Sensing of Biologically Important Cations Such as Na+, K+, Ca2+

Article pubs.acs.org/Langmuir

Sensing of Biologically Important Cations Such as Na+, K+, Ca2+, Cu2+, and Fe3+ Using Magnetic Nanoemulsions V. Mahendran and John Philip* SMARTS, Metallurgy and Materials Group, Indira Gandhi Centre for Atomic Research, Kalpakkam 603 102, TamilNadu, India S Supporting Information *

ABSTRACT: We report a simple approach to the ultrasensitive detection of biologically important metal ions using a magnetic nanoemulsion. The nanoemulsion used in our study was an oil-in-water emulsion droplet of average size ∼190 nm containing ferrimagnetic iron oxide nanoparticles of average size ∼10 nm. In a static magnetic field, the emulsion droplets selfassemble into a nanoarray with distinct interdroplet spacing. In the presence of cations in the solution, the nanofluid array shows a large blue shift in the diffracted Bragg peak and a visually perceivable color change due to changes in the electrical double layer upon the diffusion of cations. The colloidal force−distance measurements in the presence of cations show large variations at the onset of repulsion in the presence of cations. The sensor shows good selectivity to Na+, K+, Ca2+, Cu2+, and Fe3+ ions and offers a rapid response compared to conventional techniques. This approach can be useful for the recognition of biologically important cations. Cu2+,5,6,8,15,16,20,29−31 Na+,3,21,32,33 Ca2+,12,24,34 and Mg2+ and anions.23,35−37 Despite the developments in this field, many practical challenges remain in packaging these sensors to reach the market as a result of the complex fabrication procedures involved and the requirements of specific chemical functionalities. Other major drawbacks of some of the existing sensors is their slow response and poor sensitivity/selectivity. Here, we report a simple approach suitable for the recognition of metal ions with ultrahigh sensitivity (parts per million level) and selectivity using stimuli-responsive, magnetically polarizable oil-in-water nanoemulsion droplets. Over the years, magnetic dispersions have evolved as a new class of stimuli-responsive smart materials with numerous applications,36,38 and they have also been a wonderful model system for fundamental studies.39−42 The new sensor has been tested for various biologically important cations such as Na+, K+, Ca2+, Cu2+, and Fe3+. Unlike other approaches, the present approach involves neither ion receptor entities nor complex preparation techniques. The response time of the new sensor is about 2 orders of magnitude faster than that of photonic-crystal-based sensors. We obtain insight into the underlying mechanism for the changes in optical properties by measuring the subtle changes in the intermolecular forces between droplets.

1. INTRODUCTION An excess or deficiency of heavy metal ions such as Fe3+, Zn2+, and Cu2+ and intracellular ions such as Na+, K+, Ca2+, and Mg2+ in human body fluids can lead to various biological disorders. For example, Fe3+ plays an essential role in oxygen uptake, metabolism, and electron transfer in the body.1 An Fe3+ deficiency can lead to the permanent loss of motor skills, and its excess can lead to diseases such as Parkinson’s and Alzheimer’s.2 Therefore, periodic monitoring of cations is a prerequisite for studying the physiological functions and the diagnosis of diseases and their prevention. The techniques for the detection of ions at low concentrations use polymer hydrogels,3,4 conducting polymer nanoarrays,5 core/shell microsphere-based luminescent probes,6 polyelectrolyte films,7 biomediated silver nanoparticles,8 gold nanoparticles,9 conducting thin films,10 OTFTs (organic thin film transistors),11 metal ion-based fluorescence,12 luminescence,13 electrochemical methods,14 colorimetric approaches based on the catalytic leaching of silver-coated gold nanoparticles,15 an allosteric dualDNAzyme-based method,16 self-assembled monolayers,17 SERS (surface enhanced Raman scattering),18,19 magnetic materials,6,20 holography,21 photonic crystals,22 1D periodic block copolymer photonic lamellar gels,23 and functionalized hexagonal ZnO nanorod-based electrochemical sensors.24 Some of these techniques are expensive, complex in design, nonportable, and involve detailed data analysis.10 This triggered an interest in developing versatile, inexpensive, portable, and easy to use techniques for the rapid and accurate detection of toxic metal cations in our fresh water resources, food items and body fluids.25 Many strategies have been developed for sensing biologically important cations such as Fe3+,1,26,27 Zn2+,3,28 © 2013 American Chemical Society

2. MATERIALS AND METHODS 2.1. Materials. Sodium dodecyl sulfate (CH3(CH2)10CH2SO4−Na+) was purchased from Aldrich and used Received: February 6, 2013 Revised: March 5, 2013 Published: March 11, 2013 4252

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without further purification. Fe3O4 nanoparticles and oil-in-water emulsions were produced in our laboratory, and details of the preparation methods are discussed below. Milli-Q water was used for all of the experiments. 2.2. Magnetic Nanofluids. The magnetically polarizable nanoemulsion used in our studies has three constituents: an octane-based ferrimagnetic nanoparticle dispersion with a particle size of about 10 nm, an ionic surfactant of sodium dodecyl sulfate (CH3(CH2)10CH2SO4−Na+), and water. The iron oxide (magnetite, Fe3O4) nanoparticles used in our study were synthesized by a simple coprecipitation technique.43 The freshly prepared iron salt solutions of 0.2 M FeCl2·4H2O and 0.4 M FeCl3·6H2O were mixed in a 1:1 ratio at a constant stirring speed of 1000 rpm. After the addition of ammonium solution, the pH of the solution reached a value of 10. When the solution turned black, oleic acid was added and the dispersion pH was adjusted to 9.5. The temperature was then increased to 70 °C. The solution was held at the same pH, temperature, and stirring speed for 30 min to finish the coating process. After this step, the temperature was increased to 79 °C in order to eliminate the excess ammonia. The surfactant-coated particles were washed with triply distilled water at 60 °C until the pH became 7 to remove the ionic impurities, and the particles were later dispersed in hexane. The hexane dispersion was treated with acetone to induce the aggregation of particles. The aggregated particles were then separated from dispersion by centrifugation at 2500 rpm for 30 min. The precipitated magnetite nanoparticles were again dispersed in hexane for further treatment. The hexane−acetone mixture washing procedure was repeated again to remove excess surfactant in the dispersion. The surfactant-coated magnetite nanoparticles were dried at 35 °C for 48 h in an inert atmosphere, and the dried particles were dispersed in octane. The final suspensions were very stable against gravitational settling for several years because of the optimal coating.44 2.3. Magnetic Nanoemulsions. The oil-in-water ferrofluid emulsion was prepared using a simple emulsification procedure.45,46 The octane-based ferrimagnetic nanoparticle dispersion was sheared in the presence of water containing sodium dodecyl sulfate at 1000 rpm. The oil, surfactant, and water used were 5, 5, and 90 wt %, respectively. The first step leads to the formation of a water-in-oil emulsion with a very large size distribution, which is then inverted to an O/W emulsion using a colloidal mixer. The resultant polydisperse emulsion is converted to a fairly monodisperse one with a narrow droplet size distribution using a fractionation technique that exploits the depletion flocculation under added surfactant micelles.46 The origin of the depletion attraction is an excluded volume effect that produces a local osmotic pressure or chemical potential difference. When the surfactant concentration is much greater than the critical micelle concentration, the larger emulsion droplets sediment because of depletion flocculation induced by the nonadsorbed surfactant resulting from the uncompensated osmotic pressure. Depletion flocculation occurs when the interdroplet spacing is smaller than the micellar diameter where the small micelles are excluded from the gap between droplets. The larger droplets settle down with a smaller centrifugal force, and the smaller droplets remain in the dilute supernatant phase. The centrifuge rpm and the number of surfactant micelles are adjusted such that droplets with different size distributions are obtained. The dilute phase is separated, and the dense phase is further diluted with surfactant. The process is repeated six times to select particles of different sizes. The properties of the emulsions of different droplet sizes are characterized by various techniques. 2.4. Characterization Methods. The prepared nanoparticle samples were characterized for phase identity by X-ray diffraction using a Rigaku Ultima IV X-ray diffractometer. The crystallite size (d) was calculated using the Scherrer formula, d = kλ/β cos θ, where k = 0.89, λ = 1.5418 Å, β is the full width at half height of the highest peak (FWHM), and θ is half of the diffraction angle. The magnetic properties of the nanoparticles were studied using cryogen-free mini VSM (Cryogenics, U.K.) for applied field strengths of between −2.5 and 2.5 T. The thermogravimetric analysis of the particles was carried out using a Mettler Toledo TGA/DSC system under an inert atmosphere from 30 to 600 °C at a heating rate of 5 °C/min. A Tecnai

F30 instrument with an acceleration voltage of 200 kV was used to record TEM images. The samples were prepared by slowly evaporating a drop of a nanoparticle suspension in acetone on amorphous carboncoated copper grids at room temperature. Small-angle X-ray scattering (SAXS) studies were carried out on a Rigaku Ultima IV instrument that uses Cu Kα (λ = 1.5418 Å) as the X-ray source. The scattering intensity I(q) was measured as a function of the scattering vector (q = 4π sin θ/λ). The scattering intensity plot was fitted with the spherical model equation, and the most probable particle size was obtained from the distance distribution function. Fourier transform infrared spectroscopy (FTIR) studies were done using an ABB Bomem MB 3000 instrument. The spectrum was obtained in the wavenumber range of 400 to 3600 cm−1. The size distribution and zeta potential (ζ) of the final emulsion has been measured by using a Malvern Zetasizer (ZS) that works on the principle of dynamic light scattering (DLS). The cryo freeze−fracture study was done by quenching the emulsion drops to 77 K by rapid immersion in liquid nitrogen and fracturing cold in vacuum. The platinum−carbon-coated replica is then observed under a transmission electron microscope to see the topography of the droplet. 2.5. Force Apparatus. The force-measuring apparatus comprises a solenoid-type electromagnet, programmable variable-current source, white light source, and a spectrograph.47,48 The schematic and photograph of the force apparatus are shown in Figures S1 and S2 (Supporting Information), respectively. By varying the magnetic field strength, the distance between the colloidal particles is precisely controlled. White light illuminates the nanoemulsion. Optical fibers direct and steer the incoming and outgoing light beam, and a polarizing beam splitter turns the reflected light 90° with respect to the incoming beam. A monochromator with a holographic grating diffracts the light beam, and the diffracted beam is sent to a photodiode array that is interfaced with a computer. The output from the photodiode array is finally displayed as reflectance versus wavelength. To form a stable chain of droplets, the repulsive force must exactly balance the attractive force. The dominant force in a field-induced droplet chain is the dipole−dipole attraction. The van der Waals contribution becomes significant only at short distances. The attractive dipole force within an infinitely long chain is49 Fchain = −∑n∞= 1n 6m2/ (nd)4 = −ς(3)6m2/d4, where ζ(3) is the Riemann ζ function. Here, m is the induced magnetic moment of each drop, which can be determined self-consistently from the intrinsic susceptibility of the ferrofluid, the spherical shape of the droplet, and the presence of neighboring droplets, m = μ04πa3χsHT/3, where μ0 is the magnetic permeability of free space, χs is the susceptibility of a spherical droplet of radius a, and HT is the total magnetic field acting on each droplet. For a droplet within an infinitely long chain of particles with equal spacing d, the total dipole field from all other particles is H1 = 2∑n∞= 1 2m/(nd)3. Therefore, for an infinite dipole HT is the sum of the external applied field (H0) and the field from the induced magnetic moments (H1) in all of the neighboring drops in the chains. For the force calculation, the effect of the magnetic moment induced by neighboring droplets is also included. It must be noted that the formula used in the force calculation assumes a spherical shape for the droplets. To minimize the magnetic energy, a uniformly magnetized droplet elongates parallel to the magnetization direction. The competition between the magnetic and surface energies decides the eccentricity e. Because of the strong surface tension, the elongation of the nanometer-sized droplet can be very small and hence the droplet shape can be approximated as a prolate spheroid with eccentricity e ≪ 1.49

3. RESULTS AND DISCUSSION 3.1. Properties of Nanoparticles and Nanoemulsions. The XRD pattern of oleic acid-coated iron oxide (magnetite) nanoparticles (Figure S3a, Supporting Information) shows that the (220), (311), (400), (422), (511), and (440) diffraction peaks can be indexed to the cubic spinel structure of Fe3O4. The inverse spinel structure consists of oxide ions in the cubic close-packed arrangement in which one-third of the tetrahedral 4253

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interstices and two-thirds of the octahedral interstices coordinate with oxygen. The average crystallite size obtained was ∼10 nm. The room-temperature magnetization curve for the iron oxide nanoparticles shows a superparamagnetic nature with zero remanence and coercivity (Figure S3b, Supporting Information). The saturation magnetization was found to be 59 emu/g. The parallel alignment of Fe2+ and Fe3+ ion spins in the adjacent octahedral sites leads to a net magnetization and thus ferrimagnetic behavior. The thermogravimetric curve for the magnetite nanoparticles shows (Figure S3c, Supporting Information) a two-step weight loss at ∼199 and ∼320 °C. The first step should be due to the removal of loosely bound or free surfactant, and the second step should be due to the removal of strongly bound surfactant molecules. The carboxylic acid group of oleic acid binds the magnetite, and the aliphatic chain extends out into the nonpolar solvent, thus providing steric hindrance between particles. The charges at the carboxylate ion of oleic acid delocalizes in between two oxygen atoms because of the resonance effect. The surfactant coating thus prevents the agglomeration of particles against van der Waals and magnetic attractive interactions and passivates the nanocrystals from oxidation. Assuming that the surfactant forms a close-packed monolayer on the nanoparticles, the total weight loss due to the loss of surfactant is calculated theoretically, which shows that the surfactant present in the system is slightly more than the amount required, forming a close-packed monolayer on the surface of the spherical nanoparticles. The average size of the nanoparticles obtained from dynamic light scattering measurements was ∼12.5 nm (Figure S3d, Supporting Information). The larger size obtained from DLS, compared to that obtained from XRD, is due to the fact that the former gives the hydrodynamic diameter that includes the dead surface layer and solvent molecules whereas the later gives the crystallite size. The TEM analysis of the sample shows (Figure S4a,b, Supporting Information) amorphous contrast at the boundaries of nanoparticles due to the adsorbed organic moieties at the nanoparticle interface. The particle size distribution obtained from the best fit on SAXS data for a volume fraction of 0.017 shows that the most probable particle size is 11 nm (Figure S5a,b, Supporting Information). The cappng of oleic acid on nanoparticles was confirmed by Fourier transform infrared spectroscopy (FTIR), which (Figure S6, Supporting Information) shows characteristic peaks at 2921, 2858, 2358, 1728, 1458, 1375, 1274, 632, and 570 cm−1. The peaks at 2921 and 2858 cm−1 are due to the asymmetric and symmetric stretching, respectively, of the ethylene group of the oleic acid. The peak at 1458 cm−1 corresponds to the asymmetric stretching of the carboxylate (COO−) group. The peak at 570 is attributed to the stretching of bonds between octahedral and tetrahedral metal ions to oxide ions whereas that at 1728 cm−1 is due to the presence of free oleic acid molecules. The rest of the peaks are attributed to vibrations of the oil. The interaction between the carboxylate head and the metal atom can be monodentate, bridging (bidentate), chelating (bidentate), and ionic. The wavenumber separation (Δ) between the υs(COO−) and υas(COO−) of the IR bands can be used to distinguish the type of interaction between the carboxylate head and the metal atom. Our studies show that the interaction is chelating bidentate, where the interaction between the COO− group and the Fe atom is covalent (Δ ≈ 83 cm−1).50 Figure 1a,b shows the size distribution and zeta potential of the emulsion used in our study. The average size of the emulsion droplets measured by dynamic light scattering was

Figure 1. (a) Size distribution and mean hydrodynamic diameter. The inset shows the cryo freeze−fracture TEM image of emulsion droplets. The images show spherical droplets with a clear boundary. (b) Normalized zeta potential measured in the presence of 0.8 mM SDS. The peak value is found to be −42 mV.

∼190 nm. The cryo freeze−fracture TEM images of two nanoemulsion droplets (inset of Figure 1a) show a spherical shape with a clear boundary. Because the size of the nanoparticles within the droplets is 1, linear chainlike structures are formed along the field direction (Figure S7b−d, Supporting Information). To form stable chains, the repulsive force between droplets must exactly balance the attractive forces. For perfectly aligned droplets of spacing d, the first-order Bragg condition for backscattering is 2d = λmax/n, where n is the refractive index of the suspending medium and λmax is the Bragg peak wavelength. The repulsive force corresponding to each interdroplet spacing is obtained by computing the corresponding attractive dipole force and van der Waals forces. Figure 3a−d shows the λmax shift as a function of cation concentration for K+, Cu2+, Ca2+, and Fe3+. The λmax shift was

3.3. Force Profiles in the Presence of Diffused Cations. The colloidal surface layer of charge along with the diffuse cloud of co-ions and counterions in the solution forms the electrical double layer.52 The addition of cations to the solution leads to a reduction in the interdroplet spacing due to a blue shift in the Bragg peak as shown in Figure 2. In general, at higher surface charge densities, most of the counterions occupy a thin layer of thickness whereas for lower surface charge densities the counterions become diffuse. The Poisson− Boltzmann (PB) method becomes asymptotically exact in the limit of weak surface charges, low counterion valency, and high temperature. However, the PB approach fails for multivalent ions and for highly charged surfaces because of correlated iondensity fluctuations around the mean ion distribution and the additional nonelectrostatic interactions between ions or between ions and surfaces. Therefore, the force between charged surfaces in electrolyte solutions is highly ion-specific. Also, the liquid molecular structure and hydration effects can play an important role in the effective forces.53 For droplets with low (κa > 5) surface charge densities, the force profile follows the equation Fr(d) = 4πεψ02a2[k/d + 1/d2]exp[−κ(d − 2a)], where ε is the dielectric permittivity of the suspending medium, ψ0 is the electrical surface potential, and κ−1 is the Debye screening length (referred to as the decay length), which essentially depends on the electrolyte concentration (Cs) as κ−1 = [(4πq2/εkT)2Cs]−0.5 where q is the charge and kT is the thermal energy. To obtain better insight into the variation in the lattice spacing or λmax shift, the interdroplet force measurements are carried out as a function of distance between droplets. The various force measurement techniques developed over the last several decades have enabled the precise measurement of force as a function of distance. Among various force measurement techniques,54 the magnetic chaining technique enables the measurement of forces in situ in emulsions or colloidal dispersions.47 Figure 4a−c shows force−distance profiles in the presence of K+, Cu2+, and Fe3+ cations of different concentrations. In all cases, the force profiles are found to decay exponentially with the interdroplet spacing. From the force−distance curve, we extract two parameters: the first interaction distance (2L0), which is defined as the distance at which the force value is 2 × 10−13 N, and the κ−1 that describes the spatial extension over which the perturbation due to an electrical double layer extends. When the magnetic dipole attraction balances the net repulsion (i.e., electrostatic in the present case), the emulsion droplets forms a 1D-ordered structure. The minimum magnetic force required to overcome the thermal energy at (273 K) room temperature is ∼2 × 10−13 N in the present case. Below ∼2 × 10−13 N, no 1D ordering occurs in the system. In the case of K+, the 2L0 values for 0, 20, 39, 78, 195, and 391 ppm are 82, 72, 67, 58, 51, and 45 nm, respectively. In the case of Cu2+, the 2L0 values for 3, 6, 16, 32, and 63 ppm are 74, 69, 62, 55, and 51 nm, respectively. The average value of the Debye length for the K+ and Cu2+ ions is ∼7 nm. The 2L0 values for 0.410, 0.820, 2, 4, and 8 ppm of Fe3+ cations are 84, 81, 80, 78, and 76 nm, respectively, where the average decay length is ∼8 nm. Like the trivalent ions, the decay length did not change much for divalent ions. However, the magnitude of the force in the above concentration range increases significantly (∼20-fold), which indicates an increase in the surface potential. For Na+, the 2L0 values for 12, 23, 46, 115, and 230 ppm are 67, 61, 54, 47, and 43 nm, respectively (Figure S8, Supporting Information). The decay length for the above

Figure 3. λmax wavelength shift as a function of cation concentration (linear regime) for (a) K+, (b) Cu2+, (c) Ca2+, and (d) Fe3+. (Insets) Sensor response for the entire concentrations of ions.

monotonic and linear in the concentration ranges shown in Figure 3. The λmax for higher concentration is shown in the respective insets of Figure 3. For K+, the shift in λmax was 146 nm as the concentration of ions increased from 0 to 319 ppm, where the observed lattice spacing (h = d − 2a) reduction was ∼55 nm. For Cu2+ cations, the shift in λmax was 83 nm as the concentration of ions increased from 0 to 51 ppm, where the h reduction was ∼31 nm. For Ca2+ and Fe3+, the reductions in h were 32 and 20 nm, respectively. Though the overall shifts in the λmax in both the cases are similar, the slopes were different for different cations. The different slopes indicate the selectivity for various ions. Even slight changes in the ionic radius influence the slopes. The slopes of the linear regime for K+, Cu2+, Ca2+, and Fe3+are 1.27, 3.9, 1.25, and 4.9, respectively. 4255

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and dielectric constant near the interface as a result of the presence of ions.58 The structuring of water at the hydrophobic surface in the presence of ions and the directional binding of molecules can also lead to changes in 2L0. 3.4. Selectivity and Response Time. To check the selectivity of this approach for the detection of various metal ions, the variation in the slopes of λmax shift for various metal ion concentrations is compared. Figure 5a shows the slope of

Figure 5. (a) Slopes (indicating the selectivity) of λmax shift as a function of cation concentrations for different ions. (b−d) Schematic representation of the emulsion droplets in the presence of metal ions and adsorbed surfactant molecules. (Bottom to top): Low to high metal ion concentration.

the λmax shift as a function of the cation concentrations for different ions. Interestingly, the slopes were different in all cases, thus providing selectivity for the recognition of different metal ions in solution. The highest to lowest sensitivity sequence is Fe3+ > Cu2+ > Na+ > K+ > Ca2+. The typical time scale for the alignment of droplets in 1D is τ = 6η/μ0ϕχ2H02, which is about a second in the present case for a magnetic field strength of 90 G. Here, η is the viscosity of the surrounding liquid and ϕ is the initial volume fraction of the droplets. The Brownian relaxation time for a 200 nm droplet in water is ∼3 ms whereas the Neel relaxation time is ∼1 ns. Therefore, this approach offers a rapid detection possibility for various ions. To evaluate the response time of the sensor, Bragg peaks were recorded at a fixed ion concentration for 60 min (Figures S9 and S10, Supporting Information). The Bragg reflected peak attains its maximum height within ∼1 s. The change in the peak wavelength over the period of 60 min is within 1 nm. The reflectance intensity is slightly decreased under a longer exposure time because of the heat generated by the electromagnet. Figure 5b−d shows the schematic representation of the emulsion droplets in the presence of metal ions of different concentrations. The droplets are adsorbed with a monolayer of surfactant where the polar headgroups reside at the interface and the hydrophobic alkyl chains reside inside the oil droplets. The diffuse double layer around the nanodroplets is shown by the green circle. At a fixed magnetic force, the addition of cations causes a reduction in the interdroplet spacing (blue shift of λmax). Table 1 shows the various sensing methods available for different analytes and their detection range. It can be seen that the present technique offers selectivity for a wide number of cations and a faster response time of ∼1 s.

Figure 4. (a−c) Force−distance profiles for different concentrations of cations (a) K+, (b) Cu2+, and (c) Fe3+. The solid/dashed lines show the theoretical fit.

concentration range is ∼6 nm. For Ca2+, the 2L0 values for 2, 3, and 4 ppm are 45, 41, and 36 nm, respectively (Figure S9, Supporting Information). The decay length for the above concentration range was ∼5 nm. These results show that 2L0 values are very sensitive to the diffusion of ions into the double layer. However, no significant variation in the decay length is observed with added ions. The decay length calculation using electrostatic theory is found to be inaccurate for multivalent ions because of the complex many-body potential between the spheres.55−57 At smaller interdroplet spacing, only the counterions are expected to contribute to the electrostatic screening because of strong repulsion between other spheres. Our results reveal that with increase in the concentration of ions the 2L0 value decreases by several nanometers. Interestingly, the experimental force profiles follow electrostatic theory, irrespective of the concentration of added cations. It should be noted that the nonretarded van der Waals attraction is effective only at high salt concentrations and at very small surface separations. The short-range repulsions can also occur because of surface hydration layers resulting from the change in the diffusivity 4256

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Table 1. Various Sensing Methods/Materials Available, Analytes, Their Detection Range, Response Time, and the Corresponding Reference methods bilayer film of PAH/PAA HPTS (fluorescence) rhodamine B-dimer (fluorescent) fluorescence-based holographic sensors organic thin film transistor fluorescent optrode impedance response of self-assembled monolayers luminescent fluorescent (sugar−rhodamine) colorimetric (DNAzyme) colorimetric (Ag-coated Au NPs) colorimetric (SAM-modified Au NPs) visual (Cu catalyzed in Ag formation) SERS (dye-coated Ag NP based) fluorescence electrochemical present technique

AUTHOR INFORMATION

Corresponding Author

ref

*E-mail: [email protected]. Fax: 00 91-44-27450356. Tel: 00 91 44 27480232.

0−1 mM

59

Notes

Fe Fe3+ K+ Ca2+, K+ Na+ Na+, K+

1nM−12 μM 0−5 μM 0−30 mM 0.10 mM

2 26 21 11

0.01−2M 0−50 mM

33 32

Cu2+

0−10 μM 0−1 mM 5−800nM 0−80 μM 0−10 μM 0−100 μM 0−10 μM 0−40 μM 0.1 μM−10 mM 0−240 μM 0−750 μM 0−200 μM 0−15 mM 0−13 mM

6 30 16 15 17 31 19 34 24

analytes Fe3+ 3+

Ca2+ Fe3+ Ca2+ Cu2+ Na+ K+

range

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS

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REFERENCES

We thank T. Jayakumar, Baldev Raj, S. C. Chetal, and P. R. Vasudeva Rao for fruitful discussions. J.P thanks the Board of Research Nuclear Sciences (BRNS) for a perspective research grant for the advanced nanofluid development program.

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4. CONCLUSIONS We have developed a novel, inexpensive, ultrasensitive sensor for the detection of biologically important metal ions at parts per million levels using magnetically polarizable emulsion droplets. The sensor produces visually perceptible color changes in the presence of metal ions as a result of changes in the lattice periodicity of the 1D array of droplets. The alteration of the diffuse electric double layer in the presence of cations causes a large blue shift in the diffracted λmax. The concentration of the metal ions is found to be directly proportional to the shift in λmax. This approach is capable of recognizing different metal ions such as Na+, K+, Cu2+, Ca2+, and Fe3+. Because the emulsion used is easy to produce, inexpensive, portable, and allows the rapid detection of several metal ions, our new approach should become a versatile tool for metal ion recognition. The current efforts are aimed at engineering the properties of magnetically polarizable drops to improve their visual detection capability and specificity.

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ASSOCIATED CONTENT

S Supporting Information *

Force measurement apparatus schematics, photograph of the force measurement facility, force measurement working principle, nanoparticle characterization data (XRD, TGA, VSM, DLS, TEM, SAXS, and FTIR), phase contrast microscopic image nanoemulsions with and without a magnetic field, force−distance profiles for Na+ and Ca2+, Bragg peak for different time intervals, Bragg Peak wavelength as a function of time for the sensor at 90 G, and Bragg peak for different concentrations of Na+ and the corresponding Bragg peak shift. This material is available free of charge via the Internet at http://pubs.acs.org. 4257

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dx.doi.org/10.1021/la400502b | Langmuir 2013, 29, 4252−4258