
67,68 Draping 2D GO nanolayers onto CeONS further decreases the average crystallite size (8.89 nm), which highlights the formation of interfacial bonding in G-CeONS, which proves to be more efficient at producing nanosized composites
via stoichiometric synthesis.
|
| Fig. 3 X-ray diffraction (XRD) pattern of G-CeONS. | |
The surface chemical states of the heterostructure G-CeONS were studied using XPS, as presented in Fig. 4. A survey scan reveals the presence of Ce 3d, C 1s, and O 1s in the G-CeONS composite (Fig. 4(a)) with atomic percentages of 18.35%, 37.86%, and 43.79%, respectively. The Ce 3d spectrum of G-CeONS was fitted to eight peaks: Ce 3d3/2 peaks at 924.78, 914.96, and 908.91; Ce 3d5/2 peaks at 905.89, 899.89, and 890.28 eV, which are associated with Ce4+; and peaks at 912.40 eV (Ce 3d3/2) and 896.26 eV (Ce 3d5/2) associated with Ce3+, as shown in Fig. 4(b). These findings are consistent with the literature.68,69 In the G-CeONS composite, peaks in the C 1s spectrum (Fig. 4(c)) at 291.80, 293.38, 294.26, and 295.58 eV are ascribed to CC, C–O bonds, CO (carbonyl), and O–CO (carboxyl) bonds, respectively. The deconvolution of the O 1s spectrum displayed in Fig. 4(d) presents two peaks at 539.09 and 540.07 eV, which are attributed to the lattice and adsorbed oxygen. The results show the presence of a GO nanolayer on the CeONS.
|
| Fig. 4 X-ray photoelectron spectroscopy (XPS) spectrum of G-CeONS: survey spectrum with atomic % (inset) (a), deconvoluted plots of Ce 3d spectrum (b), carbon 1s spectrum (c), O 1s spectrum (d). | |
3.2. Electrochemical investigations using G-CeONS
3.2.1. Electrochemical impedance spectroscopy (EIS) studies. EIS findings were used to evaluate the surface properties of the electrode and the kinetics of electron transfer for different modified electrodes such as bare GCE, GO/GCE, CeONS/GCE, and G-CeONS/GCE. EIS determines the electron charge transfer properties of these modified electrodes based on the charge transfer resistance (Rct), Warburg impedance (Zw), double layer capacitance (Cdl), and solution resistance (Rs) between the interfaces of electrolyte and electrode. Fig. 5 represents the Nyquist plot of the modified electrodes in the supporting electrolyte FCS at an amplitude of 10 mV with the applied frequency range (0.1 Hz to 10 KHz). EIS data are fitted with the Randles equivalent circuit model, and the corresponding diagram is shown in the inset of Fig. 5. The calculated Rct values were obtained as follows: 1163.82 Ω for bare GCE, 870.35 Ω for GO/GCE, 455.69 Ω for CeONS/GCE, and 347.69 Ω for G-CeONS/GCE. Based on these results, the low Rct of G-CeONS/GCE confirms its low resistance and high conductivity compared with the other modified and bare electrodes. Notably, there is a consistent decrease in Rct values with each modification. This implies that there is efficient enhancement of electron transfer at the interface between the electrode and electrolyte. Furthermore, a charge transfer rate (Ks) can be determined by applying Rct values, using eqn (2):70 |
| (2) |
where R is the universal gas constant (8.314 J mol−1 K−1), T is the temperature of the reaction, n is the number of electrons transferred in the reaction, F is Faraday's constant (96485 C mol−1), and C represents the concentration of the redox couple. Using this equation, the Ks values were calculated as follows: 4.57 × 10−9, 6.12 × 10−9, 1.168 × 10−8, and 1.531 × 10−8 cm s−1 for bare GCE, GO/GCE, CeONS/GCE, and G-CeONS/GCE, respectively. Through the utilization of GO, there was an obvious increase in Ks compared with bare/GCE, suggesting a substantial improvement in electron conductivity. In addition, the inclusion of CeONS led to an additional increase in Ks, emphasizing the favorable impact of CeONS on the acceleration of electron transfer. The constructed G-CeONS electrode showed the highest Ks value, indicating enhanced electron transport due to the presence of GO and CeONS. These findings highlight the significance of surface modification in maximizing electrode performance for the non-enzymatic detection of DA.
|
| Fig. 5 The Nyquist plot of bare GCE (black), GO/GCE (brown), CeONS/GCE (green), and G-CeONS/GCE (red) in FCS electrolyte at frequencies from 0.1 Hz to 10 kHz. | |
3.2.2. Electrochemical kinetics of G-CeONS. The cyclic voltammetry (CV) responses of bare GCE, GO/GCE, CeONS/GCE, and G-CeONS/GCE in FCS at a scan rate of 50 mV s−1 are presented in Fig. 6. From these responses, G-CeONS/GCE shows a smaller redox peak separation (ΔEp) of 112 mV with a greater current response than bare GCE (240 mV), GO/GCE (145 mV), and CeONS/GCE (125 mV). These results coincide with the EIS results. The lowest ΔEp values are attributed to the paper-like GO layers uniformly draped on CeONS with π–π interactions, which actively increases the electrocatalytic activity and accelerates electron transfer kinetics at G-CeONS/GCE. In addition, G-CeONS/GCE exhibited the highest peak current ratio (Ipa/Ipc) of 0.99: bare GCE 0.88, GO/GCE 0.97, and CeONS/GCE 0.98. The G-CeONS electrodes exhibit a peak current ratio of nearly 1, indicating the reversible nature of the reaction in FCS. Additionally, to evaluate the surface area, which is electrochemically active for all the modified electrodes, individual FCS was utilized with varying scan rates from 20 to 200 mV s−1 with intervals of 20 mV s−1, as shown in Fig. S4 (ESI†). The linear increase in the redox peak current towards negative and positive potential proves the increased surface area of the electrodes. The charge diffusion polarization facilitates the increase in peak current in G-CeONS/GCE. The electrochemically active surface areas of bare GCE, GO/GCE, CeONS/GCE, and G-CeONS/GCE were determined by utilizing the Randles–Ševčík equation,69 eqn (3): |
Ip = 2.69 × 105n3/2AD1/2Cν1/2
| (3) |
|
| Fig. 6 The cyclic voltammetry (CV) responses recorded for bare GCE (black), GO/GCE (brown), CeONS/GCE (green), and G-CeONS/GCE (red) in FCS at a scan rate of 50 mV s−1. | |
Fig. S4 (ESI†) presents the CV responses and the linear plot of Ipa vs. ν1/2 of bare GCE, GO/GCE, CeONS/GCE, and G-CeONS/GCE in FCS by varying the scan rates from 20 to 200 mV s−1 with 20 mV s−1 intervals. The electrochemically active surface areas were determined to be 0.07, 0.12, 0.14, and 0.17 cm2 for bare GCE, GO/GCE, CeONS/GCE, and G-CeONS/GCE, respectively. The higher surface area of G-CeONS/GCE indicates the presence of more electrocatalytically active sites than those on bare GCE. Thus, G-CeONS/GCE can be efficiently used for the determination of DA concentrations because of its larger surface area with better electrocatalytic performance.
3.2.3. Effect of pH on dopamine detection. The effect of varying pH (from 3 to 11) was tested using 0.1 M PBS at a scan rate of 50 mV s−1. CV data are presented in Fig. 7(a), which reveals that the current response of oxidation towards 50 μM of DA by G-CeONS/GCE increased with increasing pH from 3 to 7; meanwhile, a decrease in redox peak current was observed when increasing the pH above 7. The corresponding linear plots of pH vs. redox peak potential (blue) and oxidation current (red) are presented in Fig. 7(b). From these results, the highest anodic peak current of 1.71 μA was observed at PBS 7 with G-CeONS/GCE for 50 μM of DA. Accordingly, pH 7 PBS (PBS 7) was chosen as the electrolyte for further electrochemical measurements. The theoretical values of the Nernst equation are adjacent to the obtained slope value for DA (−69 mV). Eqn (4) shows the linear regression equation for pH vs. peak potential. |
y = −0.0698 (pH) + 0.7253 with R2 = 0.9979
| (4) |
|
| Fig. 7 CV responses of G-CeONS/GCE in varying pH from 3 to 11 (a), respective linear plots of pH vs. current (red) with pH vs. potential (blue) (b) in PBS 7 at a scan rate of 50 mV s−1. | |
To evaluate the electrochemical response of DA, different electrodes, such as bare GCE, GO/GCE, CeONS/GCE, and G-CeONS/GCE, were used in PBS 7 with a scan rate of 50 mV s−1, as presented in Fig. S5 (ESI†). From the results, G-CeONS/GCE shows a 10-fold higher oxidation peak current than bare GCE (0.1909 μA), whereas GO/GCE shows a 7.060-fold higher value and CeONS/GCE shows a 7.803-fold higher value than bare GCE. This significantly proves the best and most effective electron transfer in G-CeONS/GCE. The mechanism of electrochemical oxidation of DA in the presence of G-CeONS/GCE is given in Scheme 2. Fig. S5 (ESI†) shows the reversible reaction of DA oxidizing into DA quinone at the applied potential.71
|
| Scheme 2 Electrochemical reaction mechanism of DA in the presence of G-CeONS/GCE. | |
The effect of increasing the DA concentration from 10 to 100 μM with intervals of 10 μM in PBS 7 at a scan rate of 50 mV s−1 is shown in Fig. 8(a). Significantly, the redox peak current increased with increasing concentration of DA. Fig. 8(b) presents the linear plot of oxidation peak current vs. DA concentration, which has a correlation coefficient of R2 = 0.9974. Thus, G-CeONS/GCE is an exceptional electrode for the detection of DA. Fig. S6(a) (ESI†) shows that the CV response of the oxidation peak current of G-CeONS/GCE increased when the scan rate of the system increased from 20 to 180 mV s−1 with 20 mV s−1 intervals. The linear correlation plot in Fig. S6(b) (ESI†) shows better linearity with (scan rate)1/2 vs. oxidation peak current with a correlation coefficient of R2 = 0.9953, which confirms the diffusion-controlled electrocatalytic process.
|
| Fig. 8 CV responses obtained using G-CeONS/GCE in the presence of DA concentrations from 10 to 100 μM in PBS 7 at a scan rate of 50 mV s−1 (a); the corresponding linear plot of DA (μM) vs. current (μA) (b). | |
3.2.4. Amperometric i–t detection of DA. We employed the amperometric i–t (i–t) technique to determine the high sensitivity and lower detection limit for DA. Fig. 9 represents the i–t data for the detection of DA against a G-CeONS-modified rotating glassy carbon electrode (G-CeONS/RDGCE) in PBS 7 at intervals of 50 s with a rotation of 1200 rpm (initial potential (Eapp) = 0.165 V). This proves that the addition of DA (from 0.1 μM to 30.8 μM) into PBS 7 plays an important role in the current response, which gradually improved with increasing DA concentration in the electrolyte solution. These results further confirm the accelerated electrocatalytic oxidation towards DA by G-CeONS/RDGCE. Fig. 10(a) represents a steady and linear response to a periodic increase in DA concentration, where the linear range is presented from 0.1 μM to 30.8 μM with a correlation coefficient of R2 = 0.9994. The constructed G-CeONS sensor has an ultra-low limit of detection (LOD) of 20.98 nM, with a sensitivity of 0.1986 μA μM−1 cm−2. The LOD was calculated using eqn (5): |
| (5) |
where σ is the standard deviation of blank signals in the absence of DA, and S is the slope value of a linear plot of different concentration vs. current responses of DA in the presence of G-CeONS. Eqn (6) shows the linear regression equation: |
Ipa (μA) = 0.0143 (μM) + 0.0227 μA
| (6) |
|
| Fig. 9 Amperometric i–t response of G-CeONS/RDGCE for each addition of DA into PBS 7 at a rotation speed of 1200 rpm. The inset shows a magnified view of the low-concentration additions of DA. | |
|
| Fig. 10 Amperometric i–t response corresponding to linear plot of DA concentration (μM) vs. current (μA) in PBS 7 (a). Anti-interference response of G-CeONS/RDGCE towards 5 μM of DA in the presence of other interfering complex biological compounds in PBS 7 (b). | |
Table 1 shows a comparison of observed analytical parameters of linear range and LOD with previously reported DA sensors, which confirms that the constructed G-CeONS sensor possesses greater efficiency towards DA detection in real-time applications or in bio-medical devices.
Table 1 Comparison of the linear range and LOD between previously reported electrodes for DA detection
Material |
Electrode |
Method |
LOD (μM) |
Linear range (μM) |
Ref. |
Carbon quantum dots. Copper oxide. Polydopamine. Cerium oxide. Tungsten diselenide. Palladium. Reduced graphene oxide. Gold. Porous silicon-poly(3-hexylthiophene). Polyaniline/thermally reduced graphene oxides. Zinc oxide. Molecularly imprinted/4-mercaptophenylboronic acid/gold nanoparticles. Porous reduced graphene oxide. Metal organic framework-titanium carbide. Lanthanum metal organic framework/carbon nanotube. Fcmc/nickel–palladium/functionalized-multiwall carbon nanotubes. Defect-palladium molybdenum metallene. |
CQDa/CuOb |
GCE |
SWV |
25.4 |
10–80 |
72 |
PDAc@CeO2d |
GCE |
DPV |
8.37 |
10–200 |
73 |
WSe2e |
PE |
CV |
5 |
5–100 |
74 |
CeO2d |
GCE |
DPV |
3.2 |
10–300 |
75 |
Pdf-CeO2d/rGOg |
GCE |
DPV |
0.69 |
5–240 |
76 |
Auh@PSi-P3HTi |
GCE |
i–t |
0.63 |
1–460 |
77 |
PANI/TRGO-700j |
GCE |
DPV |
0.43 |
0.8–20 |
78 |
ZnOk–CeO2d |
GCE |
DPV |
0.39 |
5–800 |
79 |
MIP/4-MPBA/AuNPsl |
ANE |
DPV |
0.14 |
0.5–1000 |
80 |
p-rGOm |
ITO |
DPV |
0.12 |
0–40 |
81 |
MOF-Ti3C2n |
GCE |
DPV |
0.11 |
0.09–0.13 |
82 |
La-BTC/CNTo |
GCE |
CV |
0.073 |
10–100 |
83 |
Fcmc/Ni-Pd/f-MWCNTp |
CPE |
i–t |
0.05 |
2–400 |
84 |
D-PdMoq |
GCE |
DPV |
0.029 |
0.05–100 |
85 |
G-CeONS |
GCE |
i–t |
0.021 |
1–30.8 |
Present work |
3.2.5. Investigation of selectivity, anti-interference, stability, and reproducibility of G-CeONS towards DA. The selectivity of the constructed G-CeONS sensor is vital for the real-time detection of DA due to interfering coexisting compounds. Thus, we examined interfering compounds, such as glucose, UA, AA, hydrogen peroxide (H2O2), serotonin, tyramine, histamine, and tyrosine, in the presence of DA in PBS 7 electrolyte using the i–t technique. Fig. 10(b) shows the i–t response of G-CeONS/RDGCE to two additions of 5 μM of DA at the beginning; then to 50 μM of glucose, AA, UA, H2O2, serotonin, tyramine, histamine, and tyrosine each added in periodic time intervals; and then to two more additions of 5 μM of DA included in the electrolyte at 50 s intervals. It is evident that the addition of interfering materials has no significant effect on the current response of G-CeONS towards DA detection. Furthermore, the proposed G-CeONS electrode was tested with multiple analytes such as DA, methyl parathion (MP), bisphenol A (BA), hydroquinone (HQ), 4-nitrophenol (4-NP), 4-nitrotoluene (4-NL), cadmium ions (Cd), lead ions (Pb), mercury ions (Hg), and carbendazim (CBZ) in PBS 7 at a scan rate of 50 mV s−1 to confirm the positive and negative control effects of G-CeONS/GCE (Fig. S7, ESI†).The as-prepared G-CeONS sensor was examined for operational stability, where two additions of 5 μM of DA in 50 s intervals were made to observe and record the stable response over a long time of operation (4000 s). The results revealed no additional current response or loss in the produced current in the electrolyte solution (Fig. 11(a)). Furthermore, a nanohybrid G-CeONS sensor was assessed on a day-to-day basis to detect its wearing ability. It maintained 99.95% of its initial response even after 60 d of using the same sensor (Fig. 11(b)). To explore the reproducibility and repeatability of the nanohybrid G-CeONS sensor, the CV method was utilized in PBS 7 with 50 μM of DA. Reproducibility was investigated in the fabrication of 5 individual G-CeONS/GCE (Fig. 11(c)), relative standard deviation = 0.08%. Similarly, repeatability was investigated by employing the same G-CeONS/GCE for five consecutive different measurements (Fig. 11(d)), relative standard deviation = 0.06%. The outcomes highlight the reliability and robustness of the nanohybrid G-CeONS sensor, signifying it as a promising heterostructure nanocomposite for selective and sensitive DA detection in real-time applications.
|
| Fig. 11 Operational stability of the prepared G-CeONS sensor over 4000 s at 1200 rpm in PBS 7 (a). Storage stability of the nanohybrid G-CeONS over 60-d usage in PBS 7 at a scan rate of 50 mV s−1 (b). CV responses plot for five G-CeONS/GCE electrodes in the presence of DA in PBS 7 (c). CV responses plot for five different runs in the presence of DA in PBS 7 (d). | |
3.2.6. Real sample analysis. As biological compounds with numerous interfering chemicals exist in real samples from our biological systems, developing practical applications of a nanohybrid G-CeONS sensor is greatly challenging. To exploit the performance of DA hydrochloride injections and the G-CeONS sensor for the real-time detection of DA in human saliva, we utilized PBS 7 with the standard addition of human saliva. Furthermore, DA injections were spiked into PBS 7, and the results were recorded. The percentage of accuracy and recovery are tabulated in Table 2. These values were calculated using eqn (7): |
| (7) |
where R is the experimental value obtained, and E is the real amount of spiked sample.
Table 2 Detection of DA using the G-CeONS sensor in real-time applications
Real sample |
Spiked (μM) |
Found (μM) |
Recovery (%) |
RSD (%) |
Human saliva |
5 |
4.97 |
99.4 |
0.27 |
10 |
9.96 |
99.6 |
0.31 |
15 |
14.94 |
99.6 |
0.23 |
20 |
19.96 |
99.8 |
0.28 |
|
DA injections |
5 |
4.98 |
99.6 |
0.24 |
10 |
9.94 |
99.4 |
0.30 |
15 |
14.97 |
99.8 |
0.28 |
20 |
19.96 |
99.8 |
0.30 |
Table 2 demonstrates that the constructed G-CeONS sensor exhibits consistently low relative standard deviations in the recovery percentages of spiked real samples, affirming its efficacy in detecting dopamine (DA) in biological samples. Additionally, the sensor demonstrates high accuracy in detecting DA in complex human saliva samples, further validating its suitability for practical applications in biological sample analysis.
4. Conclusions
In this study, a non-enzymatic electrochemical sensor was developed based on a nanohybrid G-CeONS nanocomposite modified electrode for dopamine detection. A GO nanolayer draped on a CeONS nanocomposite heterostructure was fabricated using a facile and cost-effective stoichiometric magnetic stirring method through interfacial surface bonding. This offered an impurity-free composite to investigate for DA detection using CV and i–t techniques. The nanohybrid G-CeONS showed greater electrocatalytic activity for DA detection with a wide linear range of 100–30800 nM, low LOD of 20.98 nM, and sensitivity of 0.1986 μA μM−1 cm−2. The prepared sensors showed substantial recovery percentages for real-time sample analysis. They also fulfilled the expectation of overcoming the limitations of traditional methods because of their advantages, such as excellent selectivity, sensitivity, fast response, and cost-effectiveness. Comprehensive studies of the structural, morphological, and electrical performances of nanohybrid G-CeONS offer new insights into the non-enzymatic detection of DA sensing.
Data availability
The data supporting this article has been included as part of the ESI.†
Conflicts of interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
Shen-Ming Chen acknowledges the financial support provided by the National Science and Technology Council of Taiwan (NSTC 113-2113-M-027-003). C. R. Kao acknowledges the financial support provided by the National Science and Technology Council, Taiwan (NSTC 113-2223-E-002-003).
References
- B. Roszek, W. H. De Jong and R. E. Geertsma, Nanotechnology in medical applications: state-of-the-art in materials and devices, RIVM report, 2005, 265001001 Search PubMed .
- G. V. Angelov, D. P. Nikolakov, I. N. Ruskova, E. E. Gieva and M. L. Spasova, Enhanced Living Environments: Algorithms, Architectures, Platforms, and Systems, Springer, 2019, pp. 226–262 Search PubMed .
- J. Angerer, U. Ewers and M. Wilhelm, Int. J. Hyg. Environ. Health, 2007, 210, 201–228 CrossRef CAS PubMed .
- J. McDowell, Encyclopedia of Human Body Systems [2 volumes]:[2 volumes], Bloomsbury Publishing USA, 2010 Search PubMed .
- H. J. Reis, C. Guatimosim, M. Paquet, M. Santos, F. M. Ribeiro, A. Kummer, G. Schenatto, J. V. Salgado, L. B. Vieira and A. L. Teixeira, Curr. Med. Chem., 2009, 16, 796–840 CrossRef CAS PubMed .
- E. Başar and B. Güntekin, Brain Res., 2008, 1235, 172–193 CrossRef .
- M. O. Klein, D. S. Battagello, A. R. Cardoso, D. N. Hauser, J. C. Bittencourt and R. G. Correa, Cell. Mol. Neurobiol., 2019, 39, 31–59 CrossRef .
- S. Latif, M. Jahangeer, D. M. Razia, M. Ashiq, A. Ghaffar, M. Akram, A. El Allam, A. Bouyahya, L. Garipova and M. A. Shariati, Clin. Chim. Acta, 2021, 522, 114–126 CrossRef CAS .
- M. Jaber, S. W. Robinson, C. Missale and M. G. Caron, Neuropharmacology, 1996, 35, 1503–1519 CrossRef CAS PubMed .
- K. H. Wang, A. Penmatsa and E. Gouaux, Nature, 2015, 521, 322–327 CrossRef CAS PubMed .
- D. Vallone, R. Picetti and E. Borrelli, Neurosci. Biobehav. Rev., 2000, 24, 125–132 CrossRef CAS .
- M. Husain and M. A. Mehta, Trends Cognit. Sci., 2011, 15, 28–36 CrossRef CAS PubMed .
- J. S. Kooij, Adult ADHD: Diagnostic assessment and treatment, Springer Science & Business Media, 2012 Search PubMed .
- J. F. Van Staden and R. I. S. van Staden, Talanta, 2012, 102, 34–43 CrossRef CAS .
- Y. Tao, Y. Lin, J. Ren and X. Qu, Biosens. Bioelectron., 2013, 42, 41–46 CrossRef CAS .
- K. E. Hubbard, A. Wells, T. S. Owens, M. Tagen, C. H. Fraga and C. F. Stewart, Biomed. Chromatogr., 2010, 24, 626–631 CrossRef CAS PubMed .
- M. E. Hows, L. Lacroix, C. Heidbreder, A. J. Organ and A. J. Shah, J. Neurosci. Methods, 2004, 138, 123–132 CrossRef CAS PubMed .
- H. Su, B. Sun, L. Chen, Z. Xu and S. Ai, Anal. Methods, 2012, 4, 3981–3986 RSC .
- D. Wen, W. Liu, A.-K. Herrmann, D. Haubold, M. Holzschuh, F. Simon and A. Eychmüller, Small, 2016, 12, 2439–2442 CrossRef CAS PubMed .
- P. S. Teo, P. Rameshkumar, A. Pandikumar, Z.-T. Jiang, M. Altarawneh and N. M. Huang, Microchim. Acta, 2017, 184, 4125–4132 CrossRef CAS .
- T. M. Olefirowicz and A. G. Ewing, J. Neurosci. Methods, 1990, 34, 11–15 CrossRef CAS PubMed .
- Y. Zhao, S. Zhao, J. Huang and F. Ye, Talanta, 2011, 85, 2650–2654 CrossRef CAS PubMed .
- P. A. Rasheed and J.-S. Lee, Microchim. Acta, 2017, 184, 1239–1266 CrossRef .
- A. Jouyban and E. Rahimpour, Talanta, 2020, 217, 121071 CrossRef CAS .
- Z. Fredj, B. Singh, M. Bahri, P. Qin and M. Sawan, Chemosensors, 2023, 11, 388 CrossRef CAS .
- P. V. Romanholo, C. A. Razzino, P. A. Raymundo-Pereira, T. M. Prado, S. A. Machado and L. F. Sgobbi, Biosens. Bioelectron., 2021, 185, 113242 CrossRef CAS .
- Z. Yang, J. Guo, L. Wang, J. Zhang, L. Ding, H. Liu and X. Yu, Small, 2024, 20, 2307815 CrossRef CAS PubMed .
- N. Thakur, D. Gupta, D. Mandal and T. C. Nagaiah, Chem. Commun., 2021, 57, 13084–13113 RSC .
- M. Sajid, N. Baig and K. Alhooshani, TrAC, Trends Anal. Chem., 2019, 118, 368–385 CrossRef CAS .
- C. Xia, N. Wang, L. Wang and L. Guo, Sens. Actuators, B, 2010, 147, 629–634 CrossRef CAS .
- M. Y. Emran, M. A. Shenashen, M. Mekawy, A. M. Azzam, N. Akhtar, H. Gomaa, M. M. Selim, A. Faheem and S. A. El-Safty, Sens. Actuators, B, 2018, 259, 114–124 CrossRef CAS .
- S. Sundar, G. Venkatachalam and S. J. Kwon, Nanomaterials, 2018, 8, 823 CrossRef PubMed .
- K. Krishnamoorthy, V. Sudha, S. M. S. Kumar and R. Thangamuthu, J. Alloys Compd., 2018, 748, 338–347 CrossRef CAS .
- S. Lakard, I.-A. Pavel and B. Lakard, Biosensors, 2021, 11, 179 CrossRef CAS PubMed .
- K. Jackowska and P. Krysinski, Anal. Bioanal. Chem., 2013, 405, 3753–3771 CrossRef CAS PubMed .
- X. Liu and J. Liu, View, 2021, 2, 20200102 CrossRef .
- T. Wu, R.-t Guo, C.-f Li and W.-g Pan, J. Environ. Chem. Eng., 2023, 11, 109136 CrossRef CAS .
- P. Wang, F. Wang, Q. Liu, Y. Zhang, S. Le and C. Zhu, J. Rare Earths, 2024 DOI:10.1016/j.jre.2024.03.022 .
- V. Sarnatskaya, Y. Shlapa, D. Kolesnik, O. Lykhova, D. O. Klymchuk, S. O. Solopan, S. Lyubchyk, I. Golovynska, J. Qu and Y. Stepanov, Biomater. Sci., 2024, 12(10), 2689–2704 RSC .
- A. Dhall and W. Self, Antioxidants, 2018, 7, 97 Search PubMed .
- M. S. Lord, J. F. Berret, S. Singh, A. Vinu and A. S. Karakoti, Small, 2021, 17, 2102342 CrossRef CAS .
- A. Boronin, E. Slavinskaya, I. Danilova, R. Gulyaev, Y. I. Amosov, P. Kuznetsov, I. Polukhina, S. Koscheev, V. Zaikovskii and A. Noskov, Catal. Today, 2009, 144, 201–211 CrossRef CAS .
- L.-Y. Lin, C. Wang and H. Bai, Chem. Eng. J., 2015, 264, 835–844 CrossRef CAS .
- M. Breitwieser, C. Klose, A. Hartmann, A. Büchler, M. Klingele, S. Vierrath, R. Zengerle and S. Thiele, Adv. Energy Mater., 2017, 7, 1602100 CrossRef .
- H. Oh, B. Son and S. Shanmugam, ACS Appl. Mater. Interfaces, 2023, 15, 28093–28105 CrossRef CAS PubMed .
- N. Maheswari and G. Muralidharan, Energy Fuels, 2015, 29, 8246–8253 CrossRef CAS .
- C.-H. Wang and S.-S. Lin, Appl. Catal., A, 2004, 268, 227–233 CrossRef CAS .
- S. Sehar, I. Naz, A. Rehman, W. Sun, S. S. Alhewairini, M. N. Zahid and A. Younis, Appl. Organomet. Chem., 2021, 35, e6069 CrossRef CAS .
- A. Miri, H. Beiki, A. Najafidoust, M. Khatami and M. Sarani, Bioprocess Biosyst. Eng., 2021, 44, 1891–1899 CrossRef CAS .
- T. T. Phan, T. Tosa and Y. Majima, Sens. Actuators, B, 2021, 343, 130098 CrossRef CAS .
- A. D. Filippova, M. M. Sozarukova, A. E. Baranchikov, S. Y. Kottsov, K. A. Cherednichenko and V. K. Ivanov, Molecules, 2023, 28, 3811 CrossRef CAS .
- P. Janoš, J. Henych, O. Pelant, V. Pilařová, L. Vrtoch, M. Kormunda, K. Mazanec and V. Štengl, J. Hazard. Mater., 2016, 304, 259–268 CrossRef .
- S. M. Hirst, A. S. Karakoti, R. D. Tyler, N. Sriranganathan, S. Seal and C. M. Reilly, Small, 2009, 5, 2848–2856 CrossRef CAS .
- H. Nosrati, M. Heydari and M. Khodaei, Mater. Today Bio, 2023, 100823, DOI:10.1016/j.mtbio.2023.100823 .
- R. G. Daré, E. Kolanthai, C. J. Neal, Y. Fu, S. Seal, C. V. Nakamura and S. O. Lautenschlager, Antioxidants, 2023, 12, 190 CrossRef PubMed .
- S. Kim and Y. J. Sa, ACS Catal., 2024, 14, 6842–6855 CrossRef CAS .
- Q. Li, L. Song, Z. Liang, M. Sun, T. Wu, B. Huang, F. Luo, Y. Du and C.-H. Yan, Adv. Energy Sustainability Res., 2021, 2, 2000063 CrossRef CAS .
- M. Terrones, Annu. Rev. Mater. Res., 2003, 33, 419–501 CrossRef CAS .
- D. Higgins, P. Zamani, A. Yu and Z. Chen, Energy Environ. Sci., 2016, 9, 357–390 RSC .
- T. T. Tung, M. J. Nine, M. Krebsz, T. Pasinszki, C. J. Coghlan, D. N. Tran and D. Losic, Adv. Funct. Mater., 2017, 27, 1702891 CrossRef .
- A. Pandikumar, G. T. S. How, T. P. See, F. S. Omar, S. Jayabal, K. Z. Kamali, N. Yusoff, A. Jamil, R. Ramaraj and S. A. John, RSC Adv., 2014, 4, 63296–63323 RSC .
- H. Ahmad, M. Fan and D. Hui, Composites, Part B, 2018, 145, 270–280 CrossRef CAS .
- X. Huang, Z. Yin, S. Wu, X. Qi, Q. He, Q. Zhang, Q. Yan, F. Boey and H. Zhang, Small, 2011, 7, 1876–1902 CrossRef CAS PubMed .
- H. Li, S. Xue, Y. Shang, J. Li and X. Zeng, Adv. Mater. Interfaces, 2020, 7, 2000881 CrossRef CAS .
- J. Chen, B. Yao, C. Li and G. Shi, Carbon, 2013, 64, 225–229 CrossRef CAS .
- P. Scherrer, Nach Ges Wiss Gottingen, 1918, 2, 8–100 Search PubMed .
- S. Sagadevan, M. R. Johan and J. A. Lett, Appl. Phys. A, 2019, 125, 315 CrossRef CAS .
- G. Jayakumar, A. A. Irudayaraj and A. D. Raj, Mech. Mater. Sci. Eng. J., 2017, 9, 127–131 Search PubMed .
- P. C. Nagajyothi, K. Pavani, R. Ramaraghavulu and J. Shim, Inorganics, 2023, 11, 161 CrossRef CAS .
- A. Lasia, Modern aspects of electrochemistry, Springer, 2002, pp. 143–248 Search PubMed .
- S. Zhang, R. Wang and G. Wang, ACS Chem. Neurosci., 2018, 10, 945–953 CrossRef PubMed .
- S. E. Elugoke, O. E. Fayemi, A. S. Adekunle, B. B. Mamba, T. T. Nkambule and E. E. Ebenso, FlatChem, 2022, 33, 100372 CrossRef CAS .
- S. Yadav, M. A. Sadique, S. Singhai and R. Khan, Hybrid Adv., 2023, 4, 100108 CrossRef .
- H. A. Alhazmi, M. Imran, S. Ahmed, M. Albratty, H. A. Makeen, A. Najmi and M. S. Alam, Phys. Scr., 2023, 98, 105006 CrossRef .
- D. S. Tharani and R. Sivasubramanian, J. Chem. Sci., 2023, 135, 93 CrossRef CAS .
- G. V. Prasad, S.-J. Jang, Y. C. Sekhar, T. M. Reddy, L. S. Sarma, H.-B. Kim and T. H. Kim, J. Electroanal. Chem., 2023, 941, 117544 CrossRef .
- J. Ahmed, M. Faisal, S. Alsareii, M. Jalalah and F. A. Harraz, J. Alloys Compd., 2023, 931, 167403 CrossRef CAS .
- D. Minta, Z. González, S. Melendi-Espina and G. Gryglewicz, Surf. Interf., 2022, 28, 101606 CrossRef CAS .
- Y. Zhang, X. Yan, Y. Chen, D. Deng, H. He, Y. Lei and L. Luo, Molecules, 2024, 29, 1786 CrossRef CAS PubMed .
- C. Xu, C. Gu, Q. Xiao, J. Chen, Z.-Z. Yin, H. Liu, K. Fan and L. Li, Chem. Eng. J., 2022, 436, 135203 CrossRef CAS .
- Z. Liao, Y. Ma, S. Yao, J. Zhang, Y. Han and K. Xu, Appl. Surf. Sci., 2022, 605, 154725 CrossRef CAS .
- J. Paul and J. Kim, Appl. Surf. Sci., 2023, 613, 156103 CrossRef CAS .
- P. M. Rajaitha, S. Hajra, A. M. Padhan, D. Dubal and H. J. Kim, Mater. Sci. Eng., B, 2023, 296, 116638 CrossRef CAS .
- K. Singh, K. K. Maurya and M. Malviya, J. Nanopart. Res., 2024, 26, 1–13 CrossRef .
- Y. Zhang, H. Wang, L. Jiao, N. Wu, W. Xu, Z. Wu, Y. Wu, P. Hu, W. Gu and C. Zhu, Chem. Eng. J., 2023, 466, 143075 CrossRef CAS .
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