Why I love Square Wave Voltammetry

Understanding Square Wave Voltammetry (SWV): A Practical Demonstration

Welcome to this short video! In this experiment, I will demonstrate a square wave voltammetry (SWV) experiment and use it to discuss why I find SWV particularly valuable, especially in the context of biosensors and electrochemical assays.

I actually prefer square wave voltammetry over electrochemical impedance spectroscopy (EIS). SWV is not mysterious—it simply provides strong signals and numerous adjustable parameters, making it highly versatile for electrochemical analysis.

Setting Up the Experiment

To begin, I will take a reagent from ZP—a ferricyanide solution. I have already decanted it, so I will apply 50 microliters onto the sensor. One of the advantages of electrochemistry, particularly the way we perform it, is that we can work with very small sample sizes. This makes it ideal for point-of-care and point-of-need diagnostics.

Next, I will name the data file: Square Wave Voltammetry 5mM, as I am using a 5mM ferricyanide solution. I have labeled it as sample #2 for easy reference, and I have categorized it under “Sample Cluster: Demo” to simplify data retrieval.

Experimental Parameters

I will set the following parameters:

• Starting potential: -400 mV

• Ending potential: 600 mV

• Voltage step: 1 mV

• Current range: 100 µA

• Amplitude: 40 mV

• Frequency: 30 Hz

One of the key aspects of SWV is the presence of amplitude and frequency, which are not typically available in cyclic voltammetry (CV). This makes SWV a hybrid between linear sweep voltammetry (LSV) and EIS—in EIS, frequency is variable, but it is not always necessary to adjust it dynamically.

Observing the Results

As the experiment runs, I can immediately see the oxidation wave forming. Starting at -400 mV, we first reduce ferricyanide to ferrocyanide, and then reoxidize it as we sweep through the potential range. This produces a characteristic wave.

The system uploads the data to the cloud, ensuring automatic storage and accessibility. This feature is particularly useful as it eliminates concerns about data loss.

Analyzing the Data

In SWV, we analyze two underlying signals:

• Forward scan

• Reverse scan

The key metric is the difference signal (Forward – Reverse), which enhances the overall signal clarity. By utilizing the software tools, I can visualize each component separately and analyze the extracted values.

For peak detection, I look for a peak height at approximately 200 mV, setting a 100 mV window around this value. This flexibility ensures peak detection even if it shifts slightly.

Converting Peak Height to Concentration

One of the powerful aspects of this system is the ability to quickly relate peak height to concentration. By inputting reference values (e.g., 10mM and 0mM), I can fit a linear equation and obtain an estimated concentration. For instance, when I input 20mM, I observe a reading of 5.4mM, which can be fine-tuned for accuracy.

Why I Prefer Square Wave Voltammetry

SWV provides two additional adjustable parameters—amplitude and frequency—which allow for optimization. In this experiment, I used an amplitude of 40 mV and a frequency of 30 Hz, which are the default settings for this sensor and potentiostat.

At Zimmer & Peacock (ZP), we take a pragmatic approach. We prioritize finding the signal that offers the lowest limit of detection and highest sensitivity, balancing signal quality with practicality. The ability to analyze the difference signal, forward scan, and reverse scan gives SWV an edge over LSV or CV.

Final Thoughts

I am a strong advocate of square wave voltammetry due to its flexibility and superior signal processing capabilities. If you have any technical questions, feel free to reach out to us on the ZP website.