Getting Started with Hard Modeling Factor Analysis

This is a tutorial for PEAXACT software for quantitative spectroscopy from S-PACT. Its main objective is to get you familiar with one of the spectra analysis methods: Hard Modeling Factor Analysis (HMFA). The tutorial addresses to PEAXACT users and persons interested in PEAXACT.

In this tutorial you learn how to:

  1. Create a representative sample
  2. Create a Hard Model of a representative sample
  3. Use the model to analyse a series of spectra from a reactive process

Data files used during the tutorial are available at the PEAXACT installation directory. If you have PEAXACT installed on your computer you may try this tutorial right away. If you don't have PEAXACT yet, get a free trial now.

Note that this tutorial was created for PEAXACT 3 and may look different in the newest version!

The big picture

HMFA can be used if you have a series of samples (e.g. from reaction monitoring) and you would like to calculate qualitative concentration profiles of the involved compounds. HMFA uses a Hard Model (a peak representation of a representative mixture sample) to analyse variations among all samples. As a result it delivers estimates of the pure component spectra and concentration profiles.

HMFA is one of the less complex analysis methods because it requires nothing more than the data you would like to analyse.

Preparations

  • Choose File > Preferences from the menu which opens the application settings window.
  • From the pulldown menu in the top-left corner select Mid-IR, then click OK.

Create a representative sample

A representative sample is one that contains all peaks of all components present in the mixture. It could be a measured sample, but in most cases one cannot find such a sample. Then it has to be computed from the set of available samples.

  • Start PEAXACT.
  • Choose Data > Load Table from the menu.
  • Browse to [PEAXACT Installation directory]\data\MidIR - Reaction.
  • Select the excel file dataTableReaction.xls and continue.
  • Select all items in the Data Sets Panel.
  • Choose Data > Create Representative Sample from the menu.
  • You are prompted to enter the number of samples to be used to calculate a representative sample. Enter 3.
  • Optionlally, choose a filename to save the representative sample, then continue. The representative sample will be added to the Data Sets Panel.
  • The representative sample is a mean sample computed from the most different samples among the selected samples. Typically, the user has to assure that the representative sample contains all relevant peaks of all components, so that it really is representative for the mixture.

Create a Hard Model for the representative sample

  • Right-click on the representative data set in the Data Sets Panel.
  • Choose New Hard Model for Active Sample from the context menu. A new model is added to the Model Tree Panel.
  • Choose Edit Model > Hard Model > Add & Autofit Peaks from the menu.
  • In the next dialog, enter 30 and continue. Wait until all 30 peaks have been fitted.
  • Optionally save the model (File > Save Model)

Perform Hard Modeling Factor Analysis

  • Select all items in the Data Sets Panel. Note that the representative sample is tagged as "ignore", which means it will be excluded from any analysis.
  • Choose Analysis > HMFA > Component Analysis from the menu.
  • You are prompted to enter the number of pure components you want to get identified. Enter 3 (The data originates from a reaction involving 3 components). Also, you could select the kind of closure constraint for concentrations. Choose Normalization which forces the sum of all component concentrations to be one.
  • Click OK to start the analysis.
  • When finished, HMFA results are displayed in a new result window. You could display several reports and export the results by clicking Export.
  • If you close the window with OK, a new model is added to the Model Tree Panel. It contains a Hard Model which again contains the 3 identified components. E.g. you can further use this model for calibration.
 

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