Spectroelectrochemistry: Bridging Electrochemical Insights with Optical Spectroscopy

Traditional electrochemical methods are crucial for observing reactions at electrodes but face several limitations:

• Capacitance currents: Each time the electrode is polarized, it acts like a small capacitor, creating extra current that can interfere with the measurement data.
• Lack of Specificity: Unless the electrode is specifically functionalized, reactions at the electrode-water interface are often not selective, leading to unwanted side reactions or adsorption processes, complicating the interpretation of results.
• Electrode Geometry: Variations in electrode size and surface roughness impact the shape of the voltammogram, changing the mass transport profile and electrical capacitances.
• Identifying Unknown Species:  Electrochemical methods are not suitable to identify unknown species that may form as intermediate or product in redox reactions.

To address these limitations, researchers often turn to spectroelectrochemistry (SEC), a technique that integrates electrochemistry with spectroscopy. Common spectroscopic techniques used in SEC include:

• UV/Vis Absorption Spectroscopy: Tracking species that absorbs light in the ultraviolet and visible region.
• Near-Infrared (NIR) and Infrared (IR) Absorption Spectroscopy: Identifies molecular bonds, revealing chemical structure.
• Raman Scattering: Provides a molecular fingerprint through vibrational modes.
• Electron Paramagnetic Resonance (EPR): Detects radicals and unpaired electron species

From an experimental standpoint, SEC often employs  thin-layer cells or with optically transparent electrodes (OTEs) (e.g., indium tin oxide, ITO) to optimize optical access. The orientation of light beam varies depending on the setup, typically aligned either normal or parallel to the sample:

• Normal Configuration: Here, the light beam is positioned perpendicular to the sample, allowing for both reflection and transmission measurements. This setup is ideal for studying changes occurring at the electrode surface.
• Parallel Configuration: In this arrangement, the light beam travels parallel to the electrode surface. This configuration is effective for observing the diffusion layer while minimizing interference from surface processes on the electrode.

The following illustration depicts these three configurations

A Simple Redox Reaction Under SEC

Consider a reaction where a reduced specie (Re) undergoes oxidation:

$$Re\underset{k_b}{\stackrel{k_f}{\rightleftharpoons }}O{x}^{+}+e^{-}$$

Both species absorb light at different wavelengths. The reduced form at 421 nm, while the oxidized form at 505 nm. The absorption spectra for the species are shown below:

The relationship between absorption and concentration is described by the Lambert-Beer law:

$$A=ϵCx$$

Where:

• $A$= Absorbance (unitless)

• $ϵ$ = Molar absorptivity coefficient (L⋅mol−1⋅cm−1L⋅mol−1⋅cm−1)

• $C$  = Concentration (mol⋅L−1mol⋅L−1)

• $x$ = Optical path length (cm) 

To effectively capture concentration changes near the electrode, the optical path length ( $x$ ) should match the diffusion layer thickness (~200-400 µm). This ensures a minimal interference from the bulk solution.

The animation below shows how gradually reducing the optical path from 700 µm to 50 µm improves the ability to track the redox process while also influencing the absorption measurement. 

The right panel of the animation illustrates the diffusion layer profile of the oxidized species, while the left panel displays the absorbance as a function of time. The arrow in the right panel indicates the progression of the signal. The measured absorbance corresponds to the maximum absorption of the oxidized species at 421 nm.

Initially, before reaching equilibrium potential ( $E_0$ ), the reduced species dominate, resulting in zero absorbance. As the potential approaches and surpasses $E_0$, oxidation occurs, and the oxidized species begin to form, leading to an increase in absorbance. When the potential sweep reverses, the oxidized species are reduced, causing the absorbance to decrease.

However, in cells with large optical path lengths, the diffusion of the oxidized species into the bulk solution prevents full reversibility, meaning the absorbance does not return to its initial value. This effect arises because some oxidized analyte diffuses away from the reaction zone before it can be reduced.

When optical path length is equal to or shorter than diffusion layer thickness, absorbance accurately reflects the reaction zone, minimizing interference form the bulk solution. The trade-off, however, is that at shorter optical paths, the absorbance present lower values. 

Interactive SEC simulator

The following interactive app simulates a cyclic voltammogram coupled with UV-Vis absorption measurements, showing how different parameters affect both current and absorbance. Additionally, the app also visualizes the diffusion layer of the oxidized species, helping to understand the diffusion. The adjustable parameters include:

• Diffusion coefficient of  Ox and Re ( $D_{Re}$ & $D_{Ox}$): See how diffusion impacts the symmetry of the voltammograms.  Note that slider values are on a logarithm scale.
• Charge transfer coefficient (α): Affects the kinetic of electron transfer; its influence is strong at low $k_0$ values but becomes negligible at high $k_0$.
• Concentration of  the reduce specie ([Re]): Adjust to see how initial concentration affects both CV shape and absorbance response.
• Global transfer charge constant ($k_0$): Determines whether the redox process is reversible or irreversible. Like diffusion coefficients, this parameter is controlled on a logarithm scale.
• Electrochemical cell Length ($x$) in mm: Explore how the CV and the absorbance change when the cell length is smaller than the diffusion layer.
• Wavelength for absorbance Measurement (λ): See how the absorbance changes with different wavelengths.
• Number of electrons transfer ($n_e$): See how electrons transfer impacts both current and absorbance.

By adjusting these parameters, you can gain a deeper understanding of the factors that influence a spetroelectrochemical measurements. In addition, the plot can be exported as csv files.  References

1. Compton, R.G, Laborda, E. Ward, K.R. (2014) Understanding Voltammetry: Simulation of Electrode Processes. Imperial College Press. https://doi.org/10.1142/p910
2. Bard, A.J., Faulkner, L.R., White, H.S. (2022) Electrochemical Methods: Fundamentals and Applications. (3rd ed). John Wiley & Sons. https://doi.org/10.1023/A:1021637209564
3. Britz, D., Strutwolf, J. (2016) Digital Simulation in Electrochemistry. (4th ed.). Springer. https://doi.org/10.1007/978-3-319-30292-8
4. Lozeman, J.J.A., Führer, P., et al. (2020) Spectroelectrochemistry: The future of visualizing electrode processes. Analyst. https://doi.org/10.1039/c9an02105a
5. Kaim, W., Fiedler, J., et al. (2009) Spectroelectrochemistry: The best of two worlds. Chem. Soc. Rev. https://doi.org/10.1039/b504286k