Using the Response Distribution to Compare and Optimize Untargeted Analysis Techniques.

Area of Science:

• Analytical Chemistry
• Data Analysis
• Chromatography

Background:

• Complex mixtures frequently exhibit a log-normal distribution for detected component response amplitudes.
• This characteristic is observable on the higher end of the response spectrum.

Purpose of the Study:

• To demonstrate a method for testing if response amplitude data fits a log-normal distribution.
• To show how fitting this distribution can quantify undetected components and their response levels.
• To propose this analysis as a metric for characterizing analytical techniques and complex mixtures.

Main Methods:

• Testing lists of response amplitudes for log-normal distribution characteristics.
• Utilizing Excel spreadsheets for straightforward data analysis.
• Analyzing log-normal fits and their parameters across various samples.

Main Results:

• Data fitting the log-normal distribution allows for the determination of undetected components and their response levels.
• The analysis is computationally accessible using standard spreadsheet software.
• Log-normal fit parameters offer insights into the nature of the mixture and the performance of analytical methods.

Conclusions:

• Log-normal distribution analysis provides a robust method for characterizing complex mixtures.
• This approach can quantify previously undetectable components, enhancing mixture analysis.
• The parameters derived from log-normal fits serve as valuable metrics for comparing analytical techniques and sample compositions.