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Empower Tip: Working with GPC/SEC data in Empower

Empower Tip: Working with GPC/SEC data in Empower

Tip #442: Using Custom Fields for GPC/SEC Analyses: Working with Polymers

Tip #442: Using Custom Fields for GPC/SEC Analyses: Working with Polymers

In this tip we will continue the discussion around using Custom Fields for GPC/SEC analyses.

Please review the following tips for the mechanics and examples of Custom Fields: Tip 82-90 and Tip 92-99.

Let’s see how it’s done!

Example 1: Does the molecular weight of a polymer fall within a specified range?

STEP 1

STEP 1

We can create a peak Custom Field, data type Boolean to determine whether or not the calculated Mw for a polymer falls within a range. In this case it would be 308100<=323900. If the Mw is within the range Empower will report “Within Range”.

STEP 2Once the data is processed, we see the resulting Mw and it is within the specified range, therefore, Empower reports “Within Range”.

Example 2: How does the molecular weight of a new polymer compare to a known “good” polymer?

STEP 3Often, we compare a new polymer to a “good” or “known” polymer by overlaying the chromatograms. We can make the comparison a bit more quantitative by comparing the Mw of the samples. This can be done with an intersample Custom Field. We begin by giving the good sample a label in either the Sample Set Method or post run in Alter Sample.

STEP 4A peak field, data type real is created using the intersample syntax. In this case we compare the Mw of any polymer to the Mw of the sample with the label “good”.

STEP 5Once the data is processed, we see the resulting Mw for this sample is about 20% less than that of the “good” sample.

How could we have Empower report a pass/fail on the comparison of the Mw between the new polymer and the good polymer? Please message me with your thoughts.

It’s that easy!


About the Author

About the Author
Neil Lander

Neil Lander

Neil provides internal support for Empower CDS software and is focused on developing laboratory software solutions that help organizations achieve their scientific and operational objectives.



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