Elucidating Molecular Structures of Nonalkylated and Short-Chain

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Elucidating Molecular Structures of Nonalkylated and Short-Chain Alkyl (n < 5, (CH2)n) Aromatic Compounds in Crude Oils by a Combination of Ion Mobility and Ultrahigh-Resolution Mass Spectrometries and Theoretical Collisional Cross-Section Calculations Arif Ahmed,† Yunju Cho,† Kevin Giles,‡ Eleanor Riches,‡ Jong Wha Lee,§ Hugh I. Kim,§ Cheol Ho Choi,*,†,∥ and Sunghwan Kim*,†,∥ †

Kyungpook National University, Department of Chemistry, Daegu, 702-701 Republic of Korea Waters Corporation, Manchester, U.K. § Pohang University of Science and Technology, Pohang, 790-784, Republic of Korea ∥ Green-Nano Materials Research Center, Daegu, 702-701 Republic of Korea ‡

S Supporting Information *

ABSTRACT: Ultrahigh-resolution mass spectrometry has allowed the determination of elemental formulas of the compounds comprising crude oils. However, elucidating molecular structures remains an analytical challenge. Herein, we propose and demonstrate an approach combining ion mobility mass spectrometry (IM-MS), ultrahigh-resolution mass spectrometry, and theoretical collisional cross-section (CCS) calculations to determine the molecular structures of aromatic compounds found in crude oils. The approach is composed of three steps. First, chemical structures are suggested based on the elemental formulas determined from ultrahigh-resolution mass spectra. Second, theoretical CCS values are calculated based on these proposed structures. Third, the calculated CCS values of the proposed structures are compared with experimentally determined CCS values from IM-MS data to provide proposed structures. For proof of concept, 31 nonalkylated and short-chain alkyl (n < 5, (CH2)n) aromatic compounds commonly observed in crude oils were analyzed. Theoretical and experimental CCS values matched within a 5% RMS error. This approach was then used to propose structures of compounds in selected m/z regions of crude oil samples. Overall, the combination of ion mobility mass spectrometry, ultrahighresolution mass spectrometry, and theoretical calculations was shown to be a useful tool for elucidating chemical structures of compounds in complex mixtures.

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chemical formulas can be helpful in understanding and predicting the chemical and physical properties of these oils.17 The next step in understanding the chemical composition of crude oil is the acquisition of structural information from the elemental formulas provided by ultrahigh-resolution mass spectrometry. This is important because knowing the chemical structures of these compounds helps in understanding their chemical reactivity. Toward this end, many techniques, such as comparison of data obtained with different ionization methods,18 double bond equivalence distributions,19,20 planar limit or compositional boundary methods,21−23 tandem mass spectrometry,24−26 and atmospheric pressure photoionization

eople in modern society are critically dependent on energy for many things, including food, transportation, electricity, and temperature control. Crude oil is one of the most important energy sources in the world. However, crude oil is generated by a process requiring millions of years and is therefore considered a nonrenewable energy source. Thus, replacing crude oil with renewable energy sources is one of the most important modern research topics. However, no alternatives have yet been developed which are as cost-effective as crude oil. It is likely that society will remain dependent on crude oil for the foreseeable future. Therefore, enormous research efforts have focused on understanding the chemistry of crude oil, a field known as petroleomics.1−3 In particular, ultrahigh-resolution mass spectrometry has been used to study the chemical compositions of crude oils at the molecular level.4−16 The chemical formulas of thousands of compounds comprising crude oil can be routinely investigated using this technique. Knowledge of these © 2014 American Chemical Society

Received: October 10, 2013 Accepted: March 4, 2014 Published: March 4, 2014 3300

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Table 1. Comparison between Experimental and Theoretical CCS Values of Standard Compounds

standards

exact mass (Da)

1 -naphthylamine 2-aminoanthracene 1-aminopyrene diphenylamine 2-phenylindole triphenylamine 9-phenylcarbazole L-methyl-2-phenylindole N-methyldiphenylamine acridine 7-methylquinoline carbazole anthracene naphthalene biphenyl phenanthrene fluoranthene pyrene 1 -phenylnaphthalene benz[b]anthracene chrysene tetramethyl-anthracene perylene 9-phenylanthracene benzo[ghi]perylene indeno(1,2,3-cd)pyrene 1,2,3,4-dibenzanthracene pentacene coronene 9,10-diphenylanthracene rubrene 4-butylaniline

143.07 193.09 217.09 169.09 193.09 245.12 243.11 207.11 183.11 179.07 143.07 167.07 178.08 128.06 154.08 178.08 202.08 202.08 204.09 228.09 228.09 234.14 252.09 254.11 276.09 276.09 278.11 278.11 300.09 330.14 532.22 149.12

formula

experimental CCS (Å2)

theoretical CCS with Sigma (Å2)

ΔΩ(exp.‑theo.(Sigma))%

theoretical CCS with Mobcal in PA mode (Å2)

C10H9N C14H11N C16H11N C12H11N C14H11N C18H15N C18H13N C15H13N C13H13N C13H9N C10H9N C12H9N C14H10 C10H8 C12H10 C14H10 C16H10 C16H10 C16H12 C18H12 C18H12 C18H18 C20H12 C20H14 C22H12 C22H12 C22H14 C22H14 C24H12 C26H18 C42H28 C10H15N

73.58 83.76 87.48 80.80 84.30 98.40 96.06 88.35 84.22 78.88 73.19 77.57 73.63 62.59 69.72 74.05 79.39 78.83 82.86 84.48 85.84 92.62 88.71 94.82 92.52 94.52 96.95 97.82 97.64 116.68 158.44 77.60

65.67 82.06 84.13 77.36 83.47 98.56 95.52 87.56 81.29 76.24 67.38 72.52 77.04 61.79 71.89 76.11 81.95 80.10 85.83 92.54 90.50 98.50 93.39 99.05 97.51 100.49 104.91 108.17 101.59 121.46 163.41 77.24

10.76 2.04 3.83 4.25 0.98 −0.16 0.56 0.89 3.48 3.35 7.94 6.51 −4.63 1.28 −3.11 −2.78 −3.22 −1.61 −3.58 −9.54 −5.43 −6.35 −5.28 −4.46 −5.39 −6.32 −8.21 −10.58 −4.05 −4.10 −3.14 0.46

67.71 83.23 84.90 79.02 84.68 99.09 96.26 88.32 82.73 77.78 69.50 74.39 78.69 64.11 73.72 77.61 83.21 81.41 87.03 93.16 91.05 98.72 93.7 99.34 97.49 100.45 104.52 107.75 101.35 120.19 157.98 78.85

(APPI) hydrogen/deuterium exchange,27,28 have been applied to study the chemical structures of crude oil compounds. Ion mobility mass spectrometry (IM-MS) is another promising technique that shows great potential for elucidating the chemical structures of crude oil compounds. The usefulness of IM-MS for this purpose has been demonstrated with biomolecules.29−43 IM-MS has also been applied to study crude oils.44−48 In IM-MS studies involving proteins and peptides, theoretical calculations played an important role in finding connections between IM-MS measurements and chemical structures.38,39,49 However, the potential of combining theoretical calculations and IM-MS analyses for the elucidation of crude oil compounds has not been fully explored. For an example, the combination of theoretical calculation and IM-MS to characterize saturated, unsaturated, and aromatic fatty acid compounds was done previously.46 However, the approach has not been used to characterize compounds in complex mixture such as crude oils. This study examined the potential of combining theoretical and experimental results using standard compounds commonly found in crude oils and in an actual crude oil sample.

ΔΩ(exp.‑theo.(PA))%

theoretical CCS with Mobcal in EHS mode (Å2)

ΔΩ(exp.‑theo.(EHS))%

7.98 0.64 2.95 2.20 −0.46 −0.70 −0.21 0.04 1.77 1.39 5.04 4.10 −6.87 −2.43 −5.74 −4.81 −4.81 −3.27 −5.03 −10.27 −6.07 −6.59 −5.63 −4.77 −5.37 −6.27 −7.81 −10.15 −3.8 −3.01 0.29 −1.61

69.64 85.92 87.66 82.08 87.50 106.44 101.44 91.33 87.07 80.24 71.70 76.91 81.07 65.84 75.78 79.96 86.24 83.91 91.12 96.21 93.9 103.84 96.57 104.17 100.69 104.35 108.02 111.54 104.87 129.73 177.45 82.37

5.36 −2.57 −0.20 −1.59 −3.80 −8.17 −5.60 −3.38 −3.38 −1.73 2.03 0.85 −10.1 −5.19 −8.69 −7.98 −8.63 −6.44 −9.97 −13.88 −9.39 −12.11 −8.86 −9.86 −8.83 −10.4 −11.42 −14.03 −7.4 −11.18 −12 −6.15

Standard compounds were dissolved in toluene (Burdick & Jackson ACS/HPLC) to a final concentration of 10 μM. The list of standard compounds and their structures used in this study is provided in the Supporting Information (Table S-1). A sample of Doba crude oil was dissolved in toluene at 0.5 mg/ mL. Detailed information regarding the Doba sample is provided in Table S-1 in the Supporting Information. Mass Spectrometry Analyses. IM-MS experiments were performed with a Waters Synapt G2-S HDMS (high-definition mass spectrometer) (Manchester, U.K.). An atmospheric solids analysis probe (ASAP) was used for analyses of the standard compounds. The ASAP was used to more easily and quickly measure multiple compounds. ASAP acquisitions were carried out using a thermal gradient from 100 to 600 °C over 2.5 min. ASAP-specific instrumental parameters were as follows: corona current 10 μA, sample cone voltage 30 V, source temperature 120 °C, nitrogen cone gas flow 0 L/h, and nitrogen desolvation gas flow 800 L/h. The crude oil sample was analyzed using APPI, and acquisitions were carried out by infusion using a syringe pump (Harvard, Holliston, MA) at a flow rate of 30 μL/min. APPI-specific instrumental parameters were as follows: repeller voltage 2.5 kV, sample cone voltage 40 V, probe temperature 400 °C, source temperature 110 °C, nitrogen cone gas flow 10 L/h, and nitrogen desolvation gas flow 800 L/h. The ion mobility and time-of-flight (TOF) MS instrumental

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EXPERIMENTAL SECTION Sample Preparation. All of the standards used in this study were purchased from Sigma-Aldrich (St. Louis, MO). 3301

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the correlation factors (R2) = 0.998 and lowest standard error implying n = 6 to be the best number of basis functions.

parameters were as follows: trap collision energy (CE) 4 V, transfer CE 2 V, argon trap/transfer collision gas flow 2 mL/ min, helium cell gas flow 180 mL/min, nitrogen IMS gas flow 90 mL/min, resulting IMS cell pressure 3.4 mbar, IMS traveling wave height/velocity (ASAP acquisitions) 40 V/930 m/s, IMS traveling wave height/velocity (APPI acquisitions) 25 V/750 m/s, TOF acquisition range 100−1000 m/z. The Synapt G2-S HDMS was operated in W mode (R ∼ 32 000 [m/Δm0.5]) for both the standard compounds and the crude oil measurements. W mode was used to achieve highest resolving power possible with IM-MS. The additional resolving power was necessary to compare IM-MS spectra with ultrahigh-resolution data. Experimental collisional cross-section (CCS) values were obtained using a polyalanine calibration. The same crude oil sample was analyzed using a 12-T solariX Fourier transform ion cyclotron resonance mass spectrometer (FTICR MS, Bruker Daltonik GmbH, Bremen, Germany) fitted with an APPI source. The prepared samples were directly injected with a syringe pump (Harvard, Holliston, MA) at a flow rate of 300 μL/h. Nitrogen was used as both the drying (250 °C, 4.5 L/min) and nebulizing (400 °C, 1.3 L/min) gas. A capillary voltage of 1000 V was used, with the skimmer voltage set to 18.0 V to minimize in-source fragmentation. Spectra were acquired with a 4-MW transient size, and the signal-to-noise ratio (S/N) was enhanced by summing 300 time-domain transients. The transient length was approximately 2.7 s. External calibration by use of an arginine cluster in the ESI mode was done and internal calibration of the positive-ion mass spectra was performed using Data Analysis 4.0 with an S1 homologous series in (+) mode. Theoretical Calculations. Two levels of theoretical calculations were performed. First, initial molecular structures were created using Chem3D Ultra (CambridgeSoft Corporation, MA) or MacMolPlt50 software. The structures were optimized in accordance with density function theory (DFT) using a B3LYP/6-31G(d)51 base set. Calculations were carried out using the general atomic and molecular electronic structure system (GAMESS).52 Second, CCS values of the compounds with optimized geometries were calculated using Sigma53,54 and Mobcal.55,56 The Lennard-Jones potential was used for the CCS calculations. CCS values were calculated 50−100 times, and the values reported herein are averages of these replicates. CCS Calibration. With the T-Wave, the following modified Mason-Schamp equation could be used to describe the relationship between CCS (ΩD) and drift time (td).45,57 z Ω D = 0.5 Atd B μ (1)

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RESULTS AND DISCUSSION Variation of CCS Values with Functional Group. A total of 31 standard compounds commonly found in crude oils and 5 standard compounds with long alkyl chains (n ≥ 5, (CH2)n) were analyzed using a commercial IM-MS to obtain experimental drift times. The standard compounds are listed in Tables 1 and 2. The obtained drift times were converted into Table 2. Comparison between Experimental and Theoretical CCS Values of Long Alkyl Chain Containing Standard Compounds

CCS values according to the drift time vs CCS calibration as described in the Experimental Section (refer to Figure S-1 in the Supporting Information). The CCS values of the standard compounds are listed in Tables 1 and 2. To observe the changes in CCS with changes in various functional groups, plots were constructed from CCS and mass values from a group of compounds, shown in Figure 1. The solid lines indicate the best fit curves to the experimental points, obtained using a least-squares method. The corresponding line equations and R2 values are noted in the plots. Plots were generated for series of compounds differing by the number of peri-condensed aromatic rings (Figure 1a), the number of linearly fused aromatic rings (Figure 1b), the linear addition of benzene groups (Figure 1c), and alkyl chain length (Figure 1d). It is important to note that the plots showed good linearity with R2 values ranging between 0.9983 and 0.9999. It is also important to note that the slopes of these linear ranges gradually increased from parts a to d of Figure 1; this indicates that a smaller change in CCS per unit mass is observed with the addition of condensed structures relative to that observed with the addition of alkyl chains. In the series of condensed structures, the generation of a more condensed form resulted in the least change in CCS per unit mass. Therefore, the data presented in Figure 1 show that IM-MS can be used to distinguish structural differences between polyaromatic hydrocarbon (PAH) compounds commonly found in crude oils. Comparison of Experimental and Theoretical CCS Values of Nonalkylated and Short-Chain Alkyl (n < 5, (CH2)n) Aromatic Compounds. Calculated CCS values are listed in Table 1. The percent deviation of the theoretical values

where μ is the reduced mass, μ = (Mi Mn)/(Mi + Mn), and Mi and Mn are the masses of the analyte ion and the neutral drift gas, respectively. z is the ion charge, and A and B are constants. Therefore, to obtain a calibration curve, (ΩDμ0.5/z) values were plotted versus tc and then fitted to a power law function of the form Y = AXB to obtain A and B. A calibration curve was generated using reported CCS values of polyalanine.58 The resulting calibration curve and curve fit are provided in Figure S-1 in the Supporting Information. Deconvolution of Ion Mobility Spectrum. The deconvolution of ion mobility spectra was performed with Gaussian functions using Peakfit 4.12 (Systat Software Inc., CA) without baseline correction. Different numbers of basis functions (n) were tested. Among trials with moderate number of basis functions, 4 ≤ n ≤ 7, n = 6 showed the highest value of 3302

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Figure 1. Plots show the changes in CCS as a function of the number of (a) peri-condensed aromatic rings, (b) linearly fused aromatic rings, (c) the linear addition of benzene groups, and (d) alkyl chain length.

Comparison of Experimental and Theoretical CCS Values of Aromatic Compounds with Long Alkyl Chains (n > 5, (CH2)n). Experimental and theoretical CCS values for the optimized structures of aromatic compounds with long alkyl chains (1,4-didecylnaphthalene, 1,6-diheptylpyrene, 9,10diheptylanthracene, 3-octylperylene, and 1,4-didecylbenzene) are listed in Table 2. The percent difference between the experimental and theoretical values ranged from 14.6 to 28.0%, and the RMS variation of the difference was 22.2% (see Table 2). Overall, the differences observed between experimental and theoretical values were much larger for the compounds listed in Table 2 than those listed in Table 1. The large discrepancy between these two groups of compounds can be attributed to the greater flexibility of the longer alkyl chains. Nonalkylated and short-chain alkyl (n < 5, (CH2)n) aromatic compounds have rigid structures with consequently smaller variation in CCS, which depends on conformational changes. In contrast, structures containing long alkyl chains are inherently more flexible, resulting in greater conformation variability, which translates into increased CCS variability. To provide further evidence for this hypothesis, CCS values were calculated for molecules with conformations at local energy minima but not at global energy minima. The resulting structures and energy differences are presented in Figure S-2 in the Supporting Information. The calculated CCS values for molecules with conformations at local energy minima showed better agreement than those obtained at global energy minima (refer to Figure S-2 in the Supporting Information). For

from the experimental values was calculated by the following equation. %deviation =

(experimental CCS − theoretical CCS) theoretical CCS × 100

(2)

The % deviations between the experimental and theoretical values obtained with three methods are listed in Table 1. The root-mean-square (RMS) variation observed between the theoretical and experimental values using the Sigma software package was 4.53%. The analogous RMS variation obtained using the Mobcal package with projection approximation (PA) was 3.96%, and the variation obtained using the exact hard spheres scattering model (EHS) was 4.24%. Therefore, CCS values of nonalkylated and short-chain alkyl (n < 5, (CH2)n) aromatic compounds can be theoretically predicted within a 5% error. It should be noted that predictions for individual molecules can be much less accurate. Table 1 shows that theoretical calculations made with the Mobcal package with PA resulted in CCS values closest to the experimental values. However, the differences between values obtained with each method were not significant. In addition, calculations performed with the Mobcal package were more expensive than the equivalent calculations obtained with the Sigma package. Therefore, the Sigma package was used to calculate the CCS values presented hereafter. 3303

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elemental compositions corresponding to specific peaks, and the Synapt G2-S HDMS instrument can provide drift times containing structural information for these same peaks. We propose that theoretical CCS calculations can play an important role in finding the link(s) between these two types of information. FTICR MS data provide proposed chemical structures based on elemental formulas. Various structures can be drawn from a given elemental formulas provided by FTICR MS data. The following criteria were used for the selection of structures. First, structures with previously reported motifs were mainly used. For example, it is well documented that phenanthrene, naphthalene, benzene, and saturated cyclic rings are important structural motifs for crude oil compounds.59−69 Therefore, the structures with the structural motifs were mainly selected and used in this study. Second, when similar structures exist the one with lower thermodynamic energy was selected. Because crude oils have been generated by process requiring millions of years, it is reasonable to expect that thermodynamically more stable isomers would be preferred. On the basis of the criteria suggested above, structures can be suggested and drawn from elemental formulas. Examples are shown in Figure 3a and are listed in Table 3. The structures considered but not finally selected for Figure 3a are provided in the Supporting Information (refer to Table S3). The peak assigned as C23H26 can be attributed to compounds containing core structures of a phenanthrene unit and one saturated ring (labels 2 and 4 in Table 3), a naphthalene with saturated rings (labels 1 and 3 in Table 3), or a benzene ring and a naphthalene ring connected with a C−C bond (labels 5 and 6 in Table 3). Next, CCS values for these proposed structures are theoretically calculated as described in the previous section. Calculated CCS values for proposed structures are given in Table 3. Finally, these calculated CCS values were compared with experimentally determined CCS values from IM-MS data. This comparison is pictorially explained in Figure 4. Drift time spectra containing information about the target elemental compositions can be extracted from IM-MS data. Extracted drift time spectrum is displayed in Figure 4. The drift time, on the x-axis, can be converted to CCS values using the calibration curve generated from polyalanine standards. For easier comparison between the experimental and theoretical CCS values, the drift time spectrum was deconvoluted and the resulting six peaks were also shown in Figure 4. The deconvolution was used for interpretation of IM-MS spectra to study conformation of ubiquitin ions.55 Judging from CCS values, peaks 3 and 4 in Figure 4 matched well with labels 2 and 3 compounds shown in Table 3. Peaks 1, 5, and 6 could match with labels 1, 4, and 5 compounds in Table 3. Therefore, the comparison between the experimental and theoretical CCS values suggests that compounds with elemental formulas of C23H26 were more likely to have core structures containing a phenanthrene unit and one saturated ring (labels 2 and 3 in Table 3) than were the other structures shown in Table 3. Therefore, this comparison narrows down the number of likely structures associated with the observed peaks. The relative energies of the compounds, obtained from DFT calculations, are listed in Table 3. It is important to note that the most likely structures (labels 2 and 3 in Table 3) exhibit lower energies than the other proposed structures. It is important to note that the structures shown in Table 3 are not the only ones matching the molecular formula. Other

example, the CCS value of 1,4-didecylnaphthalene with its alkyl chains folded as in a local energy minimum (top figure in Figure S-2a in the Supporting Information) is around 167 Å2, and the percent deviation from the experimental CCS value (156 Å2) is 7.3%. However, the CCS value of the same molecule with an unfolded conformation as would occur in a global energy minimum is about 196 Å 2 with a deviation of 26%. The data presented in Figure S-2 in the Supporting Information show that CCS values of molecules with long alkyl chains cannot be calculated based solely on the most stable structures. Further study with additional standard compounds is required to obtain more accurate CCS calculations on compounds containing long alkyl chains. Application to Real Sample Data. The same crude oil sample was analyzed by (+) APPI Synapt G2-S HDMS and (+) APPI FTICR MS. The drift diagram and regular mass spectra obtained from the (+) APPI Synapt G2-S HDMS experiments are displayed in Figure 2a. The time domain and m/z domain

Figure 2. Spectra were obtained from Doba crude oil using an (a) APPI Synapt HDMS and (b) APPI FTICR MS. The time domain signal acquired with the FTICR MS is shown as an inset.

(+) APPI FTICR MS spectra are also shown in Figure 2b. A resolution (m/Δm50%) of ∼30 000 at m/z 400 was achieved for crude oil data obtained with a Synapt G2-S HDMS, and a resolution of 600 000 was obtained for FTICR MS data. Expanded spectra showing the vicinity of m/z 302 and 398 are presented in Figure 3a,b. The mass errors of the peaks shown in expanded mass spectra are listed and provided in the Supporting Information (Table S-2). Spectra obtained with the (+) APPI Synapt G2-S HDMS and those obtained with the (+) APPI FTICR MS showed similar peak distributions. This similarity was also observed in other m/z ranges. Therefore, a comparison of the spectra in Figure 3 shows that the information provided by these two types of mass spectrometers can be compared. Thus, FTICR MS spectra can provide 3304

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Figure 3. Examples of expanded spectra from Doba crude oil are shown in the vicinity of m/z (a) 302 and (b) 398. Spectra were obtained with an APPI Synapt HDMS (top row) and an APPI FTICR MS (bottom row), both showing similar peak distributions.

Table 3. Relative Energy and Theoretical CCS Values of Structures Drawn from Elemental Formulae Shown in Figure 3a

Figure 4. Plots compare experimental and theoretical CCS values for the structural assignments of a C23H26 peak observed in the Doba crude oil spectra.

with significant different core structures. It is because the current IM-MS and calculation techniques may not be able to distinguish the trivial isomers The peak in the vicinity of m/z 398 is also given as an example in Figure S-3 of the Supporting Information. The same procedures as those described above were employed, and the most likely structures were suggested. The examples in Figure 4 and Figure S-3 in the Supporting Information show that theoretical CCS calculations can be used to find links between (+) APPI Synapt G2-S HDMS and (+) APPI FTICR MS data, thereby enabling structural elucidation.

trivial isomers that are unlikely to affect the cross section substantially (such as moving a methyl group to various positions on the ring) may be included in complex crude oils. This study is intended to differentiate only the other isomers 3305

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CONCLUSIONS This study demonstrates that the combination of IM-MS, ultrahigh-resolution mass spectrometry, and theoretical calculations can be a useful tool for elucidating the molecular structure of aromatic compounds comprising crude oil. Optimizing these theoretical CCS calculations and employing advanced methods such as molecular dynamic simulations49 can further improve calculational accuracy. It should be noted that the structure elucidation described in this study is limited to nonalkylated compounds and compounds with short alkyl chains (n < 5, (CH2)n). However, further studies employing a greater number of standard compounds would enable predictions for molecules containing longer alkyl chains. In addition, the procedure used herein to determine molecular structures was manual. The development of software that can automatically assign structures based on the mass spectrometry and calculational data would greatly expand the capabilities of this procedure.

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ASSOCIATED CONTENT

S Supporting Information *

Additional information as noted in text. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected]. *Phone: 82-53-950-5333. Fax: 82-53-950-6330. E-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was supported by the Ministry of Knowledge Economy (MKE, Korea) and by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korean government (MEST). This work was also supported by a NRF (National Research Foundation of Korea) Grant funded by the Korean Government (Grant NRF-2011-Fostering Core Leaders of the Future Basic Science Program).

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