Promoting Intra- and Intermolecular Interactions in Surface

Review pubs.acs.org/ac

Promoting Intra- and Intermolecular Interactions in SurfaceEnhanced Raman Scattering Wenjing Xi, Binaya K. Shrestha, and Amanda J. Haes*

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Department of Chemistry, University of Iowa, Iowa City, Iowa, 55242 United States noise because only 1 photon out of 109 incident photons undergoes Raman scattering.1,2 Additionally, Raman scattering cross sections are small (10−29−10−31 cm2/sr) compared to typical fluorescence cross sections (10−16 cm2/sr) or infrared cross sections (10−21 cm2).3−7 To overcome this difference in cross section and deem Raman scattering an effective detection method, enhancement processes such as resonance Raman or SERS are used. SERS, in particular, is a surface sensitive technique that utilizes nanoparticles to increase molecular signals by 2−9 orders of magnitude, which allows picomolar to single molecule detection.8 Various experimental and theoretical studies have been carried out to understand the mechanisms of SERS, which arise from both chemical and electromagnetic mechanisms.1,9 These mechanisms include (A) ground state chemical enhancement that arises from chemical interactions between a molecule and nanoparticle, (B) resonance Raman enhancement that results when the excitation energy is in resonance with the molecular HOMO to LUMO transitions and selectively increases some vibrational modes of dye molecules, (C) charge transfer effects resulting from excitation energy in resonance with molecule− nanoparticle charge transfer transitions observed in molecules with π-systems, and (D) plasmon enhancement resulting in strong electromagnetic fields when the excitation energy is in resonance with the localized surface plasmon resonance (LSPR).9,10 The first three processes (A to C) are often grouped under chemical enhancement mechanisms, which contribute up to 2 orders of magnitude in signal enhancement11−14 and is a short-range ( 1) or unfavorability (n < 1) of intermolecular interactions involved in the adsorption process. Note that, if n = 0, Langmuir assumptions apply. For example, the adsorption of 1 nM to 2 mM vitamin B9 to Au nanospheres was monitored using SERS and modeled using the Hill equation.177 The cooperative constant that was estimated was less than 1 thus indicating slightly unfavorable binding conditions, a valuable detail in SERS sensor design. Adsorption Kinetics and SERS. Before molecules adsorb to a SERS substrate, molecules must first approach the interface of interest. The rate at which transport occurs depends on the Brownian motion of molecules in bulk solution, electrostatics and/or steric forces between the analyte and surface, transport mechanisms at the interface, and the adsorption and desorption of analytes at the interface.192 As a result, time-dependent adsorption processes can be extracted from SERS data.81,178,187,193 Typical kinetic models used are summarized in Table 3 and include the pseudo-first order188−190 and timedependent Langmuir models.187 The time-dependent Langmuir model, for instance, relates the ratio of a SERS intensity at any time (t) and a maximum SERS intensity to surface coverage and an adsorption rate constant.187 In so doing, adsorption rates and, as a result, the rate at which SERS signals are observed have been shown to depend on medium,171 surface potential,194 and molecule protonation state.178 Clearly, intermolecular interactions play an important role in these rates. For instance, the adsorption mechanism of thiophenol to gold varies with pH.178 To evaluate this, various vibrational bands in SERS spectra for thiophenol were 136

DOI: 10.1021/acs.analchem.7b04225 Anal. Chem. 2018, 90, 128−143

Analytical Chemistry

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Figure 8. (A) Time-dependent SERS responses (temperature = ∼2 °C) showing the interaction of thiophenol with a Au substrate at pH (1) 2, (2) 6, and (3) 10. Schematic diagram of the proposed reaction mechanisms at pH (B) > 6 and (C) < 4. (D) Activation energy as a function of pH. Reproduced from Tripathi, A.; Emmons, E. D.; Christesen, S. D.; Fountain, A. W., III; Guicheteau, J. A. J. Phys. Chem. C 2013, 117, 22834−22842 (178). Copyright 2013 American Chemical Society.

thiophenol and thiophenylate molecules in solution becomes less favorable,197 once again demonstrating how analysis of SERS data reveal important intermolecular interaction contributions.

monitored as a function of time and pH (Figure 8A). To understand these data, the protonation state (i.e., pKa) of thiophenol must be considered. Because the pKa is 7, ∼0.001%, 9.1%, and 99.9% of thiophenol is present as thiophenolate at pH 2, 6, and 10, respectively. As a result, rates of adsorption vary. For instance, SERS signals for all vibrational modes associated with thiophenol are not observed initially for samples incubated at pH 2 and 6 but then maximize in intensity within 2 h. In contrast, signals are measured immediately for the sample incubated in the pH 10 solution, but intensities saturated after 4 h. This indicates that two mechanisms of adsorption are at play at pH 2 and 6 (fast transport to the surface followed by slow deprotonation and fast adsorption kinetics, Figure 8C) and one relatively slower chemisorption step at pH 10 because of slow transport (Figure 8D).178 Quantification of the data in Figure 8 suggest that firstorder adsorption kinetics are promoted at pH 10 while the Prout-Tompkins model195 is best used at the lower pH values. The time-dependent Prout-Tompkins model196 is as follows: θ(t) = (1 + e−k(t − t0))−1 where θ is the fraction of molecules that have adsorbed to the metal (proportional to SERS intensities), k is the adsorption rate constant, and t0 is an integration constant which is associated with the delay time. As a result, multiple “reaction” steps are supported and likely arise from variations in intermolecular processes at the metal surface. Finally and regardless of adsorption mechanism, rate constants estimated using time-dependent kinetic models can be used to quantify activation energies (Ea) of adsorption using the Arrhenius equation. These data for the same system are summarized in Figure 8D. At pH 10, a covalent bond readily forms between thiolate and gold; thus, the activation energy is ∼32.7 kJ/mol. As pH decreases and the fraction of molecules that are protonated increases, the total activation energy for all

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INTRA- AND INTERMOLECULAR INTERACTIONS INFLUENCE SERS MEASUREMENTS SERS is a powerful technique for both detecting molecules quantitatively and qualitatively and for developing an understanding of local environmental impacts on an analyte.198,199 Recall that SERS detection is impacted by other molecules and/or ions present in solution because of intra- or intermolecular forces.200,201 Usually, intramolecular interactions exist within a molecule as ionic, covalent, and metallic bonds while intermolecular interaction occur between molecules and include ion−ion, ion−dipole, dipole−dipole, and induced dipole−induced dipole interactions.86 Both intra- and intermolecular forces can either increase or decrease molecular polarizability thus influencing their normal Raman and SERS spectra. As such, this section focuses on how these forces influence SERS-based sensors. Chelation Interactions for the Realization of pH Sensors. Both SERS intensities and vibrational frequencies are sensitive to pH.200 Thus, pH measurements are possible using SERS with readout generally being based on pH-induced changes in vibrational mode frequencies202,203 and/or SERS intensities.204−209 Common pH sensitive molecules with unique vibrational fingerprints that chemisorb to metals210 are used and include 4-mercaptobenzoic acid (4-MBA),211 4aminobenzenethiol (4-ABT),212 and 2-aminothiophenol (2ABT).213 4-MBA is, by far, the most widely used pH reporter molecule200,214 because its carboxylic acid group exhibits a 137



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observed upon strong cation−carboxylate group coordination.221 Control studies were performed to understand SERS intensity changes to pH (Figure 9D). Here, the relative intensities of the COO− symmetric stretching mode were plotted with respect to the intensity of ring breathing mode in benzene as a function of pH and sample matrix (intracellular mimic (IC), cell culture medium (CM), PBS, DI water, and phosphate citrate (PC) buffer). Relative intensities collected from IC and CM, both of which contain Mg2+ and Ca2+, are larger in magnitude than those observed in the other solutions. Accurate and precise measurements, as a result, are only possible if both cation−carboxylate intermolecular interactions and pH are considered. Weak Intermolecular Interactions Influence SERS Sensors. Intermolecular interactions including hydrogen bonding222 and induced dipole−induced dipole interactions223 can significantly impact SERS signals of adsorbed molecules by influencing molecular electronic structure198,224 and/or surface orientation.223,225,226 For instance, the impact of hydrogen bond formation between 4-MBA and the amine group in aniline on SERS spectra is shown in Figure 10A.201 Upon varying aniline concentration, both SERS spectral lineshapes and intensities associated with 4-MBA changed. This is surprising given the concentration of bound 4-MBA was held constant. Important changes, however, are noted. First, the inplane ring breathing and C−S stretching mode intensity, which is centered at 1075 cm −1 , nearly doubles as aniline concentration was increased from 0.1 nM to 10 mM (Figure 10B). Second, the frequency of this same vibrational band redshifts ∼6 cm−1 upon identical aniline concentration changes. This red-shift is likely caused by hydrogen bond formation,227 thus facilitating both electron cloud redistribution in 4-MBA and charge transfer between 4-MBA and the silver nanoparticles.201 Charge transfer between adsorbed analytes and metals are most evident by evaluating b2 vibration modes in SERS spectra.201,228,229 For instance, the 1572 cm−1 (a b2, totally nonsymmetric CC) band from 4-MBA exhibits intensities that are proportional to aniline concentration. This observation is consistent with increased hydrogen bonding between aniline and 4-MBA, which perturbs the LUMO of 4-MBA. Similar effects were also reported between p-aminothiophenol and benzoic acid.230 SERS responses are influenced by intermolecular forces existing between analytes and other molecules as already highlighted as well as between identical analytes. For instance,223 restructuring of 4′-(pyridin-4-yl)biphenyl-4-ylmethanethiol (4-PBT) was promoted via π−π interactions as shown in Figure 10C-1,-2. This dense thiolated SAM forms over ∼6 h. During this time, the vibrational frequency of the intense aromatic CC stretching mode red-shifts from 1600 to 1596 cm−1 because of π−π stacking. These intermolecular interactions cause the CC force constant to decrease, which causes the vibrational frequency to red-shift. Impacts of longer incubation times reveal a subsequent blue-shift in this same vibrational mode (Figure 10D). This change is hypothesized to arise from SAM restructuring, which includes repulsive forces between adjacent molecules223 such as the electron-rich nitrogen lone pairs and benzene rings.231 These intermolecular interactions are classified as repulsive dipole−dipole forces232 and undergo minimization with increased incubation times (Figure 10C-2,-3). While these effects are subtle, these intermolecular interactions can lead to changes in SERS

surface pKa ranging from 4.5 to 7, common for biologically and environmentally relevant samples.215 For instance, a SERS-based pH sensor using 4-MBA has been developed for monitoring living cells200,216 and for studying enzymatic reactions.217 An example of this is shown in Figure 9A200 where a 4-MBA functionalized gold substrate was used to

Figure 9. (A) pH-dependent SERS spectra of 4-MBA on gold in PBS with pH from 4.0 to 9.0. The intensity of the symmetric νCOO− mode at ∼1420 cm−1 varies with (B) pH and (C) cation composition (10 mM, pH = 7). (D) pH calibration curves for different solution media. Reprinted from Biosensors and Bioelectronics, Vol. 73, Sun, F.; Zhang, P.; Bai, T.; Galvan, D. D.; Hung, H.-C.; Zhou, N.; Jiang, S.; Yu, Q. Functionalized Plasmonic Nanostructure Arrays for Direct and Accurate Mapping Extracellular pH of Living Cells in Complex Media Using SERS. pp. 202−207 (200). Copyright 2015, with permission from Elsevier.

map the extracellular pH (pHe) of single living cells. These SERS spectra show that the COO− symmetric mode is observed at ∼1420 cm−1 from deprotonated molecules (Figure 9B) while the CO symmetric stretching band is located at 1690 cm−1 and arises from protonated molecules. Two trends are noted. First, the COO− band intensity increases with increasing pH. This result is consistent with expected pH impacts on molecular protonation state. Second, the vibrational band frequencies of this same mode blue-shift from ∼1400 to ∼1425 cm−1 as pH increases. Others have observed similar trends.218 As such, we hypothesize that intermolecular forces between benzene rings impact the spectral location of this pH sensitive vibrational mode.219 It is well-established that metal ions including Ag+, Cu2+, Fe2+, Hg2+, Pb2+, Zn2+, and Cd2+ are found in many biological samples and form complexes with carboxylates. These intermolecular interactions can be observed in Raman spectra, which are sensitive to cation composition.220 For instance, the effect of K+, Na+, Ca2+, and Mg2+ complexation to carboxylate species influence the COO− symmetric stretching mode. As shown in Figure 9C, Ca2+ and Mg2+ cause this band to blueshift and increase in intensity even though pH for all measurements was 7. These changes in SERS data indicate the polarizability of COO− varies upon chelation to cations. More pronounced blue-shifts in vibrational frequency are 138



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bisboronic acid235 have been used to improve selective binding of glucose via cyclic boronate intermolecular interactions even in the presence of mannose, galactose, sucrose, and fructose. These innovative approaches for promoting some and reducing competing intermolecular interaction must be continued to improve selective interactions and SERS detection of molecules. A second opportunity and challenge related to intra- and intermolecular interactions in SERS arises from spectral variations from inherent changes in molecular polarizability and surface orientation upon direct and surface chemistrypromoted interaction with SERS substrates236 as well as impacts of varying and distance-dependent electric field strengths that a molecule experiences. Because of these changes, statistical methods such as chemometrics237 can be used to improve accurate interpretation of SERS spectra.235 These approaches, for instance, were applied to the SERS detection of eight foodborne pathogens238 as well as to identify changes in molecular speciation arising from pH changes.239 A third approach that promotes desired intra- and intermolecular interactions between analytes and SERS substrates is via the use of “surface-cleaning agents”. Halides, which are smaller than most analytes240 and covalently bind to gold,159 can be used to facilitate molecular adsorption through this mechanism by displacing residual stabilizing agents on a SERS substrate. This approach is commonly used for singlemolecule detection of Rhodamine-6G where molecules such as citrate are cleaned from a surface with halides for successful detection.240 These cleaning methods can also lead to variations in protonation states of stabilizing agents. These charge variations can also promote direct interactions between the metal surface and analyte thus promoting the SERS effect. A fourth challenge that must be considered is that intra- and intermolecular interactions can lead to degradation and/or flocculation of the nanostructures used in SERS. Degradation, for instance, can lead to changes in nanostructure, which influences the plasmonics and surface energy of the materials. These lead to variations in SERS enhancements and spectral intensities, as well as adsorption energies and probabilities. These effects can reduce the accuracy and reproducibility of SERS-based nanosensor responses.180 Experimental design parameters that influence these dynamic degradation and flocculation changes include pH and ionic composition of the solution. Methods that help control these intermolecular interaction-induced changes can aid in assay design.126,241 Finally, analyte transport mechanisms to SERS substrates242 as a function of local composition 243 and nanostructure morphology244 are also influenced by intermolecular interactions. These also influence spectral variations in SERS measurements and should be considered in designing SERS assays. All in all, opportunities exist in SERS measurements by considering how intra- and intermolecular interactions facilitate analyte adsorption to SERS substrates. These play an important role in the three-dimensional volume where SERS processes occur. As such, the examples highlighted in this Review summarized these interactions and provided explanations of why and how SERS spectral features could be impacted. Future considerations of these will further improve the reproducible and robust detection of molecules using this very surface sensitive technique.

Figure 10. Intermolecular forces influence SERS. (A) Schematic of how Ag nanoparticles conjugated with 4-MBA bind to aniline. (B) SERS intensity (in-plane ring breathing + ν (C−S)) from 4-MBA vs aniline concentration. (C). Schematic of phase transitions during the assembly of 4-PBT on gold from (1) low to (2) high coverages and (3) upon restructuring. Blue rectangles represent benzene and pyridine rings. (4) Spectra of the aromatic CC stretching mode of 4-PBT adsorbed on the Au surface as a function of adsorption time. Panels A and B are reproduced from Wang, Y.; Ji, W.; Sui, H.; Kitahama, Y.; Ruan, W.; Ozaki, Y.; Zhao, B. J. Phys. Chem. C 2014, 118, 10191−10197 (201). Copyright 2014 American Chemical Society. Panels C and D are reproduced from Wang, X.; Zhong, J.H.; Zhang, M.; Liu, Z.; Wu, D.-Y.; Ren, B. Anal. Chem. 2016, 88, 915− 921 (223). Copyright 2016 American Chemical Society.

spectral variations and, if considered, can improve accurate detection using SERS.

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OUTLOOK AND OPPORTUNITIES SERS is a highly sensitive and selective method for detecting low concentrations of analytes, and as highlighted in this Review, intra- and intermolecular interactions must be considered for rigorous interpretation and analysis of SERS spectra. Both chemisorption and physisorption can promote analyte−SERS substrate interactions; however, challenges still exist for molecules that exhibit weak affinity to SERS-active metals. Accurate quantification and selective binding of a weak binding molecule such as glucose from blood or urine is often limited using SERS because of competitive and preferential interactions of other molecules such as uric acid, ascorbic acid, and acetaminophen to SERS substrates thus prohibiting glucose detection.233 This is because amine group-containing uric acid and acetaminophen form weak covalent bonds to metals whereas glucose does not. Nanoparticle functionalization with molecules such as 4-mercaptophenylboronic acid234 and 139



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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Tel: 319-384-3695. ORCID

Wenjing Xi: 0000-0003-1284-2056 Amanda J. Haes: 0000-0001-7232-6825 Author Contributions

The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. Notes

The authors declare no competing financial interest. Biographies Wenjing Xi earned both B.S. and M.S. degrees in Pharmaceutical Engineering from East China University of Science and Technology and is currently a Ph.D. candidate in the Chemistry Department at the University of Iowa under the direction of Prof. Amanda J. Haes. Her research focuses on improving the detectability of low concentrations of small molecules in complex samples using novel materials design and understanding how solution composition and molecular adsorption influences the quantitative and reproducible SERS detection. Binaya K. Shrestha earned his Ph.D. in 2015 from the Department of Chemistry at the University of Iowa under the supervision of Amanda J. Haes. His graduate work focused on innovative nanomaterials design for SERS. Currently, he is the Instructional Services Manager at the University of Iowa where he collaborates with faculty on instructional design, for laboratory teaching assistant training, and in the oversight of upper level chemistry laboratory course operations. Amanda J. Haes is an Associate Professor in the Chemistry Department and Associate Director of the Nanoscience and Nanotechnology Institute at the University of Iowa. She earned her Ph.D. in Chemistry at Northwestern University with Richard P. Van Duyne (2004) and her B.A. in Chemistry and Physics from Wartburg College (1999). Before beginning her independent career, she was a National Research Council Research Associate with Greg E. Collins at the U.S. Naval Research Laboratory (2004−2006). Prof. Haes and her group members focus their research efforts on a number of key issues related to nanoscience and nanotechnology including understanding nanomaterial design and measuring and modeling how intermolecular forces influence interfacial phenomena in plasmonics and SERS, as well as applying these materials and understanding to biological, chemical, dental, environmental, and radiological applications and/or sensors.

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ACKNOWLEDGMENTS This work was funded by the National Science Foundation, (CHE-1707859).

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