This groundbreaking software automates the identification of peaks and valleys in cyclic voltammetry, significantly reducing manual analysis time. Developed for seamless integration with instrument output files, this tool leverages advanced algorithms to deliver rapid and accurate results, enhancing productivity and operational efficiency. Ideal for potential licensees seeking to innovate in electrochemistry technology.

The electrochemical industry faces significant challenges in analyzing and interpreting complex data from cyclic voltammetry (CV) procedures. Traditionally, this process is time-consuming and requires manual analysis, leading to inefficiencies and potential human errors. Industry professionals experience delays and inaccuracies, impacting overall productivity and quality control.

The technology developed at Pacific Northwest National Laboratory overcomes these barriers with a sophisticated software solution. The software automates peak and valley identification in CV datasets. Specifically, a method of differentiation has been developed to apply to CV, providing precise feature extraction and quantification across varying scan rates and experimental conditions.

By integrating this technology, Pacific Northwest National Laboratory scientists have addressed the industry's pain points, automating an otherwise manual and laborious task. This tool captures reduction dips and peaks automatically, using identification algorithms that generalize across different operators, speeds, and ions. The technology promises increased accuracy and efficiency, reducing the time required for analysis and allowing professionals to focus on higher level decision-making.

APPLICABILITY
Ultimately, this innovative tool enhances data processing capabilities, resulting in significant economic and operational benefits. Its automation potential can streamline workflows, reduce labor costs, and improve estimation of the reduction/oxidation potentials when using cyclic voltammetry, offering a substantial advancement in the field.

DESIGN
An overview of how the software can contribute to research efforts that have the potential to scale industrially by generating an automatic and accurate bird's eye view of large datasets.