Promoting Intra- and Intermolecular Interactions in Surface-Enhanced

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Promoting Intra- and Intermolecular Interactions in Surface-enhanced Raman Scattering (SERS) Wenjing Xi, Binaya K. Shrestha, and Amanda J. Haes Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.7b04225 • Publication Date (Web): 23 Oct 2017 Downloaded from http://pubs.acs.org on October 25, 2017

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Analytical Chemistry

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

University of Iowa, Department of Chemistry, Iowa City, Iowa Keywords: SERS, Chemisorption, Physisorption, Intramolecular Interactions, Intermolecular Interactions 1.

INTRODUCTION

Normal Raman and surface–enhanced Raman scattering (SERS) are powerful analytical methodologies that are complementary to infrared absorption spectroscopy and provide unique molecular fingerprint information.1 Vibrational energies detected using both techniques arise from quantized energy states associated with the vibrational and rotational motions of molecular bonds. If a molecule exhibits a unique structure, mass, and bond strength; unique energies will appear as vibrational energies shifted from the Rayleigh line in a Raman spectrum. Small changes in the quantized energies can be related to small changes in polarizability that can occur in response to electromagnetic radiation, changes in the local environment, and/or intermolecular interactions. While Raman spectroscopy offers many advantages for molecular detection, this approach is limited by low signal to 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 mechanism 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 resonance effects resulting from excitation energy in resonance to the molecule-nanoparticle charge transfer transitions observed in molecules with π-systems, and (4) plasmon enhancement resulting from strong nanoparticle electromagnetic field 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 (< 2 nm)12,15,16 effect.17-19 As a consequence, the nanoparticle interface plays a key role in the magnitude of chemical enhancement obtained. In comparison, electromagnetic enhancements can exceed 9 orders of magnitude12,16,20 and depend on the large electric fields that form on the surface of a material when a plasmon resonance is induced. In comparison to chemical enhancement effects, higher electromagnetic SERS enhancements are possible because both the incident electric field (E(ω)laser) of the laser light and the scattered Raman (E(ω)Raman) are impacted upon interaction with the LSPR. As such, the total SERS electromagnetic enhancement factor is |Elaser|2∙|ERaman|2. For small Raman shifts, Elaser and ERaman are assumed to be ~equal; therefore, the SERS enhancement scales as a factor of |E(ω)|4.19,21,22 Both SERS mechanisms require that the molecular chromophores interact with the metal interface at short distances. Chemisorption and/or physisorption between these can lead to the observation of SERS signals if surface selection rules are satisfied.23 Molecules with poor affinity to metal often require nanoparticle functionalization or molecule derivatization.23 In some cases, Raman reporters must be used for detection.24 For example, RNA labeled

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with methylene blue was used for indirect nucleic acid sensing. 25 This approach was also used to selectively detect As3+ using 4-mercaptopyridine as a reporter and glutathione for recognition. 26 Challenges with both direct and indirect SERS detection include nanoparticle stability, SERS spectral complexity, and variations in SERS intensities and vibrational frequencies. All of these challenges depend on intra- and intermolecular interactions. As a result, this review focuses on the critical role of intra- and intermolecular interactions in SERS then summarizes recent advances in how these forces can lead to reproducible and robust detection using this highly sensitive analytical technique. Specifically, an overview of general considerations that influence SERS is provided. Next, intra- and intermolecular interactions that influence adsorption and SERS spectral features are considered. Corresponding mechanisms and examples are emphasized. The impacts of these interactions are described in the context of specific sensing examples. Finally, opportunities related to these are provided so that previous advances in chemical27 and biochemical28,29 analysis can be expanded resulting in robust SERS measurements with excellent sensitivity, rapid responses, and low detection limits. 2.

OVERVIEW OF PARAMETERS THAT INFLUENCE SERS SPECTRA

SERS signal intensities depend on many parameters including laser excitation (integration time, power, polarization, wavelength), metallic substrate (composition, dimensionality, uniformity), and intrinsic analyte properties (Raman polarizability tensors, intrinsic Raman crosssections).30 In addition, SERS signals also depend on analyte affinity to and distance from the metal substrate.30 Reviews and books that detail each of these parameters are cited in the above text. One motivator in using SERS as an analytical technique is the large signal enhancements achieved. Although SERS is a powerful method that can be used for single molecular detection,8,31,32 trace chemical analysis is limited by poor reproducibility and small dynamic ranges. An important need to improve the analytical and general performance capabilities of SERSactive substrates must consider how nanoparticle composition and morphology, molecular densities on/near SERS substrates, and SERS mechanisms and selection rules influence the overall performance of these systems. As such, these are discussed in this section. 2.1. Nanoparticle Morphology and Composition The optical properties of noble metal nanoparticles such as copper, gold, and silver are widely exploited for molec-

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ular detection using SERS.33-39 SERS partially relies on the optical properties of noble metal nanoparticles that arise when free conduction electrons in the nanoparticles interact with incident electromagnetic waves. For instance, noble metal nanoparticles with diameters much smaller than the wavelength of light can exhibit a surface plasmon resonance, which is a collective in-phase oscillation of the free electrons within the conduction band of the metal nanoparticle induced by the incident electric field.39-42 If the nanoparticles are small such that the collective oscillation occurs only on a particle surface, the phenomenon is referred to as an LSPR.39,42 The energy and width of LSPR spectral features depend on the free electron density, dielectric medium, and characteristic electron scattering time.40,42 SERS substrates are routinely fabricated and synthesized using lithography, electrodeposition, etching, and bottom-up synthetic techniques. Several considerations of SERS substrates attributes include:1,40 (1) high SERS activity (enhancements approaching 109 vs. normal Raman scattering);43 (2) uniform SERS enhancement (deviations < 20%); (3) substrate stability and reproducibility; and (4) either cost-effective or reusable. For instance, nanolithography provides flexibility in fabricating SERS substrates with diverse shapes, sizes, and spacing (>10 nm)1 that are highly uniform and reproducible44-46 but requires expensive deposition equipment, and the substrate impacts the LSPR of the nanostructures. In contrast, bottom-up synthesized nanoparticles are typically formed through nucleation and growth processes. Materials result from the addition of metal salts to a solution containing a reducing agent such as sodium borohyride, sodium citrate, or alcohols.47-50 Surfactants such as cetryl trimethylammonium bromide (CTAB), poly vinyl pyrrolidone (PVP), or sodium dodecyl sulfate (SDS) can be used as capping agents to prevent aggregation or oxidation of nanoparticles as well as to control growth rates and growth direction. Depending on the solution parameters used and how well nucleation and growth conditions are controlled, targeted shapes and sizes of nanoparticles can be realized.47 The resulting materials can be used as SERS substrates, and their performance depends on nanomaterial component,51 size,52 shape,53 electron density,54 surface chemistry,55 and surrounding medium.56 Anisotropic nanostructures such as nanorods and nanostars show higher SERS enhancements vs. spheres because of the lightning rod effect.57 For instance, gold nanostars with uniform branches and tips were synthesized using a seed and surfactant based method.58 The gold nanostars showed re2


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markable monodispersity in terms of shape, size, and branch symmetry (Figure 1A). When compared to nanostars with less uniform morphologies, the monodisperse nanostars exhibited superior SERS performance (Figure 1B).

tional mode intensities observed in SERS.65 Systematic changes in a SERS signal, as a result, can be correlated to the number of molecules present until molecular saturation occurs.66 Thus, time-dependent changes in SERS signals depend on the dynamics of molecular transport to a SERS substrate and adsorption rates. For a molecule to be detected using SERS, analytes must exhibit favorable binding energies, show non-zero sticking probabilities, and satisfy the selection rules associated with SERS.67 Sticking probability (S), which is the adsorption rate divided by the collision rate, provides a quantitative metric regarding the likelihood that a molecule will collide and remain on an interface.67,68 Sticking probability values are, as a result, related to temporal responses in SERS measurements.68

Figure 1. (A) TEM image of a single symmetric Au nanostar. (B) SERS spectra of 4-mercaptobenzoic acid using (1) symmetric and (2) asymmetric Au nanostars, respectively. Reproduced from Niu, W.; Chua, Y. A. A.; Zhang, W.; Huang, H.; Lu, X. Journal of the American Chemical Society. 2015, 137, 10460-10463 (ref 58). Copyright 2015 American Chemical Society.

Ultimately, the surface concentration (σ, molecules/cm2) of molecules on an initially clean surface is a product of the incident flux (F) and residence time. In general, when molecules approach a SERS substrate, stabilizing interactions increase the residence time (t) an analyte spends at an interface. Residence time can be calculated using the following expression t = t0exp(ΔHads/RT) where ΔHads is the heat of adsorption, t0 is a known vibrational time, and T is temperature.67 This relationship indicates that residence times increase as adsorption energies increase. Thus, molecular surface concentration is proportional to SERS intensity and depends on residence times, heats of adsorption, and flux (depends on initial molecular concentration). In addition, residence time also plays an importance role in adsorption/desorption mechanisms69 because this parameter describes how strongly a molecule adsorbs and how frequently it moves to neighboring sites or into solution after the initial adsorption step.70 Impacts of morphology on residence times have been observed. For instance, average residence times of H2O molecules are at least two orders of magnitude higher on platinum nanocube faces vs. corners indicating water interacts more strong to nanocube faces vs. corners.70

SERS signals are also impacted by inherent materialsdependent electric fields that molecules experience near a metallic surface. These are known as vibrational Stark effects,59 which arise from perturbations in the electronic environment of a chemical bond. As the electromagnetic field strength increases, Stark effects typically lead to blue-shifts in the vibrational frequencies of molecules.60,61 These vibrational frequency variations can be related to the local electric field strength near the metal.62 Examples of these effects have been observed in both SERS and tipenhanced Raman scattering (TERS). For instance, frequency changes in nitrile co-adsorbed to gold with thiophenol was evaluated with SERS and TERS.63 The CN stretching frequency showed significant energy differences upon co-adsorption. Two trends were noted. This stretch shifted to higher frequencies at metal edges and where thiophenol densities were locally high. These effects were verified with TERS. The CN stretch underwent a ~130 cm-1 Stark shift, which was correlated to electric field variations from coupling between the metal surface and tip.63 These effects have also been observed for other alkyl nitriles.64 In all cases, these nanoparticle composition and morphology effects support that locations of vibrational bands observed in SERS spectra can be impacted by electric field strengths. 2.2. Molecular Densities near SERS Substrates The number of molecules in the volumes near SERS substrates and total probe volume impacts the overall vibra-

2.3. SERS Mechanisms and Selection Rules SERS intensities depend on both chemical and electromagnetic enhancement mechanisms, which depend on the distance between a vibrational mode and metal surface.30 The largest contributor to a SERS signal is related to the strong electromagnetic fields near a metal surface, which attenuate as the distance an analyte is from a metal surface increases and extend several nanometers away from the interface.71 Thus, SERS intensities (ISERS) scale inversely with the distance (r) between the chromophore and metal surface and the radius of curvature of the metal surface (a). A commonly used model to describe this de3



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pendence scales71 as 𝐼𝑆𝐸𝑅𝑆 = (

𝑎+𝑟 −10 ) , 𝑎

a model that is well-

supported experimentally. For instance, silica coated gold nanoparticles were prepared with defect-free silica shells with thicknesses varying from 1.5 to 15 nm.72 Once nanoparticles containing silica defects were removed, SERS detection of 2-naphthalenethiol closely followed this theoretical model.72 Similar trends have been observed using carboxylic acid terminated alkanethiols including 3-mercaptoproprionic acid, 6-mercaptohexanoic acid, and 11mercaptoundecanoic acid chemisorbed onto Au nanostars. Quantitative uranyl detection was facilitated via the formation of coordination complexes between uranyl and carboxylate.23 As shown in Figure 2A, similar free ener-

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to the surface are subject to the greatest enhancement effects while parallel components are often not observed. Surface selection rules, as a result, support that analyte orientation at an interface impacts the magnitudes and observation of various vibrational modes.75 For instance, C-H stretching mode intensities of benzene rings, which are not observed when the aromatic ring is parallel to the interface, was used to determine the molecular orientation dependence of benzene, toluene, and benzonitrile at gold-aqueous interfaces.76 Significant differences were noted and can be attributed to differences in intermolecular interactions (vide infra). In addition to surface selection rules, charge transfer between an analyte and metal must also be considered. Charge transfer is related to electronic transitions from filled metal orbitals (near the Fermi level) to unfilled molecular orbitals. These processes depend on the chemical nature and electronic potential of the interface and depend on nanostructure dimensionality and excitation as these both influence the Fermi energy of the metal.77 Recently, both charge transfer and surface selection rules were observed in SERS spectra of 1,4phenylenediisocyanide (PDI) on silver nanoparticles.78 To

Figure 2. SERS detection of uranyl. (A) Uranyl concentration dependent SERS responses using (1) 3mercaptopropionic acid, (2) 6-mercaptohexanoic acid, and (3) 11-mercaptoundecanoic acid functionalized Au nanostars. (B) Relative SERS singals relative to the longest alkanethiol as a function of SAM thickness. A distance dependence model as a function of (1) radius of curvature of the gold nanostar tips and (2) average gold nanostar size. Dotted lines represent propagated errors from TEM measurements. Reproduced from Lu, G.; Forbes, T. Z.; Haes, A. Analyst 2016, 141, 5137-5143 (ref 23), with permission of The Royal Society of Chemistry.

gies of adsorption were calculated using each alkanethiol indicating similar surface-analyte coordination, and the largest SERS signals were observed for the shortest monolayer. Furthermore, the SERS distance dependence scales with the radius of curvature of the nanostar tips as shown in Figure 2B and highlights the importance of both nanoparticle structure and distance dependence in quantitative SERS detection. While SERS intensities scale approximately as the electric field to the fourth power, vibrational mode symmetry and surface selection rules must be considered.73 Surface selection rules were first conceptualized by Moskovits74 to describe how the polarizability of normal modes in a molecule can be selectively enhanced in SERS. In general, changes in molecular polarizability that are perpendicular

Figure 3. (A) Plot of the IC−H/IC-C ratio as a function of PDI concentration using silver, nanoparticles. Depiction of how PDI adsorbs to silver when the PDI concentration is (B) less than 0.1 μM, (C) between 0.1 - 3 μM, and (D) greater than 3 μM. Reproduced from López-Tobar, E.; Hara, K.; Izquierdo-Lorenzo, I.; Sanchez-Cortes, S. The Journal of Physical Chemistry C. 2014, 119, 599-609 (ref 78). Copyright 2014 American Chemical Society. 4


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do this, the relative intensity of the in-plane C-H stretching (3066 cm-1) and C=C stretching (1600 cm-1) modes (ICH/IC-C) were plotted as a function of PDI concentration (Figure 3A). This ratio increased as PDI concentration increased to 0.1 µM PDI, which is consistent with a parallel to perpendicular binding geometry of the molecule with respect to the metal surface (Figure 3B).79 From 0.1-3 µM PDI, charge transfer effects caused this ratio to decrease (Figure 3C). DFT calculations, which support this claim of charge transfer, predict that PDI adsorbed to Au exhibit HOMO and LUMO states at 0.7 and 3 eV, respectively, above the Fermi level of the metal. Furthermore, the energy difference between the LUMO and Fermi level of the metal varies with molecular surface density.79,80 Once the surface is saturated (when more than 3 µM PDI is used), the IC-H/IC-C ratio is stabilizes (Figure 3D). This example supports the importance of enhancement mechanisms and surface selection rules in SERS measurements and spectra. 3.

CHEMISORPTION AND PHYSISORPTION OF MOLECULES TO SERS SUBSTRATES

As discussed previously, SERS depends on the distance between a vibrational chromophore and a metal surface because the electric field induced upon plasmon excitation decays rapidly with increased metal-chromophore distance. In addition to this electromagnetic enhancement, chemical enhancement mechanisms also contribute to the SERS signal if the adsorbate direct interacts with the metal surface.81 These enhancements are closely associated with the binding energy between the analyte and metal.82 In addition, molecules with high surface affinity show the strongest SERS signals if surface selection rules are satisfied.83 A key consideration in SERS measurements is the affinity of a molecule to the metal substrate, which can range from weak physical adsorption to strong covalent or dative bond formation.83 Herein, driving forces that promote molecular adsorption to metal surfaces are classified and discussed. Specifically, mechanisms that facilitate adsorption are summarized in this section with relevant examples, advantages, disadvantages, and their contribution to SERS (Table 1). 3.1. SERS Signals Promoted via Chemisorption Chemisorption is caused by strong perturbations of molecular electronic structure during chemical bond formation with a substrate84,85 and is less influenced by the local environment compared to physisorption.86 Molecules containing functional groups that chemisorb to SERS substrates include thiol,87-89 pyridine,90 amine,91 nitrile,92 and carboxylic acid91 and promote SERS detection

because of strong and direct binding affinity to the metal surface. Furthermore, these molecules are able to replace stabilizing reagents and ions. Thus, molecules containing these functional groups often experience the strongest induced electromagnetic fields at the metal interface. Chemisorption facilitated via thiol-metal bond formation is widely used in SERS applications for both detecting small molecules88,89 and functionalizing nanoparticles.89,93,94 This is because thiols exhibit strong affinity to silver,95,96 gold,68,95,97-99 copper,95 and palladium100,101 by forming dative covalent bonds102 between sulfur and metal atoms. Alkanethiols adsorbed on gold form a tightly packed single molecular layer or self-assembled monolayer (SAM)103 with previously reported associated free energies of adsorption (ΔGads) of -14 kcal/mol at low SAM densities and -7 kcal/mol at higher coverages.104 While the exact mechanism of thiolate bond formation is debated,105-107 sulfhydryl (RS-H) bonds are cleaved upon chemisorption to the surface from a water or other solvent phase such as ethanol.108,109 Some studies suggest thiols deprotonate upon adsorption to gold thus leading to a subsequent decrease in solution pH,105,110 while evidence supporting the production of H2 has also been shown.111 For instance, pH decreased from 6.7 to 4.2 upon SAM formation, and the surface pKa of the thiol decreased vs. the solution value upon covalent bond formation to gold.105 In contrast,110 no significant pH change upon alkanethiol SAM formation was observed for silver nanoparticles. The difference between these two studies could be attributed to binding affinity differences between thiols to gold and silver. Namely, thiols bind more strongly to gold than silver,112 thus deprotonation of thiols on gold occurs more readily. Thiolate molecules bind to silver nanoparticles through reaction with their oxidized surface113 thereby producing RS-Ag and water instead of protons.110 Thus, no pH change in solution is observed, and the resulting insoluble RS-Ag salts either remain on the metal surface or form a precipitate in solution.110,113 Other functional groups form relatively weaker chemisorption interactions to SERS substrates vs. thiol. While relatively weaker in terms of bond strength, nitrogencontaining functional groups bind to SERS substrates through the electron lone pairs on nitrogen.114 Resultingly weak covalent bonds115 typically form and exhibit binding energies between 6-8 and 2 kcal/mol to gold116-118 and silver,116 respectively. Pyridine and nitrile-containing molecules, in contrast, bind to SERS substrates through both nitrogen lone pair electrons and π electrons in the ring.67 These binding interactions change the population of lone 5



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Table 1. Driving forces to promote molecule-metal adsorption Driving Force

Typical Binding 119 Energy (kcal/mol)

Chemical Interactions with Examples

Advantages

Disadvantages

Largely irreversible; Direct adsorption; Shortest distances between analyte and metal

Limited to certain functional group interactions to metals

Long range effect; Promotes charge selectivity

Limited to charged molecules and/or nanoparticles; non-specific interactions

High selectivity

Requires multiple intramolecular interactions

Aids in molecular assembly and 126 orientation

Weak forces that increase adsorbate residence times

120-123

Au/Ag-S Covalent Interaction

50-150

92

Ag-C≡N ; Ag82 aniline/aminobiphenyl -115

Au- COOH/COO

Positively charged silver nanoparticles + negatively 124 charged DNA

Ion-ion Interaction

100-200

Hydrogen Bonding

2-7

OH---O

London Dispersion Forces

1-10

Benzene ring-Au

125

126

pair and delocalized π electrons.127 While the N-Au interaction is weakly covalent, amine-containing molecules chemisorb to SERS substrates and can replace common stabilizing agents such as citrate89 and borohydride.128 For instance, (3-aminopropyl)trimethoxysilane has been shown to displace citrate from gold thus forming silica shells on citrate-stabilized gold nanoparticles.129 In so doing, the vibrational bands associated with citrate are reduced and/or eliminated. Thus, SERS can be used to facilitate small molecule detection by promoting adsorption. In comparison, molecules containing carboxylic acids can also interact with SERS substrates but with much weaker affinities vs. sulfur or nitrogen as indicated by ~2 kcal/mol binding energies.130 This weak interaction has been classified as either physisorption131 or chemisorption. While the binding mechanism of COOH to a metal is not fully understood, both ionic and coordination interactions are hypothesized.115 For instance, 4-aminobenzoic acid was shown to bind to silver via orbital overlap between the π electrons in carboxylate and metal.132 This interaction leads to a 10 cm-1 red-shift in the carboxylate symmetric stretching mode in SERS vs. normal Raman spectra.132 This result is significantly different from studies of benzoic acid on a silver electrode surface where coordination occurs through lone pair electrons on oxygen resulting in a blue-shift of the symmetric COO- stretching frequency.132 This same metal-functional group interaction promotes gold nanoparticle stabilization by citrate

anions. Calculated adsorption energies of this species range from 8-10 kcal/mol,130 which suggests multiple carboxylate interactions to the metal. Clearly, interactions of molecules to a metal surface are important in SERS. For instance, nanoparticle stability and reversible adsorption-desorption processes could be better understood and predicted if the binding affinities of molecules to metals are known.133 Table 2 summarizes previously reported binding energies between molecules and/or functional groups chemisorbed to gold, silver, and copper. All of these chemisorption interactions promote direct functional group-metal interactions and can minimize the distance between analytes and SERS substrates. In addition, the vibrational modes of molecules are not equally enhanced upon adsorption, and SERS spectral features and intensities are also dependent on adsorbate concentration,134 structure,135,136 and orientation. 136,137 Thus, SERS provides information regarding the moleculemetal interface138 and mechanisms of metal-molecule interactions.139 Assuming surface selection rules are satisfied, the vibrational modes from functional groups directly adsorbed to the metal are usually most enhanced, and the associated vibrational frequencies can vary and broaden significantly vs. those observed in normal Raman spectra.140,141 Nitrile (C≡N), for example, binds to metals via σ and π interactions.142 The σ interactions (i.e., end-on binding through nitrogen lone-pair electrons) show minor perturbations in the C≡N stretching mode compared to normal Raman 6


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Analytical Chemistry Table 2. Binding Energies of Molecules Chemisorbed to Au, Ag, and Cu Binding Energy to Metals in

143

Sulfur (exp)

kcal/mol

Hydrogen Sul144 fide (calc)

Other Thiols (calc)

118,145,146

Amine (calc)

116

Carboxylic Acid 130 (calc)

Au

61

19

44 ± 3

8

2

Ag

52

11

NA

5

NA

Cu

66

16

NA

NA

NA

*NA: Not available analysis.147 In contrast, π interactions (i.e., π donation between nitrile and metal) lead to large red-shifts in the C≡N stretching mode frequency as this same bond is weakened upon adsorption.148 Thus, the vibrational frequency of the C≡N stretch can be used to indicate surface adsorption geometry. As an example,92 the adsorption of organic nitriles to silver nanoparticles was evaluated using SERS. As Figure 4 shows, both carboxylate and C≡N groups can interact with silver. Depending on the coordination geometry, the polarizability vector of the molecular vibrational modes can be oriented perpendicular, parallel, or to various degrees between these extremes. Because C≡N stretches are Raman-active and exhibit unique vibrational frequencies, resulting Raman spectra can be used to understand surface coordination. Basic solutions promoted the parallel adsorption of C≡N to the surface.92 This was demonstrated by evaluating the vibrational frequency of the C≡N stretch mode. In normal Raman spectra, this band cen-

Figure 4. Proposed surface geometries of α-cyano-4hydroxycinnamic acid chemisorbed to silver nanoparticles via (A) nitrile and (B) carboxylic acid groups. SERS spectra of the C≡N stretching mode in (1) basic and (2) acidic con-1 ditions. C≡N stretching frequencies at (blue) 2216 cm , which represents nitrile adsorption perpendicular to the -1 surface and at (red) 2188 cm , which represents nitrile oriented parallelly to the surface. Reprinted from Applied Surface Science., Vol. 425, Jung, D.; Jeon, K.; Yeo, J.; Hussain, S.; Pang, Y. Multifaceted Adsorption of Α-Cyano4-Hydroxycinnamic Acid on Silver Colloidal and Island Surfaces, pp. 63-68 (ref 92). Copyright 2017, with permission from Elsevier.

tered at 2217 cm-1 but red-shifts to 2188 cm-1 when molecules adsorb via π overlap to the metal, which is consistent with a parallel adsorption geometry. Upon acidification, the same vibrational band is observed primarily at 2216 cm-1. This vibrational frequency is consistent with the molecules interacting with the metal via σ interactions or a perpendicular binding geometry. Similarly, the vibrational modes associated with carboxylic acid (in acidic conditions) and carboxylate groups (in basic conditions) also exhibit pH and orientation-dependent SERS spectral features.92 The carboxylate stretching mode only appears in basic conditions while vibrational modes representing the protonated structure are not observed in acidic solutions.92 This indicates adsorption occurs via carboxylate interactions to the metal. As demonstrated in these examples, the binding affinities between molecules and SERS substrates depend on functional group protonation. In addition, competition of different adsorbates to SERS substrates must also be considered. According to the relative bond strengths between various stabilizing ligands and nanoparticle surfaces, analytes can displace stabilizing agents such as citrate on gold nanospheres149 or CTAB on gold nanorods.150 These processes can be studied by SERS via analysis of band intensities,134,151 vibrational frequencies,150-152 and vibrational band widths.151,152 For instance, the ligand exchange reaction between CTAB and 4-aminothiophenol (4-ATP) was monitored using SERS.151 The kinetics of gold-thiolate bond formation revealed differences in this displacement reaction as shown in Figures 5A and 5B. The vibrational modes associated with adsorption of 4-ATP and desorption of CTAB are noted via increases in the C-S and C-C stretching mode intensities at 1094 and 1594 cm-1, respectively. These time-dependent changes are highlighted in Figures 5C and 5D. Furthermore, the C-C stretching mode red-shifts from 1601 to 1594 cm-1 and the full width at half maxima (FWHM) of the same bands broadens from 50 to 120 cm-1 over the course of an hour upon chemisorption. These spectral changes are consistent with weakening of the C-C bond strength once the metal7



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silver nanoparticles coated with spermine. In the presence of negatively-charged DNA, nanoparticles aggregate within 2 hours. These clusters are stable in solution for 24 hours as demonstrated in Figure 6B.

Figure 5. (A) Schematic of the ligand exchange process and (B) time-dependent SERS spectra of 4aminothiophenol adsorption on CTAB-stabilized Au nanoparticles. Time-dependent changes in (C) FWHM and (D) vibrational frequency of (1) the mixed ν(C–C) + β(C–H) modes and (2) the fundamental ν(C–C) mode of 4aminothiophenol. Reproduced from DeVetter, B. M.; Mukherjee, P.; Murphy, C. J.; Bhargava, R. Nanoscale 2015, 7, 8766-8775 (ref 151), with permission of The Royal Society of Chemistry.

SERS detection of DNA is usually facilitated using Raman labels,25 but chemical-specific information regarding DNA can also be obtained using direct SERS measurements. For instance, the ring breathing mode of adenine in the DNA backbone is located at 734 and 730 cm-1 for single-stranded sequences (ss1 and ssc) and their corresponding double-helix structure (ds1), respectively. As the molar ratio (R = [ds1]/([ds1]+[ssc])) between ssc and ds1 varying, the ring breathing mode shifts from 730 to 734 cm-1 (Figure 6C). Close evaluation of difference spectra (i.e., dotted line in Figure 6C) reveals a minimum at 724 cm-1 and a maximum at 738 cm-1. The ratio of these intensities (I724/I738) reveals important trends as a function of double-helix (ds1) concentration (Figure 6D). As the molar ratio increases from 0-20%, the intensity ratio also increases. This suggests that DNA duplexes systematically form on the nanoparticle surfaces and demonstrates how

molecule complex has formed. Longer incubation times reveal a subsequent narrowing in FWHM indicating 4ATP molecules are becoming more ordered once most of the CTAB is displaced.94 This occurs until equilibrium in adsorbate composition via chemisorption is reached at which point, no additional changes in SERS spectra are observed. 3.2. SERS Signals Promoted via Physisorption Physisorption is defined as adsorption in which the electronic orbitals of species involved remain unchanged upon interaction with a substrate.84 As such, physisorption involves relatively weaker interactions vs. chemisorption and can be classified as electrostatic, dipole-ion, dipoledipole, or induced dipole-induced dipole (dispersion) interactions. These intermolecular forces and their importance for molecule adsorption onto SERS substrates will be discussed in this section. 3.2.1. Ion-Ion Interactions Influence SERS Detection Ion-ion interactions are long range forces (1 to 100 nm)153 with energies ranging from 100 to 200 kcal/mol 119 and can both attract and repel species. Attraction between two ions is an important driving force that promotes molecule adsorption as this overcomes other weak repulsive interactions that can prohibit observation of a SERS signal for an analyte. Ion-ion interactions between nanomaterials with charged surfaces facilitate label-free SERS analysis of biomolecules such as unmodified DNA.124 Figure 6A shows an example of this in which ion-ion attraction occurs between negatively charged phosphate groups in double-stranded DNA (dsDNA) and positively charged

Figure 6. SERS analysis of DNA duplexes. (A) Diagram of dsDNA sandwiched between two positively charged Ag nanoparticles (AgNPs). (B) Extinction spectra of Ag@spermine nanoparticles (AgNP@Sp) in the (1) absence and presence of dsDNA acquired (2) 2 and (3) 24 h after DNA addition. (C) SERS spectra of a single stranded sequence (SSC) and the corresponding double-helix structure (ds1) mixture at different molar ratios (R = [ds1]/([ds1]+[ssc]; top, R = 0.011 to bottom R = 1). The dotted line is the difference spectrum (ssc – ds1) with a spec-1 -1 tral minimum at 724 cm and a maximum at 738 cm . (D) Ratio of peak intensities I724/I738 vs. R. Reproduced from Direct Surface‐Enhanced Raman Scattering Analysis of DNA Duplexes, Guerrini, L.; Krpetić, Ž.; van Lierop, D.; Alvarez‐Puebla, R. A.; Graham, D. Angewandte Chemie, Vol. 127, Issue 4 (ref 124). Copyright 2015 Wiley


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ion-ion attractions induce energetically favorable intermolecular interactions.124,154,155 Signal irreproducibility, however, can also result from these same interactions because of induced nanoparticle instabilities156,157 thus often limiting this approach to molecular adsorption on SERS substrates to trace, qualitative analysis. In addition to facilitating adsorption on SERS substrates, ion-ion interactions also affect nanomaterial surface potentials.157 Recall that anionic and cationic species can form an electrostatic double layer at interfaces153 thus attracting and repelling counter and co-ions via Coulombic forces.157 Increased electrolyte concentration, for instance, can induce nanoparticle aggregation by reducing nanoparticle surface potentials.157 For instance, gold nanoparticles washed in potassium nitrate were used to detect 1,3-bis(3′-butylimidazolium)-benzene dihalide ((BBIB)X2, X = Cl, Br, I) salts. Both (BBIB)2+ and X-1 features were observed in SERS spectra before and after washing indicating (BBIB)2+ and halides co-adsorb to gold. Because of the lack of spectral changes after washing, electrostatic-induced adsorption of co-ions is a likely interaction mechanism. In another study, (BBIB)I2 underwent competitive adsorption to citrate stabilized gold nanoparticles with adenine. (BBIB)I2 was shown to exhibit a higher binding affinity to gold than adenine because of preferential ion pairing with I-.157 In addition, SERS features of (BBIB)X2 were not observed in (BBIB)Br2 and (BBIB)Cl2 in the presence of adenine because I- binds more readily to gold than either Br- or Cl-.158,159 3.2.2. Hydrogen Bonding Promotes Selectivity in SERS Hydrogen bonding is a unique subset of dipole-dipole interactions86 with bond strengths ranging from 1-9 kcal/mol. 86,119 Hydrogen bonding, while weak, is a short range effect (0.25-0.35 nm)86 that collectively promotes molecular adsorption in SERS. Hydrogen bonding, for instance, is the driving force in antibody-antigen interactions160 as well as in small molecule-artificial antibody couples125,161 (i.e., molecular imprinted polymers (MIPs)). For instance, ~8 hydrogen bonds typically form between the monoclonal antibody 1A1D-2 and its antigen.162 Similarly, multiple hydrogen bonding interactions are designed into artificial antibodies thus providing selective adsorption to SERS substrates.42 While MIPs are designed to bind to target molecules of specific shapes and sizes, hydrogen bonding reduces desorption of target molecules by cooperatively promoting selective recognition.125,161,163166 Disruption of hydrogen bonds can facilitate reuse of these substrates if the regeneration process is successful without degrading or changing the nanostructure morphology and composition.167

Material design is critical for realizing MIP-induced SERS detection. Thus, an overview of MIP design is described here. Briefly, MIPs are fabricated using functional monomers that undergo covalent, electrostatic, and/or hydrogen bonding around template molecules.168 Next, polymerization is induced resulting in a polymer where template molecules are under ideal conditions, uniformly incorporated. Template removal leaves complementary cavities for analyte rebinding and detection. Hydrogen bonds, which are strong enough to collectively promote binding between analytes and polymer and weak enough to be disrupted during template removal, are key attributes of MIP-template interactions and design. To realize the powerfulness of hydrogen bonding in analyte adsorption for SERS detection, Ag substrates were functionalized with a MIP designed to bind to R6G.42 In general, the more hydrogen bonds that form between molecules and a MIP, the stronger the binding affinity.169,170 In this case, five hydrogen bonds could potentially form during R6G binding thus resulting in selective SERS detection and a reusable SERS platform. Five cycles of detection and a demonstrated 0.1 pM limit of detection for R6G were shown.42 One challenge for this approach, however, is that only molecules that were captured in cavities nearest to the SERS substrate contributed to detectable signals because of the distance dependence of SERS. As a result, methods that satisfy this fundamental design requirement of SERS while promoting collective and selective hydrogen bonding interactions could push this technology into new and exciting applications. While hydrogen bond formation can promote molecular adsorption to SERS substrates, these interactions can also prohibit molecule adsorption to metals. Previously, SERS detection of the dye (Bu4N)2[Ru(dcbpyH)2(NCS)2] (N719) using solution-phase gold nanospheres generated strong signals in acetonitrile but not in water.171 N719, which contains thiocyanates171,172 readily undergoes solvation in water. In other words, the electron pairs on nitrogen form preferential hydrogen bonds with water thus decreasing the probability of adsorption to gold.173 In acetonitrile, these solvation effects do not take place so both adsorption of the dye to gold and SERS signal generation readily occur. This example clearly demonstrates that hydrogen bonding interactions between molecules, solvent, and SERS substrates need to be considered when designing a SERS experiment. 3.2.3.

Dispersion Forces Influence SERS Detection

Dispersion (London) forces are induced dipole-induced dipole interactions174 and are the weakest intermolecular forces that can promote SERS. While these forces are not strong enough to promote adsorption directly to SERS


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substrates, dispersion interactions do play an important role in intermolecular interactions between molecules on SERS substrates after adsorption occurs.126 For instance, dispersion interactions can improve adsorbate uniformity by promoting reorganization and similar orientations of molecules on SERS substrates. An example of how dispersion interactions contribute to SERS measurements is shown in Figure 7.126 Here, experimentally estimated tilt angles of benzenethiol, 4-mercaptobenzoic acid, and paminothiophenol adsorbed onto SERS substrates are shown. While all these molecules contain thiol groups that promote chemisorption, this study revealed that benzenethiol adsorbs to the metal with a near perpendicular orientation while 4-mercaptobenzoic acid and paminothiophenol show similar yet more significant tilt angles. Tilt angle differences are attributed to repulsion forces between molecules induced by the functional group in the para positions on the benzene rings, which subsequently lead to slight differences in the number of molecules that can chemisorb. Both 4-mercaptobenzoic acid and p-aminothiophenol, as a result, exhibit stronger dispersion interactions between the molecules and gold and more favorable free energies of adsorption compared to benzenethiol on gold.126,175

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The implications of these slight differences in orientation significantly influence the observed SERS spectra. As shown in the SERS spectra in Figure 7, influences of surface selection rules are noted. First, symmetric CS stretches for benzenethiol, 4-mercaptobenzoic acid, paminothiophenol are centered at 1075, 1077, and 1084 cm-1, respectively. These vibrational frequencies are the most intense feature in all spectra because they are nearest to the metal and differ slightly because of variations in the electron withdrawing ability of the para-substituted functional groups on the benzene ring. Next, the vibrational frequencies associated with the CH in-plane bending mode for the same three molecules are centered at 1021, 1182, and 1175 cm-1, respectively. This as well as the CCC in-plane bending modes are highly sensitive to molecular orientation (i.e., surface selection rules) and are most intense when the polarizability tensor is parallel to the surface normal. As such, these bands are only observed when the benzene rings are approximately perpendicular to the metal surface as observed in the spectrum for benzenethiol. All in all, while London dispersion forces are too weak to promote adsorption directly, these interactions still impact spectral features routinely used for molecular identification. 3.3. SERS Investigations of Thermodynamic and Kinetic Limited Adsorption As discussed in previous sections, chemisorption and physisorption promote SERS detection. As a result, SERS also aids in understanding adsorption processes both kinetically and thermodynamically.176 SERS, for instance, can be used to quantify thermodynamic binding metrics such as adsorption and desorption constants and binding energies as well as kinetic parameters including rate constants and activation energies. These metrics are influenced by analyte surface coverage,104 intermolecular forces,177 and adsorption mechanisms.178 This section summarizes these mechanisms, compares and contrasts their strengths and weaknesses, and provides examples of how relevant models can be used in SERS spectral interpretations.

Figure 7. Surface adsorbed orientations, tilt angles, and SERS spectra for (A) benzenethiol, (B) 4-mercaptobenzoic acid, and (C) p-aminothiophenol. (Yellow = sulfur, black = carbon, blue = hydrogen, red = oxygen, and purple = nitrogen.) Both the surface normal and estimated tilt angle are included. Vibrational mode assignments to the mole-1 cules are as follows: 1075, 1077, and 1175 cm is a combina-1 tion of CS + CC stretching mode; 1021, 1182, and 1175 cm is CH in-plane bending mode; and 998 cm-1 is a CCC inplane bending mode. Reproduced from Lu, G.; Shrestha, B.; Haes, A. J. The Journal of Physical Chemistry C. 2016, 120, 20759-20767 (ref 126). Copyright 2016 American Chemical Society.

3.3.1.

Adsorption Isotherms

Typical quantitative descriptors of adsorption thermodynamic parameters are equilibrium adsorption constants (Keq) and free energies of adsorption (ΔGads = -RT×ln Keq where R is the gas constant and T is temperature),81,178 Four common models including Langmuir,177,179 Freundlich,179,180 Tempkin,181 and Brunauer−Emmett−Teller (BET)182 have been used in SERS studies. These models each exhibit unique assumptions and are summarized in Table 3. For instance, Langmuir adsorption isotherm analysis is one of the most widely used adsorption models and assumes monolayer adsorption, homogeneous


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Analytical Chemistry Table 3. Thermodynamic and Kinetic Adsorption Models Model

Assumptions

181,183

Linearized 183 Equation

183

Isotherm Parameters

References

Ce: equilibrium concentration (mg/L);

Langmuir

Monolayer adsorption; homogeneous surface

Ce/qe = (1/KLQm)+Ce/Qm

qe: amount of adsorbate in the adsorbent at equilibrium (mg/g);

81,177,179,184

Qm (mg/g): theoretical maximum adsorption capacity; KL (L/mg): Langmuir isotherm constant

Freundlich

Multi-layer adsorption; non-uniform distribution

Log qe = log KF + (1/n)log Ce

Tempkin

Uniform distribution; heterogeneous surface

qe = (RT/bT)lnKT + (RT/bT)lnCe

Isotherm

n: adsorption intensity; KF (mg/g): Freundlich isotherm constant

179,180

bT : Tempkin isotherm constant; KT (L/g): equilibrium binding constant

181

Cs: equilibrium concentration (mg/L); Brunauer−Emmett− Teller

Gas–solid equilibrium systems; multilayer adsorption systems

Ce/(qe(Cs- Ce)) = 1/(qsCBET) + (CBET1)Ce/(qsCBETCs)

qs: theoretical isotherm saturation capacity (mg/g); qe: amount of adsorbate in the adsorbent at equilibrium (mg/g);

182

CBET: BET adsorption isotherm relating to the energy of surface interaction (L/mg) Model

Kinetics

Time- dependent first order Langmuir adsorption

Assumptions

185

186

186

Linear Equation

Parameters

Examples

θ: surface coverage of adsorbate relative to its maximum value; No micro- porosity, surface heterogeneity, or lateral interactions

θ(t) =1-exp(-kC0t)

C0: adsorbate initial concentration (mg/L);

187

T: temperature (K); -1

k: rate constant (s ) -1

Pseudo-first order

Rate is proportional to the degree of equilibrium

k1: rate constant (s ); log (qe-qt) = log qe(k1/2.303)/t

surface sites, 1:1 binding between an adsorbate and surface site, and dynamic equilibrium between adsorptiondesorption. Freundlich isotherms follow similar assumptions except that multilayer, non-uniform adsorption is considered. Tempkin models assume that binding energies of adsorbates are coverage dependent. BET, on the other hand, is used to model multilayer adsorption where intermolecular interactions largely influence adsorption. Each isotherm model can be linearly transformed so that isotherm parameters such as equilibrium binding con-

qe or qt: the amount of molecules adsorbed at equilibrium and at various time t (mg/g)

188-190

stants, separation factors, and surface heterogeneity can be quantified. These models are routinely applied to SERS. For instance, calculated free energies of adsorption are used to quantify the binding affinity between molecules and a SERS substrate. The equilibrium constants and Gibbs free energy of adsorption for a series of nitrogen-containing aromatic molecules including 1,2-bis(4-pyridyl)ethylene (BPE), isoquinoline, pyridine, and aniline to gold SERS substrates, for example, were quantified using the Lang-


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muir adsorption isotherm.176 BPE, which contains two pyridine rings, exhibited the most energetically favorable binding energy. Isoquinoline exhibited the next strongest binding affinity and was followed by pyridine then aniline.176 This trend in isotherm parameters is consistent with Au-N bond strengths in these molecules, which are proportional to delocalized electron density. When molecules weakly adsorb to SERS substrates, the Langmuir adsorption isotherm model is an excellent platform for extracting binding metrics from SERS data; however, this commonly used model fails to account for multilayer formation and other intermolecular interactions whereas the Freundlich and Tempkin isotherm models account for how molecule-molecule and moleculesubstrate interactions influence binding metrics. In other cases, the BET model is best used. The adsorption of 2,9dimethylquinacridone onto silver nanoparticles, for example, is best fit using the BET model because of the strong intermolecular driving forces between the molecule to silver.182 In some cases, it is difficult to determine which binding model should be used. As such, the Hill equation can be used to extract quantitative binding metrics by plotting SERS intensities vs. concentration.177 The Hill equation is as follows:191

Page 12 of 33 ISERS =

Imax × Cn Kads + Cn

where Imax is the maximum SERS intensity, C is the analyte concentration, Kads is the equilibrium constant, and n is a cooperative constant. The cooperative constant reveals information regarding the energetic favorability (n > 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 – 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 slight unfavorable binding conditions, a valuable detail in SERS sensor design. 3.3.2.

Adsorption Kinetics and SERS

Before molecules adsorb to a SERS substrate, molecules must be 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, timedependent 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-

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 III, A. W.; Guicheteau, J. A. The Journal of Physical Chemistry C . 2013, 117, 22834-22842 (ref 178). Copyright 2013 American Chemical Society.


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and time-dependent Langmuir models.187 The timedependent 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 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 the 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 hours. In contrast, signals are measured immediately for the sample incubated in the pH 10 solution, but intensities saturate after 4 hours. This indicates that two mechanisms of adsorption are at play at pH 2 and 6 (fast transport to the surface followed by slow deprotonation then fast adsorption kinetics, Figure 8C), and one relatively slower chemisorption step occurs at pH 10 because of slow transport (Figure 8D).178 Quantification of the data in Figure 8 suggest that first-order adsorption kinetics are promoted at pH 10 while the Prout-Tompkins model195 is best used at the lower pH values. The timedependent 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 kinetics 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 thiophenol and thiophenylate molecules in solution becomes less favorable197 once again demonstrating how analysis of SERS data reveal important intermolecular interaction contributions.

4.

INTRA- AND INTERMOLECULAR INTERACTIONS INFLUENCES SERS MEASUREMENTS

SERS is a powerful technique for both detecting molecules quantitatively and qualitatively and for developing an understanding of local environment 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 as ionic, covalent, and metallic bonds while intermolecular interactions include ion-ion, ion-dipole, dipole-dipole, and induced dipole-induceddipole 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. 4.1. 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 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 (4MBA),211 4-aminobenzenethiol (4-ABT),212 and 2aminothiophenol (2-ABT).213 4-MBA is, by far, the most widely used pH reporter molecule200,214 because its carboxylic acid group exhibits a surface pKa ranging from 4.5-7, common for biologically and environmentallyrelevant 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 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+, Cd2+are found in many biologi-


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on-carboxylate intermolecular interactions and pH are not considered. 4.2. Weak Intermolecular SERS Sensors

Interactions

Influence

Intermolecular interactions including hydrogen bonding222 and induced dipole-induce 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 associ-

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 − −1 the νCOO mode at ~1420 cm 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 (ref 200). Copyright 2015, with permission from Elsevier.

cal samples and form complexes with carboxylates. These intermolecular interactions can be observed in Raman spectra, spectra variations 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 blue-shift 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 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 was 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 cati-

Figure 10. Intermolecular forces influence SERS. (A). Schematic of how Ag nanoparticles conjugated with 4MBA 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 Au surface as a function of adsorption time. Figure A and B are reproduced from Wang, Y.; Ji, W.; Sui, H.; Kitahama, Y.; Ruan, W.; Ozaki, Y. The Journal of Physical Chemistry C. 2014, 118, 10191-10197 (ref 201). Copyright 2014 American Chemical Society. Figure C and D are reproduced from Wang, X.; Zhong, J.-H.; Zhang, M.; Liu, Z.; Wu, D.-Y.; Ren, B. Analytical Chemistry 2016, 88, 915-921 (ref 223). Copyright 2016 American Chemical Society.


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ated with 4-MBA changed. This is surprising given the concentration of bound 4-MBA was held constant. Important changes, however, are noted. First, the in-plane 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 vibrational frequency of this same vibrational band red-shifts ~6 cm-1 upon identical aniline concentration changes. This red-shift is likely caused by hydrogen bonds formation227 thus facilitating both electron cloud redistribution in 4-MBA and charge-transfer between 4MBA 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 non-symmetric 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 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-yl)methanethiol (4-PBT) was promoted via π-π interactions as shown in Figures 10C-1 and -2. This dense thiolated SAM forms over ~6 hours. 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 will cause 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 is driven by 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 after longer incubation times (Figures 10C-2 and -3). While these effects are subtle, these intermolecular interactions can lead to changes in SERS spectral variations and if considered, can improve accurate detection using SERS. 5.

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 4mercaptophenylboronic acid234 and 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 binding and SERS detection of molecules. A second opportunity and challenge related to intraand intermolecular interactions in SERS arises from spectral variations from inherent changes in molecular polarizability and surface orientation upon direct and surface chemistry-promoted 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 quantify changes in molecular speciation arising from pH changes.239 A third approach to promoting 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 single-molecule 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


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SERS enhancements, 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 composition243 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.

(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, 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.

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.

* AJH: Email: [email protected], Tel: 319-384-3695

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

AUTHOR INFORMATION Corresponding Author

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

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

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Figure 1. (A) TEM image of a single symmetric Au nanos-tar. (B) SERS spectra of 4-mercaptobenzoic acid using (1) symmetric and (2) asymmetric Au nanostars, respectively. Reproduced from Niu, W.; Chua, Y. A. A.; Zhang, W.; Huang, H.; Lu, X. Journal of the American Chemical Society. 2015, 137, 10460-10463 (ref 58). Copyright 2015 American Chemical Society. 858x434mm (96 x 96 DPI)



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Figure 2. SERS detection of uranyl. (A) Uranyl concentra-tion dependent SERS responses using (1) 3mercaptopropionic acid, (2) 6-mercaptohexanoic acid, and (3) 11-mercaptoundecanoic acid functionalized Au nanostars. (B) Relative SERS singals relative to the longest alkanethiol as a function of SAM thickness. A distance dependence model as a function of (1) radius of curvature of the gold nanostar tips and (2) average gold nanostar size. Dotted lines represent propagated errors from TEM measurements. Reproduced from Lu, G.; Forbes, T. Z.; Haes, A. Analyst 2016, 141, 5137-5143 (ref 23), with permission of The Royal Society of Chemistry. 1468x592mm (96 x 96 DPI)


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Figure 3. (A) Plot of the IC−H/IC-C ratio as a function of PDI concentration using silver, nanoparticles. Depiction of how PDI adsorbs to silver when the PDI concentration is (B) less than 0.1 µM, (C) between 0.1 - 3 µM, and (D) greater than 3 µM. Reproduced from López-Tobar, E.; Hara, K.; Izquierdo-Lorenzo, I.; Sanchez-Cortes, S. The Journal of Physical Chemistry C. 2014, 119, 599-609 (ref 78). Copyright 2014 American Chemical Society. 1024x1056mm (96 x 96 DPI)



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Figure 4. Proposed surface geometries of α-cyano-4-hydroxycinnamic acid chemisorbed to silver nanoparticles via (A) nitrile and (B) carboxylic acid groups. SERS spectra of the C≡N stretching mode in (1) basic and (2) acidic conditions. C≡N stretching frequencies at (blue) 2216 cm-1, which represents nitrile adsorption perpendicular to the surface and at (red) 2188 cm-1, which represents nitrile oriented parallelly to the surface. Reprinted from Applied Surface Science., Vol. 425, Jung, D.; Jeon, K.; Yeo, J.; Hussain, S.; Pang, Y. Multifaceted Adsorption of Α-Cyano-4-Hydroxycinnamic Acid on Silver Colloidal and Island Surfaces, pp. 63-68 (ref 92). Copyright 2017, with permission from Elsevier. 1440x573mm (96 x 96 DPI)


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Figure 5. (A) Schematic of the ligand exchange process and (B) time-dependent SERS spectra of 4aminothiophenol adsorption on CTAB-stabilized Au na-noparticles. Time-dependent changes in (C) FWHM and (D) vibrational frequency of (1) the mixed ν(C–C) + β(C–H) modes and (2) the fundamental ν(C–C) mode of 4-aminothiophenol. Reproduced from DeVetter, B. M.; Mukherjee, P.; Murphy, C. J.; Bhargava, R. Nanoscale 2015, 7, 8766-8775 (ref 151), with permission of The Royal Society of Chemistry. 1391x797mm (96 x 96 DPI)



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Figure 6. SERS analysis of DNA duplexes. (A) Diagram of dsDNA sandwiched between two positively charged Ag nanoparticles (AgNPs). (B) Extinction spectra of Ag@spermine nanoparticles (AgNP@Sp) in the (1) absence and presence of dsDNA acquired (2) 2 and (3) 24 h after DNA addition. (C) SERS spectra of a single stranded se-quence (SSC) and the corresponding double-helix struc-ture (ds1) mixture at different molar ratios (R = [ds1]/([ds1]+[ssc]; top, R = 0.011 to bottom R = 1). The dot-ted line is the difference spectrum (ssc – ds1) with a spec-tral minimum at 724 cm-1 and a maximum at 738 cm-1. (D) Ratio of peak intensities I724/I738 vs. R. Reproduced from Direct Surface‐Enhanced Raman Scattering Analysis of DNA Duplexes, Guerrini, L.; Krpetić, Ž.; van Lierop, D.; Alvarez‐Puebla, R. A.; Graham, D. Angewandte Chemie, Vol. 127, Issue 4 (ref 124). Copyright 2015 Wiley 1075x882mm (96 x 96 DPI)


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Figure 7. Surface adsorbed orientations, tilt angles, and SERS spectra for (A) benzenethiol, (B) 4mercaptobenzoic acid, and (C) p-aminothiophenol. (Yellow = sulfur, black = carbon, blue = hydrogen, red = oxygen, and purple = nitrogen.) Both the surface normal and estimated tilt angle are included. Vibrational mode assignments to the molecules are as follows: 1075, 1077, and 1175 cm-1 is a combination of CS + CC stretching mode; 1021, 1182, and 1175 cm-1 is CH in-plane bending mode; and 998 cm-1 is a CCC in-plane bending mode. Reproduced from Lu, G.; Shrestha, B.; Haes, A. J. The Journal of Physical Chemistry C. 2016, 120, 20759-20767 (ref 126). Copyright 2016 American Chemical Society. 1047x941mm (96 x 96 DPI)



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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 III, A. W.; Guicheteau, J. A. The Journal of Physical Chemistry C . 2013, 117, 22834-22842 (ref 178). Copyright 2013 American Chemical Society. 1309x828mm (96 x 96 DPI)


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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 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 Bio-sensors 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 (ref 200). Copyright 2015, with permission from Elsevier. 951x849mm (96 x 96 DPI)



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Figure 10. Intermolecular forces influence SERS. (A). Schematic of how Ag nanoparticles conjugated with 4MBA 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 Au surface as a function of adsorption time. Figure A and B are reproduced from Wang, Y.; Ji, W.; Sui, H.; Kitahama, Y.; Ruan, W.; Ozaki, Y. The Journal of Physical Chemistry C. 2014, 118, 10191-10197 (ref 201). Copyright 2014 American Chemical Society. Figure C and D are reproduced from Wang, X.; Zhong, J.-H.; Zhang, M.; Liu, Z.; Wu, D.-Y.; Ren, B. Analytical Chemistry 2016, 88, 915-921 (ref 223). Copyright 2016 American Chemical Society. 857x1085mm (96 x 96 DPI)


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Promoting Intra- and Intermolecular Interactions in Surface-Enhanced

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