Anionic Functionalized Gold Nanoparticle Continuous Full Filling

Dec 28, 2011 - Published online 28 December 2011. Published in print 7 February 2012. +. Altmetric Logo Icon More Article Metrics. Chemical & Engineer...
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Anionic Functionalized Gold Nanoparticle Continuous Full Filling Separations: Importance of Sample Concentration Michael R. Ivanov and Amanda J. Haes* Department of Chemistry, University of Iowa, Iowa City, Iowa 52242, United States S Supporting Information *

ABSTRACT: Electrically driven separations which contain nanoparticles offer detection and separation advantages but are often difficult to reproduce. To address possible sources of separation inconsistencies, anionic functionalized gold nanoparticles are thoroughly characterized and subsequently included in continuous full filling capillary electrophoresis separations of varying concentrations of three small molecules. Citrate stabilized gold nanospheres are functionalized with 11-mercaptoundecanoic acid, 6-mercaptohexanoic acid, or thioctic acid self-assembled monolayers (SAMs) and characterized using dynamic light scattering, extinction spectroscopy, zeta potential, and X-ray photoelectron spectroscopy prior to use in capillary electrophoresis. Several important trends are noted. First, the stability of these anionic nanoparticles in the capillary improves with increased ligand packing density as indicated by a ratio of absorbance collected at 520 to 600 nm. Second, increasing nanoparticle concentration from 0 to 2 nM (0−0.0025%, w/w) minimally impacts analyte migration times; however, when higher nanoparticle concentrations are included within the capillary, nanoparticle aggregation occurs which induces separation inconsistencies. Third, analyte peak areas are most significantly impacted as their concentration decreases. These trends are attributed to both sample enrichment and electrostatic interactions between the anionic carboxylic acid functionalized gold nanoparticles and sample. These important findings suggest that sample concentration-induced conductivity differences between the sample matrix and separation buffer as well as SAM packing density are important parameters to both characterize and consider when nanoparticles are used during continuous full filling separations and their subsequent use to enhance spectroscopic signals to improve in-capillary analyte detection limits.

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of how nanoparticles can be used to improve the detection of trace molecules. Nanoparticles are also known to impact separations as a function of composition,23−28 concentration,16,29 plug length,18 shape,6,30 size,6,31,32 and/or surface chemistry.16,22,29 For instance, functionalized gold nanoparticles underwent aggregation at nanomolar concentrations when used in capillary electrophoresis.16 When aggregation occurred, separation reproducibility and efficiency decreased. Furthermore, baseline noise increased, thereby reducing detection sensitivity. While interesting results were previously garnered from separation and detection perspectives, a thorough investigation of how nanoparticle surface chemistry and sample concentration impact detection was not performed. In this study, gold nanoparticle surface chemistry and concentration are thoroughly characterized and then included in continuous full filling capillary electrophoresis separations of three small molecules (i.e., dopamine, epinephrine, and uric acid). Citrate stabilized, spherical gold nanoparticles are (1) functionalized with 11-mercaptoundecanoic acid (solution pKa = 4.6−5.0),33 6-mercaptohexanoic acid (solution pKa = 4.8),34

ne promising use of nanoparticles involves their inclusion in separations including capillary electrophoresis.1−7 In these electric field-driven separations, nanoparticles are typically bound to the capillary wall,8−14 included as a pseudostationary plug (i.e., partial filling),15−18 or added as a buffer component (i.e., continuous full filling).10,13,17,19 The incorporation of nanoparticles with capillary electrophoresis offers many detection and separation efficiency advantages. Previously, biocompatible lipid nanoparticles were used to promote the separation and detection of proteins.20,21 When a 2% w/w nanoparticle concentration was included, both the protein concentration and capillary surface area were low relative to that of the nanoparticles. As a result, the nanoparticles provided a large biocompatible surface area for the proteins, the adsorption of proteins to the capillary was subsequently suppressed, and the previously undetectable proteins were not denatured yet easily separated and detected. This approach was speculated to lead to complex biological sample analysis without adverse side effects (i.e., protein denaturization). In another example, citrate stabilized gold nanoparticles were used to preconcentrate indoleamines from solution prior to capillary electrophoresis-based separations.22 Detection limits for the targeted molecules increased by a factor of ∼4000 relative to experiments which did not include nanoparticles. Both of these examples highlight the importance © 2011 American Chemical Society

Received: August 26, 2011 Accepted: December 28, 2011 Published: December 28, 2011 1320

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Table 1. Summary of Ligand, Functionalized Gold Nanoparticle Properties, and Gold Nanoparticle Properties in Electrically Driven Separations

a

Reference 33. bReference 34. cReference 35.

hypothesized to arise from (1) ∼150-fold sample enrichment in the capillary thereby decreasing sample detection limits by the same magnitude and (2) electrostatic interactions between the anionic carboxylic acid functionalized gold nanoparticles and analytes. These important findings suggest that nanoparticle concentration and sample concentration, as well as SAM packing density and identity are important parameters to both characterize and consider when metal nanoparticles are used during continuous full filling separations and subsequently consider when simultaneously exploiting the nanoparticle properties for surface enhanced spectroscopic detection.

or thioctic acid (solution pKa = 4.75 −5.3)35 self-assembled monolayers (SAMs) and (2) thoroughly characterized prior to use (Table 1). Notably, these investigations reveal the role of anionic gold nanoparticles during continuous full filling separations. First, nanoparticle stability (i.e., tendency to not flocculate) in the capillary improves with increased ligand packing density. Second, increasing nanoparticle concentration from 0 to 2 nM (0−0.0025 %, w/w) minimally impacts analyte migration times. These trends diminish as nanoparticles aggregate within the capillary. Third, analyte peak areas are most significantly impacted as their concentration decreases (for a fixed nanoparticle concentration). These trends are 1321

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EXPERIMENTAL SECTION

voltage. Methods utilized for data analysis are included in Supporting Information.



Materials. Gold(III) chloride trihydrate (HAuCl4), trisodium citrate dihydrate (citrate), 6-mercaptohexanoic acid (6MHA), thioctic acid (TA), 11-mercaptoundecanoic acid (11MUA), dopamine hydrochloride (DA), epinephrine (EP), and uric acid (UA) were purchased from Sigma Aldrich. Sodium dihydrogen phosphate dihydrate, sodium phosphate dibasic heptahydrate, sodium hydroxide (NaOH), ethanol, hydrochloric acid (HCl), and nitric acid (HNO3) were purchased from Fisher Scientific. Ultrapure water (18.2 MΩ cm−1) was obtained from a Barnstead Nanopure System (Dubuque, IA) and used for all experiments. Fused silica capillary (internal diameter = 75 μm, outer diameter = 360 μm) with an external polyimide coating was purchased from Molex Corporation. Carboxylic Acid Functionalized Gold Nanoparticle Synthesis and Characterization. Citrate stabilized nanoparticles were synthesized using an established procedure16 and subsequently characterized using dynamic light scattering (DLS), extinction spectroscopy, flocculation (parameter) evaluation, transmission electron microscopy (TEM), zeta potential measurements, and X-ray photoelectron spectroscopy (XPS). Complete details can be found in Supporting Information. Buffer, Sample, and Nanoparticle Solution Preparation. A stock 250 mM sodium phosphate buffer (∼16 mS cm−1, pH 7.3) was prepared from phosphoric acid and sodium phosphate and pH adjusted with concentrated NaOH. A 5.5 mS cm−1, pH 7.3, separation buffer (30 mM sodium phosphate buffer) was prepared by diluting the 250 mM stock buffer. All buffers were filtered (0.2 μm filters, Whatman) and degassed prior to use. Stock (5 or 50 mM) solutions of dopamine and epinephrine were prepared in 10 mM HCl. A 5 mM uric acid solution was prepared in 10 mM NaOH. To prepare sample aliquots, all three analyte stock solutions were mixed and diluted in 10 mM HCl. Sample 1 contained 1× sample concentrations, sample 2 contained 2× sample concentrations, sample 3 contained 4× sample concentrations, and sample 4 contained 6× dopamine and epinephrine and 8× uric acid concentrations (where 1× = 1.56 μM dopamine, 1× = 1.56 μM epinephrine, and 1× = 0.78 μM uric acid). The preparation and determination of gold nanoparticle concentration is included in Supporting Information. Capillary Electrophoresis. All separations were performed using a Beckman Coulter P/ACE MDQ capillary electrophoresis instrument equipped with a deuterium lamp and either UV or photodiode array (PDA) detection. The instrument was utilized per manufacturer recommendations at all times. UV detection occurred at 200 nm, and PDA detection occurred at both 520 and 600 nm. The capillary temperature was maintained at 25 °C. The total capillary length was 60.2 cm with a 50 cm effective separation length. The capillary was conditioned using the following procedure: 0.1 M HNO3 (20 psi for 5 min), H2O (20 psi for 2.25 min), 1 M NaOH (20 psi for 2.25 min), H2O (20 psi for 2.25 min), 250 mM sodium phosphate buffer (20 psi for 3 min), and 30 mM sodium phosphate separation buffer (either with or without nanoparticles) depending on the experiment (20 psi for 3 min). Analyte and nanoparticle samples were hydrodynamically injected into the capillary at 1 psi for 5 s, and separations were performed using normal polarity and a 20 kV separation

RESULTS AND DISCUSSION Characterization of Anionic Gold Nanoparticles. Achieving reproducible separations through the effective use of nanoparticle pseudostationary phases requires electromagnetically and physically stable, homogeneous nanoparticles with size-dependent (i.e., size scale ranging from 1 to 100 nm) chemical and/or physical properties which can be tracked during separations.7 For example, plasmonic nanoparticles exhibit localized surface plasmon resonance (LSPR) spectra, a size-dependent property in which electromagnetic fields arise at nanoparticle surfaces.36,37 The LSPR of noble metal nanoparticles is dictated by composition, shape, and size as well as local dielectric environment.38,39 When correlated with structural and surface properties, LSPR spectra provide detailed information regarding the ultimate function of nanoparticles. The ligand properties and characterization of gold nanoparticles functionalized with (A) 11-MUA, (B) 6-MHA, and (C) TA (termed Au@MUA, Au@MHA, and Au@TA, respectively) are summarized in Table 1. A more complete discussion of these results and their analysis are included in Supporting Information. Four important characteristics are noted. First, nanoparticle diameter (d = 12.7 ± 1.1 nm) as determined using TEM does not vary significantly upon SAM formation or composition. Second, ligand density is quantified using XPS and LSPR spectroscopy. Both techniques indicate that ligand density increases with increasing SAM length40 and/ or decreasing binding moiety size.41,42 As a result, the slightly different extinction maximum wavelengths (λmax) and shifts in extinction maximum wavelengths (Δλmax) upon molecular binding are a result of changing surface chemistries (i.e., local refractive index changes). Third, the carboxylated terminal groups on the surface bound ligands are deprotonated. As a result, all nanoparticles are anionic at pH 7.3. This surface charge is quantified using zeta potential measurements. Alkanethiols such as 11-MUA are known to exhibit increased ligand packing densities versus relatively shorter (i.e., six carbon alkanethiol) SAMs.39 As the alkanethiol chain length increases, SAM uniformity improves while zeta potential becomes more negative. Finally, as ligand packing density increases, the hydrated nanoparticle diameter decreases (DLS). This suggests that the double layer surrounding the nanoparticle is more compact (as with Au@MUA nanoparticles) than surrounding nanoparticles with relatively lower SAM packing densities (Au@TA). This is consistent with previous results43 which suggested that covalently functionalized gold nanoparticle (electromagnetic and physical) stability improves with increased ligand packing density. Evaluation of Anionic Carboxylic Acid Functionalized Au Nanoparticles in Capillary Electrophoresis. The large (2 × 108 M−1 cm−1)44 extinction coefficient at 519 nm of ∼13 nm gold nanoparticles (LSPR) allows their stability (i.e., tendency to not aggregate) to be easily monitored using visible wavelength detection coupled with capillary measurements. Previously, nanoparticle stability (i.e., electromagnetic and physical) was monitored in a capillary using a ratio of nanoparticle absorbance band areas monitored at λ = 520 and 600 nm via dual wavelength PDA detection.16,18 A similar approach is used here to evaluate the LSPR properties at discrete wavelengths associated with Au@MUA, Au@MHA, and Au@TA nanoparticles during electrically driven flow. To 1322

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areas for Au@MHA and Au@TA nanoparticles is consistent with their observed zeta potential values (−18.4 and −20.9 mV, respectively). Au@MUA nanoparticles are relatively more negative (−37.6 mV) in these buffer conditions, a value that likely arises from more densely packed and ordered 11-MUA molecules (4.97 × 1014 molecules/cm2) as compared to the other two SAMs. Finally, nanoparticle peak widths (i.e., Γ) differ significantly among the three functionalized nanoparticle samples (Figure 1A−C). Γ collected at 520 nm are 56, 65, and 100 s for Au@ MUA, Au@TA, and Au@MHA nanoparticles, respectively. These variations are attributed to slight nanoparticle surface chemistry differences such as SAM ordering and/or packing density.39 Because Au@MUA and Au@TA nanoparticles exhibit similar and relatively narrower band widths than Au@ MHA nanoparticles, the uniformity of SAM chain orientation is hypothesized to be more ordered on the first two nanoparticle functionalities vs Au@MHA nanoparticles.39,45 Sample Separations as a Function of Anionic Nanoparticle Concentration. Utilizing nanoparticles in continuous full filling modes1,19 where nanoparticles are included in the separation buffer requires optimization of nanoparticle concentration to produce targeted separation effects while not adversely impacting reproducibility. Because Au@MUA nanoparticles exhibited minimal electrostatic and hydrophobic interactions with the capillary wall, these nanostructures were added to the separation buffer at varying (0, 0.5, 1.0, or 2.0 nM) concentrations (i.e., 0−0.0025 % w/w) and used during the separation of 0.78−15 μM sample concentrations (dopamine, epinephrine, and uric acid) in 30 mM sodium phosphate buffer (5.5 mS/cm, pH 7.3). Several trends are observed in the sample separations (Figure 2A). First, analyte elution order depends on their respective

do this, a nanoparticle plug which occupies 2% of the total capillary volume is injected into the capillary; and an electric field is applied using a buffer that does not contain nanoparticles. Representative electropherograms collected at λ = 520 and 600 nm for 1 nM Au@MUA (Figure 1A), Au@ MHA (Figure 1B), and Au@TA nanoparticles (Figure 1C) are shown and summarized in Table 1.

Figure 1. Representative electropherograms from dual wavelength detection at (1) 520 and (2) 600 nm for a 2% plug (1 psi for 5 s) of 1 nM (A) Au@MUA, (B) Au@MHA, and (C) Au@TA nanoparticles. Electropherograms were obtained using the following conditions: separation voltage = 20 kV using 30 mM sodium phosphate buffer.

The optical properties of the plug of nanostructures reveal important trends. First, a single band is observed at λ = 520 nm for all three functionalized nanoparticles. Second, a less intense band with a similar migration time as the band collected at 520 nm is observed at λ = 600 nm for each SAM functionalized nanoparticle sample. Finally, integrated band area ratios (Area520/Area600) for the three nanoparticle samples are 5.43, 5.24, and 4.66 for Au@MUA, Au@MHA, and Au@TA nanoparticles, respectively. In general, the degree of nanoparticle aggregation decreases as this ratio increases; however, these band area ratios are indicative of highly electromagnetically and physically stable nanostructures (because these ratios are all greater than 4).16 Furthermore, electroosmotic flow mobility was 0.033 cm2V−1min−1 and did not vary significantly when the nanoparticle surface chemistry and/or concentration was modified. Despite these similarities, three significant differences are noted in nanoparticle band (1) migration times, (2) areas and/ or intensities, and (3) full width at half-maximum (Γ) values. For instance, the average migration time of nanoparticle bands collected with the PDA detector range from 14.55, 14.71, and 15.87 minutes for Au@MUA, Au@MHA, and Au@TA nanoparticles, respectively. In capillary electrophoresis, analyte migration time and electrophoretic mobility (μ) are proportional to charge (q) and inversely proportional to the Stokes radius (r). As a result, nanoparticle elution order and migration time depend on effective surface charge (zeta potential) and the hydrated radius of a nanoparticle. Au@MUA nanoparticles exhibit the most negative zeta potential but the relatively smallest hydrodynamic radius. Because Au@MUA nanoparticles exhibit slightly faster mobility vs the other two functionalized nanoparticles, increased SAM packing density is hypothesized to facilitate double layer compression, which reduces the hydrated nanoparticle radii and subsequently increases nanoparticle mobility in these capillary electrophoresis experiments. Second, peak area and intensity differences are clearly noted among the three functionalized nanoparticle bands in Figure 1A−C and Table 1. Despite injecting equal concentrations and volumes of the various anionic nanoparticles, the peak area for Au@MUA nanoparticles is ∼30−35% larger than that for either Au@MHA or Au@TA nanoparticles. The similarity in peak

Figure 2. Separation of analytes as a function of anionic nanoparticle concentration. (A) Representative electropherograms for the separation of samples using separation buffer containing (1) 0, (2) 0.5, (3) 1.0, and (4) 2.0 nM Au@MUA nanoparticle concentrations. (B) Evaluation of migration time changes for (■) dopamine (DA), (red ●) epinephrine (EP), and (blue ▲) uric acid (UA) as a function of Au@MUA nanoparticle concentration. Migration time changes are reported relative to separations performed in the absence of Au@ MUA nanoparticles. Separations were performed using the following conditions: separation voltage = 20 kV, 30 mM sodium phosphate buffer = 7.3, 5.5 mS/cm), and 1× sample concentrations (injected at 1 psi for 5 s).

electrophoretic mobilites and not on the absence or presence of the nanoparticles. In all cases, dopamine eluted first and is followed by epinephrine and uric acid. Second, nanoparticles functionalized with 11-MUA exhibit irreproducible peak areas and migration times when 2 nM Au@MUA nanoparticles are included in the separation buffer. This result is consistent with previously observed covalently functionalized gold nano1323

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particle-based separations which revealed that nanoparticle concentrations greater than ∼2 nM lead to uncontrolled nanoparticle aggregation in the capillary.16 Because gold exhibits size-dependent electrical properties at the nanoscale, gold nanoparticle aggregation leads to irreproducible solution conductivity and separation currents. Third, analyte migration times are only slightly impacted when nanoparticles are included in the separation buffer. As shown in Figure 2, two reproducible observations are noted when nanoparticle concentration is less than 1.5 nM and included in the separation buffer: (1) no significant changes are measured in the migration times for dopamine and epinephrine versus controls; and (2) urate anions migrate 11.94 ± 0.54 seconds more quickly when 1 nM Au@MUA nanoparticles are included in the separation buffer relative to controls. This effect is attributed to repulsive forces between the anionic analytes and anionic Au@MUA nanoparticles.18,46 Finally, sample peak areas vary when nanoparticles are included in the separations. Each biomolecule possesses an inherent pKa value and is hypothesized to uniquely interact with the negatively charged Au@MUA nanoparticles. The extent and nature of the sample−nanoparticle interaction is evaluated vs control experiments (no nanoparticles present). For example, the separation of 4× concentrations (where × = 1.56, 1.56, and 0.78 μM, for dopamine, epinephrine, and uric acid, respectively) are performed in the absence (Figure 3A-1)

increases, the resulting analyte peak area differences are similar to control separations. Several interesting trends are observed in Figure 3. First, peak areas significantly decrease for positively charged dopamine and epinephrine relative to controls. Peak area loss for these molecules are attributed to electrostatic interactions between the negatively charged carboxylic acid terminal groups on Au@MUA nanoparticle surfaces and positively charged molecules.18 As the concentration of dopamine and epinephrine increase, peak area differences between nanoparticlecontaining and control separations decrease and approach baseline noise. Second, peak areas for uric acid increase relative to control separations. As with dopamine and epinephrine, increasing the concentration of uric acid leads to diminished peak area differences between nanoparticle-containing and nanoparticle-free separations. The observed area difference variations are attributed to sample enrichment which occurs when the conductivity of the injected sample is lower than that of the surrounding buffer.47,48 As sample concentrations increase, the effective conductivity of the sample matrix increases and begins to match the conductivity of the separation buffer and these effects are diminished. To quantitatively evaluate analyte area difference trends when 1 nM Au@MUA nanoparticles are included during continuous full filling experiments vs controls, normalized peak areas for dopamine, epinephrine, and uric acid were calculated by integrating the difference analyte peak areas and are shown in Figures S2 and S3-A,-B, Supporting Information, respectively. These dopamine concentration data are fit using a Boltzmann dose−response function to estimate the concentration that causes a 50% change in the signal response. This analysis reveals that the half-response value occurs at 5.53 μM dopamine (see Figure S2, Supporting Information, and Figure 4A). As dopamine concentration increases, analyte peak area

Figure 3. Representative electropherograms (A) for the separation of dopamine, ephinephrine, and uric acid using buffers containing (1) 0 and (2) 1.0 nM Au@MUA nanoparticles and 4× concentrations of each sample. (3) A representative electropherogram difference plot was made by subtracting (1) from (2). (B) Electropherogram difference plots for various sample concentrations performed with a 1.0 nM Au@MUA nanoparticle containing buffer. Samples 1, 2, and 3 contained 1×, 2×, and 4× sample concentrations, respectively while sample 4 contained 6× dopamine and epinephrine and 8× uric acid concentrations (1× = 1.56 μM dopamine, 1× = 1.56 μM epinephrine, and 1× = 0.78 μM uric acid). The separation conditions are identical to those in Figure 2.

and presence (Figure 3A-2) of 1 nM Au@MUA nanoparticle containing separation buffer. To better illustrate how anionic nanoparticles impact analyte bands, a difference electropherogram is included in Figure 3A-3. To account for migration time differences, the time scale was adjusted prior to subtracting electropherograms collected using 0 nM Au@MUA nanoparticles from those with 1 nM Au@MUA nanoparticlecontaining separation buffer. By doing this, differences in electropherograms can be easily observed where negative and positive peaks indicate analyte area loss and gain, respectively. Figure 3B shows difference electropherograms when molecular concentration increases from 1× to 8× concentrations when continuous full filling 1 nM Au@MUA nanoparticle containing separations are performed. As the sample concentration

Figure 4. Nanoparticle−dopamine “titration” curves. (A) Normalized peak area changes for dopamine using (■) capillary electrophoresis (half response = 5.53 μM). (B) Normalized signal changes for (red ●) flocculation and (blue ▲) zeta potential (half response = 820 μM). The data were fit using a Boltzman dose response function. Cartoons are included which visualize what is occurring in the system. 1324

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Analytical Chemistry differences (from difference electropherograms) are eliminated (i.e., the most significant effects are observed for the lowest sample concentrations). For instance, 1× (1.56 μM) dopaminecontaining sample matrixes reveal that analyte peak area decreases by ∼30% relative to controls. Above ∼9 μM dopamine, no observed peak area differences between nanoparticle containing and nanoparticle-free separations are observed as signal differences approach baseline noise levels. These responses are attributed to electrostatic interactions between the sample and the anionic Au@MUA nanoparticle surface.49−52 Similar but less reproducible observations are made (1) in peak area differences for epinephrine (Figure S3-A, Supporting Information) and uric acid (Figure S3-B, Supporting Information) when Au@MUA nanoparticles are used and (2) for all sample peak area differences during continuous full filling experiments that contain either Au@TA (Figure S4, Supporting Information) or Au@MHA (Figure S5, Supporting Information) nanoparticles. In general, these data are not significantly different from control assays. These results are attributed to analyte specific-nanoparticle interaction differences, poor ligand order, and/or reduced SAM packing densities as quantified using zeta potential and XPS. Comparing Capillary Electrophoresis to “Bulk” Au@ MUA Nanoparticle−Dopamine Interactions. To better understand the peak area difference trends in the capillary electrophoresis data as a function of sample concentration, the flocculation and zeta potential of 1 nM Au@MUA nanoparticles upon incubation with 5 × 10−2 − 5 × 10−6 μM dopamine for 1 h are measured (Figure 4). Upon normalizing these dopamine−nanoparticle “titration” responses from 0 to 100% signal change (where 0% and 100% signal represent minimum and maximum changes, respectively), these two techniques reveal similar dopamine concentration-dependent trends but differ from similarly plotted capillary electrophoresis separations. As shown in Figure 4A, the largest peak area changes (100%) in the capillary electrophoresis were observed when ∼1 μM dopamine was included in the sample matrix. As dopamine concentration increases, the magnitude of area variations vs controls decreases. Using the same dose response function as in the capillary electrophoresis measurements, a half-dose dopamine concentration of 820 μM is calculated from both flocculation and zeta potential measurements (Figure 4B). This half-dose response value is 150 times larger than that observed in the capillary electrophoresis measurements (Figure 4A). This suggests that the observations obtained using continuous full filling capillary electrophoresis are dictated by sample enrichment48,53,54 and not nanoparticle aggregation. At low dopamine concentrations, the conductivity difference between the sample matrix and separation buffer is high and sample enrichment occurs. At the half-dose concentration, 150-fold sample enrichment is achieved in capillary electrophoresis because of conductivity differences between the buffer and sample matrix. This lowers the effective limit of detection for dopamine by 150 times in the capillary relative to the bulk measurements at the half-dose concentration. Lowered dopamine detection limits in nanoparticle continuous full filling capillary electrophoresis separations relative to bulk measurements emphasize the promise of these measurements in biological and chemical detection schemes.



CONCLUSIONS



ASSOCIATED CONTENT

Article

In conclusion, gold nanoparticles were functionalized with 6MHA, 11-MUA, or TA and were subsequently characterized using DLS, LSPR spectroscopy, zeta potential measurements, and XPS. These techniques revealed that nanostructures functionalized with 11-MUA were most optically stable (i.e., aggregated the least), a result that likely arose from the superior ligand packing density and order vs the other two SAMfunctionalized nanostructures. Next, the anionic nanostructures were added to separation buffers during the capillary electrophoresis-based separation of dopamine, epinephrine, and uric acid. Buffers containing 1 nM (0.001 2 % w/w) gold nanoparticle concentrations produced the most consistent separations and were used for all subsequent separations. This nanoparticle concentration was sufficiently low, and nanoparticle aggregation was suppressed. For separations performed in the presence of Au@MUA, Au@MHA, or Au@TA nanoparticle containing separation buffers, cationic dopamine and epinephrine electrostatically interacted with the nanoparticle surfaces. These effects depended on SAM packing density and analyte concentrations. Because separations that occurred in the presence of electromagnetically and physically stable Au@MUA nanoparticles were the most reproducible in terms of analyte peak areas and migration times, a 1 nM Au@MUA nanoparticle-containing separation buffer was used to evaluate how dopamine peak area varied with analyte concentration vs nanoparticle-free separations. These data were described using a dose response function and was estimated at 5.53 μM dopamine. Similar Au@MUA nanoparticle and dopamine interaction studies were evaluated with zeta potential and flocculation. The half dose response for both “bulk” measurement techniques was ∼150 times larger (820 μM) than the capillary electrophoresis results. This suggests that sample enrichment (and not nanoparticle aggregation) dictated the responses observed in capillary electrophoresis. Because these effects decreased as sample concentration increased, we hypothesized that sample enrichment was occurring because of conductivity differences between the nanoparticle containing separation buffer and the sample matrix. Importantly, 1 nM gold nanoparticle concentration is dictated by both nanoparticle core properties and surface chemistry but is low in terms of solution percentage, while this concentration is relevant for implementing these materials for enhancing detection but relatively lower than what is typically used in electrically driven separations which include nanoparticles. As a result, future investigations could include (1) other nanoparticle surface chemistries which promote greater nanoparticle stability at higher (up to micromolar) concentrations and (2) other analyte−nanoparticle interactions which could lead to more systematic improvements in the separation and subsequent detection of target biological and chemical species. Consequently, previous and future experiments which utilize similar metal nanoparticles could be better understood and reproducibly exploited for in-capillary analyte detection using capillary electrophoresis and surface enhanced spectroscopic methods.

S Supporting Information *

Complete experimental details and nanoparticle characterization, as well as concentration dependent trends for dopamine, epinephrine, and uric acid in the presence of Au@ 1325

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TA, Au@MHA, or Au@MUA nanoparticles. This material is available free of charge via the Internet at http://pubs.acs.org.



AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Telephone: (319) 3843695. Fax: (319) 335-1270.



ACKNOWLEDGMENTS We thank the Roy J. Carver Charitable Trust and Camille & Henry Dreyfus Foundation for financial support.



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dx.doi.org/10.1021/ac2022376 | Anal. Chem. 2012, 84, 1320−1326