Nonlinear Optical Methods for Characterization of Molecular Structure and Surface Chemistry

Abstract

The principles, strengths and limitations of several nonlinear optical (NLO) methods for characterizing biological systems are reviewed. NLO methods encompass a wide range of approaches that can be used for real-time, in-situ characterization of biological systems, typically in a label-free mode. Multiphoton excitation fluorescence (MPEF) is widely used for high-quality imaging based on electronic transitions, but lacks interface specificity. Second harmonic generation (SHG) is a parametric process that has all the virtues of the two-photon version of MPEF, yielding a signal at twice the frequency of the excitation light, which provides interface specificity. Both SHG and MPEF can provide images with high structural contrast, but they typically lack molecular or chemical specificity. Other NLO methods such as coherent anti-Stokes Raman scattering (CARS) and stimulated Raman scattering (SRS) can provide high-sensitivity imaging with chemical information since Raman active vibrations are probed. However, CARS and SRS lack interface and surface specificity. A NLO method that provides both interface/surface specificity as well as molecular specificity is vibrational sum frequency generation (SFG) spectroscopy. Vibration modes that are both Raman and IR active are probed in the SFG process, providing the molecular specificity. SFG, like SHG, is a parametric process, which provides the interface and surface specificity. SFG is typically done in the reflection mode from planar samples. This has yielded rich and detailed information about the molecular structure of biomaterial interfaces and biomolecules interacting with their surfaces. However, 2-D systems have limitations for understanding the interactions of biomolecules and interfaces in the 3-D biological environment. The recent advances made in instrumentation and analysis methods for sum frequency scattering (SFS) now present the opportunity for SFS to be used to directly study biological solutions. By detecting the scattering at angles away from the phase-matched direction even centrosymmetric structures that are isotropic (e.g., spherical nanoparticles functionalized with self-assembled monolayers or biomolecules) can be probed. Often a combination of multiple NLO methods or a combination of a NLO method with other spectroscopic methods is required to obtain a full understanding of the molecular structure and surface chemistry of biomaterials and the biomolecules that interact with them. Using the right combination methods provides a powerful approach for characterizing biological materials.

Keywords: Biomaterial Characterization; Coherent Raman Spectroscopy; Nonlinear Optics; Structure Analysis; Sum-Frequency Generation; Surface Analysis.

Figure 1

Diagrams of the photophysical processes for a variety of the most common nonlinear optical techniques for material characterization, including multiphoton excitation fluorescence (MPEF), second harmonic generation (SHG), coherent anti-Stokes Raman scattering (CARS), stimulated Raman scattering (SRS), and sum-frequency generation (SFG).

Figure 2

a) A short-pulsed excitation laser may produce SHG and TPEF signals, which can be detected in a multiphoton microscope. b) SHG signals, in this case from collagen fibers, always appear at the double-frequency of the excitation light, while the TPEF signals are broadened and Stokes-shifted to a characteristic peak with a longer wavelength. Figure 1b is reprinted with permission from ref [53], copyright 2002 National Academy of Sciences.

Figure 3

a) The TPEF (green) identifies features in the mouse ovary tissue distinct from the SHG (red), which primarily shows the ordered collagen fiber regions. b) The ${\chi }_1={\chi }_{z^{\prime }{z}^{\prime }{z}^{\prime }}^{(2)}/{\chi }_{z^{\prime }{x}^{\prime }{x}^{\prime }}^{(2)}$ parameter shows two populations of collagen-related signals in the SHG channel, which are attributed to the presence of collagen type I (χ₁ = 1.2) and type III (χ₁ = 0.83). c) The ${\chi }_2={\chi }_{x^{\prime }{z}^{\prime }{x}^{\prime }}^{(2)}/{\chi }_{z^{\prime }{x}^{\prime }{x}^{\prime }}^{(2)}$, only includes one broad population that does not provide additional contrast for the collagen fibers in the χ-image of the tissue. d) A pseudo-colored image of χ₁. Reprinted with permission from ref [64], copyright 2015 John Wiley and Sons.

Figure 4

a) Short-pulsed excitation pump and Stokes lasers may produce SRS and CARS signals, which can be detected in nonlinear microscopes. By fast modulation of either the pump or the Stokes beam, coupled with a lock-in-amplifier, signals can be detected with low noise levels. b) Left: While interference with a nonresonant (dotted) background can shift the maximum signal from the vibrational peak in CARS (blue squares), the SRS signal (red circles) remains similar to the corresponding spontaneous Raman signal (solid line) from retinol. Right: The SRS signal intensity has a simple linear intensity dependence on the analyte concentration. Figure 4b is reprinted with permission from ref. [8], copyright 2008 American Association for the Advancement of Science.

Figure 5

A nonresonant contribution gives a non-zero background in CARS (a) that interferes with the vibrational signal from the MLV and causes an apparent broadening of the orientation distribution function as determined by the S₂ parameter in the theoretical model (b and c). However, the background is low in SRS (d) and the corresponding model and parameter give a more definite and narrow distribution function of the molecular orientation for the CH₂ groups in the MLV (e and f). The orientation of the lines denotes the average CH₂ orientation obtained, while the color indicates the magnitude of the S₂ parameter (b and e). Reprinted from ref. [79], copyright 2015 American Chemical Society.

Figure 6

a) A schematic of a typical setup for vibrational SFG spectroscopy in reflection mode. b) Illustrations of solid/liquid (i), solid/air (ii), and liquid/air (iii) interfaces, which are commonly analyzed with SFG. The interactions at the interface typically induce a preferential orientation of the analyte that can then be characterized with SFG, while the isotropically distributed species in bulk do not contribute to the signal.

Figure 7

a) A model of a CH₃ group with the tilt (θ), azimuthal (φ) and twist (ψ) angles defined. b) Measured values of the asymmetric stretch vibration of CH₃ for lysozyme adsorbed at hydrophilic silica surfaces from different bulk concentrations. The error of the ratios is about 20 %. c) ${\chi }_{\mathit{yyz}}^{(2)}/{\chi }_{\mathit{yzy}}^{(2)}$ ratios for the CH₃ (as) vs. θ, assuming isotropic φ and ψ. If the gaussian distribution function for θ is broad, the tilt angle sensitivity is low, illustrating the difficulty to specifically identify one angle for complex macromolecules. The data are reprinted from ref [101], copyright 2003 American Chemical Society.

Figure 8

a) Top: A color map of the ${\chi }_{\mathit{zzz}}^{(2)}/{\chi }_{\mathit{yyz}}^{(2)}$ ratio depending on the tilt and twist angles for an azimuthally isotropic distribution of the β-Gal enzyme with a V152C mutation. Bottom: Based on the measured ${\chi }_{\mathit{zzz}}^{(2)}/{\chi }_{\mathit{yyz}}^{(2)}$ ratio of 1.9, the orientation map has been color-coded 0 to 1 from worst to perfect fit with the top color map. b) The corresponding color maps for the ratio of s- and p-polarized ATR-FTIR measurements of the same interface. c) When combined, only a limited range of orientations give values that agree with both the SFG and ATR-FTIR data. The protein illustration shows one of the predicted orientations, given the data and the V152C mutation. Reprinted with permission from ref. [106], copyright 2013 American Chemical Society.

Figure 9

a) A setup for PS-SFG. A concave mirror ensures that the Vis, IR and SFG beams from the sample are refocused onto the LO and that the SFG signal and the LO signal are collinear. The silica plate induces a delay of 1.7 ps between SFG and LO signals. b and c) A frequency domain interferogram is obtained, which can be Fourier transformed into the time domain where one of the interference terms (in this case at +1.7 ps) can be selected by filtering. d) Transforming back to the frequency domain yields the real (solid) and imaginary (dashed) interferograms. Division of the sample signals by the nonresonant reference yields the clean spectra. e and f) The real and imaginary parts of the water vibrations flip in sign relative the CH_X stretches when switching from SDS to CTAB surfactants at liquid/air interfaces as the head-group charge induces different water orientations. Reprinted with permission from ref. [115], copyright 2009 American Institute of Physics Publishing.

Figure 10

a) At a scattering angle away from the phase-matched direction, the travelling distances for the three mixing beams on either side of the spherical particle are slightly different, which yields a phase-shift across the particle diameter. The difference in traveling distance (δL) for the IR and visible beams is here illustrated for the two opposite sides perpendicular to the scattering angle; however, the integrated contributions from the particle surface has to be considered. b) The angular scattering pattern is dependent on factors such as particle size and shape, molecular orientation, and the angle between the excitation beams. A simulated pattern for achiral signals from spherical particles is shown, for which strong signals are precluded in the phase-matched direction (0°).

Figure 11

a) The scattering pattern for water (C_2v symmetry) and CH₃ (C_3v symmetry) depend on the specific vibration (symmetric vs. asymmetric stretch), the polarization combination, and the molecular orientation on the particle (R = 500 nm) surface. The tilt angles in the simulations are 0° (blue), 30° (cyan), 60° (green), and 90° (red). b) The ratio between signals in different polarization combinations can be used to identify the molecular tilt angle; however, certain combinations have poor sensitivity. Reprinted with permission from ref [168], copyright 2010 American Institute of Physics.

Figure 12

a) Schematic of a SFS experiment of water nanodroplets in oil. b) The spectral features for the D₂O stretch vibrations of water nanodroplets in hydrophobic environments (black) are distinct from the corresponding data of planar interfaces (blue and red). The nanodroplets have more of strongly H-bonded vibrations appearing at ~2370 cm⁻¹ and they lack the free OD groups at ~2745 cm⁻¹. Reprinted with permission from ref. [174], copyright 2017 Nature Publishing Group.