In a recent video we discussed fast processing of data in Djuli.
In this video, the presenter demonstrates how to process cyclic voltammetry (CV) data using a potentiostat and the cloud platform Djuli. Although the data was originally gathered using a third-party potentiostat and saved as a CSV file, the presenter shows how it can be uploaded to Djuli for analysis.
The process begins with uploading the file and viewing the raw data. The presenter then walks through several steps of data processing, including:
Cropping the Data – The dataset is trimmed between 0V and -0.7V to focus on the relevant section.
Flipping the Y-Axis – The data is inverted for convenience.
Finding the Peak Height – A window is set to identify the peak, demonstrating that small reference potential shifts do not impact peak detection.
Converting to ppm – Instead of working with raw signal intensity, the peak height is converted into a parts-per-million (ppm) value. The presenter fine-tunes the conversion factor to approximate a real-world oxygen concentration (around 6 ppm).
The key takeaway is that Djuli provides a user-friendly way to process electrochemical data without coding. If the data had been gathered using a Sensit potentiostat from ZP, it would have been sent directly to the cloud for immediate analysis. However, the workflow remains flexible enough to handle third-party data as well.
The presenter concludes by inviting viewers to reach out with any questions regarding ZP’s Sensit potentiostat technology or the Djuli cloud platform.