I have been trying to find literature on derivative cyclic voltammetry but except for one paper online I haven't been able to find any books or anything else for that matter.
Understand cyclic voltammetry: Before diving into derivative analysis, it's essential to have a solid understanding of cyclic voltammetry (CV). Familiarize yourself with the basic principles, experimental setup, and interpretation of CV data.
Derivative calculation: To obtain a derivative cyclic voltammogram, calculate the derivative of the current (dI/dE) with respect to the voltage (E). This can be achieved by applying numerical differentiation techniques such as finite differences or spline interpolation on the raw CV data. Several software packages, such as MATLAB or Origin, offer built-in functions for derivative calculation.
Interpretation of the derivative plot: The derivative cyclic voltammogram typically provides sharper peaks or features compared to the original CV plot. These peaks represent changes in current intensity with respect to voltage, indicating specific electrochemical events, such as redox processes or adsorption/desorption phenomena. The position, shape, and magnitude of the peaks can provide information about reaction kinetics, electrode surface properties, or the presence of species involved in the electrochemical process.
Compare with the original CV: To fully understand the information provided by the derivative cyclic voltammogram, compare it with the original CV plot. The derivative highlights subtle changes in the current, but it may lose some absolute current values. Therefore, referring back to the original CV can help in interpreting the derivative features accurately.
Consult related literature: While literature specifically dedicated to derivative cyclic voltammetry may be limited, you can refer to publications that discuss the analysis of cyclic voltammograms or electrochemical techniques in general. These resources can provide guidance on interpreting electrochemical data and may indirectly help in understanding derivative plots.
Ahmed Emad Fathy Abbas Thank you so much! I just have one more question, if it’s not a problem. Should I expect the direct correlation between the concentration of the analyzed species and the intensity of peaks in DCV?
The statement that cyclic voltammetry (CV) or derivative cyclic voltammogram (DCV) should be relied upon for quantitative analysis or that there is a direct correlation between the concentration of the analyzed species and the intensity of peaks is not entirely accurate because CV and DCV measure both faradic and non-faradic currents but for accurate quantification, we should measure faradic current only, thus they can still be used for quantitative analysis under appropriate conditions and considerations.
Here are some points to consider:
1- Faradic and non-faradic currents: Faradic current in CV arises from the redox reactions of the analyte. In contrast, non-faradic currents can arise from processes such as charging/discharging of the double-layer capacitance or adsorption/desorption phenomena. It is important to separate and differentiate these currents to focus on the faradic current when quantifying the analyte concentration.
2- Calibration and standardization: To enable quantitative analysis with CV or DCV, calibration curves can be constructed using known concentrations of the analyte. The concentration of unknown samples can be determined by measuring the current response at different concentrations and establishing a correlation. The linearity, sensitivity, and range of the calibration curve need to be carefully determined to ensure accurate quantification.
3- Background subtraction and signal processing: Techniques such as background subtraction or baseline correction can be employed to isolate the faradic current and minimize the effects of non-faradic currents or interferences. Signal processing methods, including derivative analysis, can also be used to enhance the resolution and quantification of peaks in the voltammogram.
4- Consideration of limitations and interferences: CV and DCV may be affected by interferences or limitations, such as overlapping peaks, matrix effects, or slow electrode kinetics. These factors need to be carefully evaluated and addressed to ensure accurate quantitative analysis.
While other techniques such as SWV or DPV may provide a more straightforward quantification of faradic currents, CV can still be a valuable tool in quantitative analysis, especially when combined with appropriate calibration, signal processing, and consideration of potential interferences. It is crucial to evaluate the specific requirements and limitations of the analysis, as well as consult established methods and literature in the specific field of application, to determine the most suitable approach for quantitative analysis.