Selective and sensitive colorimetric determination of cobalt ions using Ag–Au bimetallic nanoparticles

Abstract

Plasmonic nanoparticle-based colorimetric sensing has gained wide attention due to its advantages including rapidity, simplicity and expensive instrument-free characters. In the present study, Ag–Au bimetallic nanoparticles were proposed as novel optical probes to determine cobalt ion (Co²⁺) concentration. The sensing mechanism is based on the fact that Co²⁺ can react with ethylenediamine (en) and S₂O₃²⁻ to form (en)₂CoS₂O₃⁺ on the nanoparticle surface, which can decrease the negative charge of the nanoparticle, reduce the repulsion between adjacent nanoparticles, and subsequently induce nanoparticle aggregation, was verified by dynamic light scattering. The effects of several parameters on the detection sensitivity, including the concentration of S₂O₃²⁻ and en, pH value and incubation time, were investigated. The assay demonstrated high selectivity toward Co²⁺ in the presence of K⁺, Cu²⁺, Pb²⁺, Ag⁺, Zn²⁺, Ba²⁺, Mn²⁺, Fe²⁺, Fe³⁺, Ni²⁺ and Hg²⁺. Under optimal conditions, the absorbance ratio of A₆₀₀/A₄₃₄ showed a linear relationship versus Co²⁺ concentration from 0 to 0.6 μM with a correlation coefficient (R²) of 0.980, and the detection limit was calculated to be 0.02 μM. The practical application of the proposed nanoprobes was evaluated with river and tap water samples.

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1. Introduction

Plasmonic nanoparticle-based colorimetric methods for detecting analytes have gained growing interest because of their simplicity, low cost, rapid response and expensive instrument-free characters.^1–4 Various analytes including metal ions,^5,6 proteins,⁷ DNA,^8,9 glucose,¹⁰ H₂S¹¹ could be determined through elaborately designed strategies with high sensitivity and selectivity. Monometallic nanoparticles, in particular gold nanoparticles and silver nanoparticles, are the two most selected materials for developing colorimetric assays due to their prominent characteristics. Both gold and silver nanoparticles possess high absorption and scattering coefficients, high optical stability without photobleaching and photoblinking.^12,13 Gold nanoparticle is inert to oxidation, having stronger chemical stability and better biocompatibility. However, silver nanoparticles have the highest efficiency of absorption and scattering light compared to gold and copper materials. For example, the molar extinction coefficient of silver nanoparticles is 20-fold larger than that of gold nanoparticles in the same volume,¹⁴ and the molar extinction coefficient is closely related to sensor sensitivity. Recently, Ag–Au bimetallic nanoparticles (BNPs, e.g., Ag core–Au shell nanoparticles) have attracted increasing attentions because their specific optical and physical features, such as good catalytic capacity, surface-enhanced Raman scattering property.¹⁵ They also can integrate the merits of the Ag and Au materials, that is, high plasmonic property of Ag and the stability of Au.¹⁶ The bands of localized surface plasmonic resonance in the range of 400–550 nm can be conveniently tuned by varying their components while keeping the nanoparticle diameter constant.¹⁷ Correspondingly, the BNP solution color could also vary from yellow to brown, to red by changing the components. Thus, BNP-based probes can provide low detection background, well stability and high sensitivity in assays. Despite of wide applications of Ag–Au BNPs, the studies on using Ag–Au BNPs as a platform in colorimetric sensors are still very rare.

Cobalt (Co²⁺) is normally recognized as an essential element for human body, which acts as the metallic component of vitamin B12 and some metal loprotease. However, exposure to its excess amount can lead to serious health diseases.^18–20 For example, excess Co²⁺ could change the enzyme activities, cause oxidative stress and DNA damage.^21,22 It can also bring about low blood pressure, paralysis and even tissue carcinogenesis.²³ On the other side, the widespread applications of cobalt in industries and medical science increase its exposure risks. For example, cobalt is important for processing alloys with corrosion and heat resistance, strong magnetism and high-strength.¹⁸ Cobalt is widely utilized in pigments in the glass and ceramics,²⁴ and lithium ion batteries.²⁵ In clinic, hip replacements are usually made from cobalt,^26,27 inevitably lifting serum cobalt levels of patients. Therefore, developing assays for detecting Co²⁺ is urgent. Up to now, atom absorption spectroscopy,²⁸ fluorescent techniques²⁹ and electrochemical methods³⁰ were exploited for Co²⁺ determination. However, there are several shortcomings including time-consuming and complex sample preparation when using these techniques. In contrast, colorimetric methods with rapid response and simple preparation characters may benefit the development of Co²⁺ determination strategy.^31,32 Thereby, colorimetric method based on plasmonic nanoparticle may be an alternate owing to its specific virtues. Zhang et al. reported a colorimetric method for Co²⁺ quantification with a detection limit of 3.0 × 10⁻⁷ M based on Co²⁺ induces aggregation of thioglycolic acid capped gold nanoparticles.³³ In Sung's work, glutathione functionalized silver nanoparticles with the shapes of sphere, plate and rod as probes for Co²⁺ were investigated and it was found rod-type silver nanoparticles showed better selectivity.³⁴ Yao et al. synthesized triazole-carboxyl bifunctionalized silver nanoparticles by a click reaction to detect Co²⁺ sensitively.³⁵ Zhang et al. developed a label free colorimetric method for cobalt determination.³⁶ Annadhasan et al. reported a green method to fabricate gold nanoparticles under sunlight irradiation by using N-cholyl-L-valine as the reducing and capping agent, which demonstrated high selectivity and sensitivity toward Co²⁺.³⁷ Nevertheless, the development of new colorimetric methods for Co²⁺ sensing is still appealing.

Herein, we developed a label-free method for sensing Co²⁺ in aqueous solutions by using Ag–Au BNPs fabricated by one-pot synthesis. The sensing is due to Co²⁺ can trigger the formation of (en)₂CoS₂O₃⁺ in the presence of thiosulfate (S₂O₃²⁻) and ethylenediamine (en), which decreases the repulsion between adjacent nanoparticles and causes the aggregation. This proposed method exhibited high selectivity toward Co²⁺ over other metal ions because of the involvement of a series of specific chemical reactions. The practical application of this method was further validated by detecting Co²⁺ in tap and river water samples.

2. Experimental

2.1 Chemicals

Hydrogen tetrachloroaurate(III) trihydrate (HAuCl₄·3H₂O), silver nitrate (AgNO₃), polyvinyl pyrrolidone (PVP, 25k MW), trisodium citrate (C₆H₅O₇Na₃·2H₂O), ethylenediamine (en), sodium thiosulfate (Na₂S₂O₃) and glycine were purchased from Sinopharm Chemical Reagent (China). Analytical grade chemicals including CoSO₄·7H₂O, KCl, CuSO₄·5H₂O, Pb(NO₃)₂, ZnCl₂, BaCl₂, MnSO₄·H₂O, FeSO₄·7H₂O, FeCl₃, NiCl₂·6H₂O, and Hg(NO₃)₂ were obtained from Sigma Aldrich. Deionized water (18.2 MΩ cm) was obtained from a Millipore system (Billerica, USA). All glassware was cleaned with fresh aqua regia (HCl : HNO₃ = 3 : 1) before use. Glycine–NaOH buffer solutions (0.1 M) with pH values ranging from 8.6 to 9.6 were prepared by glycine and NaOH and the pH values were measured with a benchtop Orion™ plus pH meter (Thermo-Fisher, USA).

2.2 Characterization

The UV-vis absorption spectra of the nanoparticles were obtained with a UV-1800 spectrophotometer (Shimadzu, Japan). Transmission electron microscopy (TEM) images of nanoparticles were collected with a JEOL JEM-1230 transmission electron microscope under operation of 100 kV (Hitachi, Japan). Photographs of nanoparticle solution was obtained with iphone 5. Dynamic light scattering (DLS) and zeta potential measurements were performed with a Zetasizer Nano ZS analyzer (Malvern, U.K.). X-ray photoelectron spectroscopy (XPS) was obtained on K-alpha 1063 X-ray photoelectron spectrometer (Thermo Fisher Scientific, USA) with Al Kα radiation operated at 72 W (6 mA emission current, 12 kV) and a base pressure of 10⁻⁹ mbar. Elemental mapping analysis was performed in the STEM mode on a Tecnai G² F20 field emission TEM (FEI, USA).

2.3 One-pot synthesis of Ag–Au BNPs

Ag–Au BNPs were prepared according to the previous reported papers with slight modifications.¹⁷ In brief, 182 μL 0.1 M AgNO₃ and 250 μL 24.28 mM (1% in weight) HAuCl₄ solutions was added into 95.5 mL distilled water in a flask. The mixture was heated to boil in oil bath under constant stirring at 250 rpm. During reflux, 2 mL 1 wt% trisodium citrate was rapidly injected into the solution. Reflux of the solution for another 1 h was to insure the formation of colloid. During this process, the color of the solution would turn to yellow from colorless. After cooling, the colloid suspension was stored at 4 °C in refrigerator prior to use.

2.4 Sensitivity and selectivity of Co²⁺ sensing

A high concentration stock solution of CoSO₄ (0.1 M) was prepared and used to prepare standard solutions through a serial dilution. For Co²⁺ detection, 1000 μL the as prepared Ag–Au BNP suspension was first mixed with 710 μL 0.1 M glycine–NaOH buffers in 2 mL tube to make the ultimate solution pH value at 9.0. Then, 55 μL distilled water, 20 μL 0.05 M Na₂S₂O₃ and 200 μL Co²⁺ solution with different concentrations were injected into the tube in sequence. Finally, after 2 min equilibration at room temperature, 15 μL 1% v/v en solution was added to each tube. The photos and UV-vis spectra of the solutions were recorded during the 20 min window. The following metal ions were used to evaluate the selectivity of the BNP sensing system: K⁺, Cu²⁺, Pb²⁺, Ag⁺, Zn²⁺, Ba²⁺, Mn²⁺, Fe²⁺, Fe³⁺, Ni²⁺ and Hg²⁺.

2.5 Real sample analysis

Water samples obtained from Xiang River and tap water in campus were firstly centrifuged (12 000 rpm, 30 min) and then filtered through a 0.2 μm membrane to remove large suspended particles. The Co²⁺ detection procedure is the same as sensitivity test. 1000 μL of the as prepared Ag–Au BNP suspension was mixed with 710 μL 0.1 M glycine–NaOH buffers, 55 μL distilled water, 20 μL 0.05 M Na₂S₂O₃ and 200 μL of the tested samples sequentially. Finally, after 2 min equilibration at room temperature, 15 μL 1% v/v en solution was added to each tube. The photos and UV-vis spectrum of the solutions were recorded after 20 min.

3. Results and discussions

3.1 Principle of Co²⁺ detection

We prepared Ag–Au BNPs by a one-pot synthetic procedure.^38,39 According to the literature,¹⁷ the BNPs have Ag core–Au shell structures, which endows them high stability. The molar ratio of Ag : Au was finally set to be 3 : 1, since the compromise was made between the strong optical properties of nanoparticles relating to the detection signals and the well chemical stability associating with convenient storage. The obtained Ag–Au BNP was characterized by camera, UV-vis spectra, TEM and XPS, as displayed in Fig. 1. The color of as-prepared nanoparticle solution was yellow, whose UV-vis spectrum peak was located at 434 nm. In contrast, the UV-vis peak of gold nanoparticle (AuNP) and silver nanoparticle (AgNP) with the same diameter are at 532 nm and 393 nm according to the Mie simulations, respectively.⁴⁰ The statistical size distribution of 132 nanoparticles was displayed in Fig. 1C. TEM results showed that these nanoparticles are spherical and monodisperse with a size of 28.6 ± 4.1 nm. Distribution of Ag and Au elements in BNPs proved that the nanoparticles consist of a predominant Ag core and a Au rich shell, which is consistent with the reported structure.¹⁷ As shown in Fig. 1E, the valence of both Ag and Au in BNP XPS was zero due to the overdose of the reducing agent. After 1.2 μM Co²⁺ was added, the color of the solution turned to pale green from yellow due to the obvious aggregation of Ag–Au BNPs with the presence of S₂O₃²⁻ and en (Fig. 1A(a) and (b)). The absorbance below 500 nm decreased, while that above 500 nm increased. The color alternation in our assay is different from that of pure AuNPs or AgNPs systems, in which AuNP solution would become purple or blue from red^2,3 and AgNP solution turns pale red from yellow.^2,41 We found that the value of A₆₀₀/A₄₃₄ could effectively reflect the ratio of the dispersed to the aggregated Ag–Au BNPs, and thus was finally used to evaluate Co²⁺ in our study.

Fig. 1 UV-vis spectra (A) and TEM images (B) of Ag–Au BNPs in 0.1 M glycine–NaOH buffer solution (pH = 9.0) containing 0.5 mM S₂O₃²⁻ and en (0.0075%, v/v) in the absence (a) and presence (b) of 1.2 μM Co²⁺. (C) The statistic diameter distribution of the Ag–Au BNPs. (D) Elemental analysis of Ag–Au BNPs (from left to right): the mapping image of Ag and Au, the overlay image and the corresponding TEM image. The size of each image is 100 × 100 nm. (E) XPS spectra of Au 4f (left) and Ag 3d (right) for Ag–Au BNPs.

In order to further study the mechanism, we measured the hydraulic diameter and zeta potential of Ag–Au BNPs under different solution conditions, as shown in Fig. 2. As expected, an obvious increase on hydraulic diameter of Ag–Au BNP (from 50.7 nm to 190.1 nm) was observed, indicating the color change of solution can be assigned to the aggregation of Ag–Au BNPs. With the addition of chemicals, the surface potential of Ag–Au BNPs also changed. When S₂O₃²⁻ was mixed with Ag–Au BNP solution, S₂O₃²⁻ was immediately and strongly absorbed onto nanoparticle surface due to the strong affinity between sulfur and gold.⁴² The zeta potential of Ag–Au BNP changed to −26.9 mV from −18 mV. S₂O₃²⁻ coated Ag–Au BNPs are very stable due to the strong electrostatic repulsions between negatively charged nanoparticles even at high ionic strength. These nanoparticles do not aggregate with the presence of 0.0075% en and their zeta potential (−26.1 mV) was unchanged, partially because en does not react with S₂O₃²⁻ directly. Upon the addition of Co²⁺, Co²⁺ could quickly react with en to form Co(en)₃²⁺ first and then Co(en)₃²⁺ was readily oxidized to Co(en)₃³⁺ by the dissolved oxygen in water.⁴³ Afterwards, Co(en)₃³⁺ would attack S₂O₃²⁻ on nanoparticle surface to form positively-charged (en)₂CoS₂O₃⁺.⁴⁴ As a result, the formed (en)₂CoS₂O₃⁺ decreased the negative charge of nanoparticle and triggered the aggregation of nanoparticle. However, the measured zeta potential become more negative (−31.6 mV) after the formation of aggregates, which can not conclude the surface charge of single nanoparticles was reduced. To bypass the problem, 0.02 wt% PVP, a polymer that is widely applied to stabilize the nanoparticle, was added to the solution to prevent nanoparticle aggregation after adding Co²⁺. PVP stabilized nanoparticles have a potential of −13.8 mV, but after the addition of Co²⁺, an increased potential around −4.0 mV emerged (Fig. 2C). This result confirmed that Co²⁺ indeed reduced the negative charge and caused the aggregation of Ag–Au BNPs. Scheme 1 depicted the mechanism of Co²⁺ detection.

Fig. 2 (A) Hydrodynamic size distribution of Ag–Au BNPs without and with the addition of 0.8 μM Co²⁺ in the presence of 0.5 mM Na₂S₂O₃, 0.0075% (v/v) en at pH 9.0. (B) Zeta potential of Ag–Au BNPs without and with the addition of 0.5 mM Na₂S₂O₃, 0.5 mM Na₂S₂O₃/0.8 μM Co²⁺, 0.5 mM Na₂S₂O₃/0.8 μM Co²⁺/0.0075% en and 0.5 mM Na₂S₂O₃/0.0075% en, respectively. (C) Zeta potential of Ag–Au BNPs upon adding 0.02% PVP, 0.5 mM Na₂S₂O₃ and 0.8 μM Co²⁺ at pH 9.0 in the absence and presence of 0.0075% en.

Scheme 1 Schematic illustration of colorimetric Co²⁺ detection using Ag–Au BNPs.

3.2 Establishment of the colorimetric sensing method for Co²⁺

As mentioned above, the Co²⁺ induced nanoparticle aggregation was attributed to the formation of (en)₂CoS₂O₃⁺ at the surface of Ag–Au nanoparticles. Since this reaction needs the participation of several reagents, a systematic investigation was performed to optimize these parameters by monitoring the ratio of absorbance ratio (A₆₀₀/A₄₃₄)_sample/(A₆₀₀/A₄₃₄)_blank changes at 600 and 434 nm, including the concentration of S₂O₃²⁻ and en, solution pH value and the incubation time. During this study, the concentration of Co²⁺ of 1 μM was fixed.

The content of S₂O₃²⁻ in the range of 0–1.0 mM was investigated when en was fixed at 0.0075% and the pH value at 9.2 in the presence (sample) and absence (blank) of Co²⁺, as illustrated in Fig. 3. With the increasing S₂O₃²⁻ concentration, (A₆₀₀/A₄₃₄)_blank remained unchanged, but the values of (A₆₀₀/A₄₃₄)_sample and (A₆₀₀/A₄₃₄)_sample/(A₆₀₀/A₄₃₄)_bank increased gradually and reached to the top above 0.5 mM. The possible explanation is that, at low S₂O₃²⁻ concentration, the surface of nanoparticle was not completely coated by S₂O₃²⁻ and thus there was no enough sites on nanoparticle for Co(en)₃³⁺ combination. While at high S₂O₃²⁻ concentration (>0.5 mM), the surface of nanoparticle is totally occupied and free S₂O₃²⁻ exists in solution. We suppose Co(en)₃³⁺ tends to react with S₂O₃²⁻ at particle surface probably due to the strong electrostatic attraction between Co(en)₃³⁺ and the high negatively charged surface. Consequently, 0.5 mM S₂O₃²⁻ was chosen for the assay.

Fig. 3 Absorbance ratio (A₆₀₀/A₄₃₄)_blank, (A₆₀₀/A₄₃₄)_sample and (A₆₀₀/A₄₃₄)_sample/(A₆₀₀/A₄₃₄)_blank of Ag–Au BNPs solution versus the concentration of Na₂S₂O₃. Experimental conditions: 1.0 μM Co²⁺, pH = 9.2, 0.0075% (v/v) en, 20 min incubation time.

It is well-known that solution pH could influence the interactions of nanoparticle with capping molecules, and thus alter nanoparticle stability, sensitivity and selectivity of the assay. We investigated the effect of solution pH in the range of 8.6–9.6. As shown in Fig. 4, (A₆₀₀/A₄₃₄)_sample/(A₆₀₀/A₄₃₄)_blank reached the maximum value at pH 9.0. It is possible because low pH could cause decomposition of S₂O₃²⁻, since its stability is proportional to pH. On the other hand, protonated en can hinder the formation of (en)₂CoS₂O₃⁺. Conversely, extremely high pH may decrease the stability of nanoparticles via decreasing the surface repulsion and reduce oxidizing capacity of dissolved O₂ on Co²⁺. Therefore, pH 9.0 was finally opted for the assay. Similarly, as demonstrated in Fig. 5, the optimal en concentration was determined to be 0.0075% (v/v).

Fig. 4 Absorbance ratio (A₆₀₀/A₄₃₄)_blank, (A₆₀₀/A₄₃₄)_sample and (A₆₀₀/A₄₃₄)_sample/(A₆₀₀/A₄₃₄)_blank of Ag–Au BNPs solution versus solution pH. Experimental conditions: 1.0 μM Co²⁺, 0.5 mM S₂O₃²⁻, 0.0075% (v/v) en, incubation time 20 min.

Fig. 5 Absorbance ratios (A₆₀₀/A₄₃₄)_blank, (A₆₀₀/A₄₃₄)_sample and (A₆₀₀/A₄₃₄)_sample/(A₆₀₀/A₄₃₄)_blank of Ag–Au BNPs solution versus en concentration. Experimental conditions: 1.0 μM Co²⁺, 0.5 mM S₂O₃²⁻, pH = 9.0, incubation time 20 min.

The incubation time is a key point for the colorimetric assays. The relationship between the ratio of A₆₀₀/A₄₃₄ and incubation time was obtained by recording the UV-vis spectra of Ag–Au nanoparticle solution after the addition of 1 μM Co²⁺, as shown in Fig. 6. It can be seen that (A₆₀₀/A₄₃₄)_sample increased with the increasing incubation time, and reached a flatform after 20 min. The incubation time of 20 min in Co²⁺ assays was selected.

Fig. 6 Plots of the time-dependent absorbance ratio (A₆₀₀/A₄₃₄) of Ag–Au BNPs solution versus reaction time without (black) and with (red) the addition of 1.0 μM Co²⁺ in the presence of 0.5 mM S₂O₃²⁻, 0.0075% (v/v) en at pH 9.0.

3.3 Co²⁺ sensing in aqueous media

Selectivity of sensing methods is very important for its practical applications. In this study, the ratio of A₆₀₀/A₄₃₄ of Ag–Au nanoparticle solution upon addition of various metal ions including K⁺, Cu²⁺, Pb²⁺, Ag⁺, Zn²⁺, Ba²⁺, Mn²⁺, Fe²⁺, Fe³⁺, Ni²⁺ and Hg²⁺ under optimal conditions were measured to investigate whether the aggregation induced by Co²⁺ is specific. As manifested in Fig. 7, none of these metal ions (K⁺, Pb²⁺, Ag⁺, Zn²⁺, Ba²⁺, Mn²⁺, Fe²⁺, Fe³⁺, Ni²⁺, Hg²⁺: 100 μM; Cu²⁺: 5 μM) can induce comparable aggregation of Ag–Au nanoparticle as 1 μM Co²⁺ did. Such a high selectivity toward Co²⁺ of this method might be ascribed to the specific chemical reactions in Co²⁺, en and S₂O₃²⁻ system. First, Co²⁺ can react with en to generate chelating complex Co(en)₃²⁺; second, the complex with low Gibbs free energy can be oxidized into Co(en)₃³⁺ by dissolved oxygen; third, by reacting with S₂O₃²⁻, Co(en)₃³⁺ could effectively reduce the negative charge on gold surface and lead to nanoparticle assembly. Despite of the formation of other metal–en complex, the lacking valence conversion or low reactivity to S₂O₃²⁻ lead to different results upon adding other metal ions. Thus, our system showed excellent selectivity toward Co²⁺.

Fig. 7 The absorbance ratio (A₆₀₀/A₄₃₄) of Ag–Au BNPs solution upon the addition of various metal ions at pH 9.0 in the presence of 0.5 mM S₂O₃²⁻ and 0.0075% (v/v) en. Concentrations: 100 μM K⁺, Pb²⁺, Ag⁺, Zn²⁺, Ba²⁺, Mn²⁺, Fe²⁺, Fe³⁺, Ni²⁺, Hg²⁺, 5 μM Cu²⁺ and 1 μM Co²⁺.

For the sensitivity evaluation, absorption spectra of Ag–Au nanoparticle solution were recorded after adding Co²⁺ with different concentrations (0, 0.05, 0.1, 0.2, 0.4, 0.6, 0.8, 1.0 and 1.2 μM). Upon increasing Co²⁺ concentration, the absorbance at 434 nm decreased, while that of new generated peaks in the range of 600–850 nm increased. The appearance of absorption shifted probably due to the occurrence of fusion between aggregated nanoparticles, which is confirmed by TEM results. The corresponding photographs of solution changed from yellow to light yellow, and finally pale green. As can be seen from Fig. 8, the ratio of A₆₀₀/A₄₃₄ of Ag–Au nanoparticle solution increased gradually upon increasing Co²⁺ concentration, and a typtical S-shaped curve is acquired. At 0.6 μM, the curve has nearly reached the plateau, which is lower than that tested by gold nanoparticle.³⁶ A linear relationship was obtained with Co²⁺ in the range from 0 to 0.6 μM and was easily described by the linear equation with a correlation coefficient (R²) of 0.980: y = 0.085 + 1.055x, where y and x are the ratio of A₆₀₀/A₄₃₄ and Co²⁺ concentration, respectively. The limit of detection toward Co²⁺ of our assay was calculated to be 0.02 μM (3σ), which is lower than those reported colorimetric methods.^33–36 Taken together, we could conclude that Ag–Au nanoparticle could be capable probes for Co²⁺ sensing.

Fig. 8 (A) Absorption spectra and solution color of Ag–Au BNPs solution with the addition of various concentrations of Co²⁺ (from (a to i): 0, 0.05, 0.1, 0.2, 0.4, 0.6, 0.8, 1.0 and 1.2 μM). (B) Corresponding plots of absorbance ratio (A₆₀₀/A₄₃₄) versus the concentration of Co²⁺.

3.4 Quantification of Co²⁺ in real samples

To investigate the potential application of the designed system in real samples, we tested tap and river water samples with spiked Co²⁺. The water samples did not induce the color change of Ag–Au nanoparticle solution without extra Co²⁺. The atomic absorption spectrum analysis demonstrated that the Co²⁺ content is below the detection limit of our method. Further, spike-recoveries tests showed that the recoveries for 0.4 μM Co²⁺ in tap water and 0.3 μM in river water were 102% and 106%, respectively. These results suggest the accuracy of the proposed method and its practicability for Co²⁺ detection in environmental samples.

4. Conclusions

In this study, a simple and selective colorimetric method of Co²⁺ detection based on the aggregation of Ag–Au BNPs was developed. These BNPs used in this methods guarantee the high chemical stability and optical signals. Based on the special reactions in Co²⁺, en and S₂O₃²⁻ system, this assay can achieve the Co²⁺ determination with the presence 100-fold other ions such as K⁺, Pb²⁺, Ag⁺, Zn²⁺, Ba²⁺, Mn²⁺, Fe²⁺, Fe³⁺, Ni²⁺ and Hg²⁺ and 5-fold Cu²⁺. This method has a low LOD of 0.02 μM with a linear range in 0–0.6 μM. The rapid response within 20 min makes the assay capable of real-time and on-site Co²⁺ sensing applications. Our assay also showed effective applications in the real water sample analysis. New avenues for the design of bimetallic sensors for other analytes based on a similar strategy might be opened up in the analytical and related fields by preparing BNP with different sizes and compositions.

Acknowledgements

This work was supported by funding from the National Natural Science Foundation of China (21505162, 21605003, 31571874), the Grain-Oil Process and Quality Control 2011 Collaborative and Innovative Grant from Hunan province, the China Postdoctoral Science Foundation (2016M600899), and the Fundamental Research Funds for the Central Universities (BUCTRC201619, ZY1625).

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