Chromatography Forum

We have a system at work, where we must quantify the sum of three peaks, adding each peaks amount and correcting that amount with the corresponding response factor.

The calibration is made against a standard that contains only one of those peaks. At the same time, the peak of the compound that is used as a standard has a response factor because we use a bromide salt as a std, but we are actually quantifying a chloride salt.

I tried making a named group, that adds all of the areas, but have been unable to correct with the response factors, because when I enter the response factors, it also affects the Y value in the curve (because my standard has an F factor too), so the amount for that peak remains unchanged.

Is there any way I can multiply the curve for a factor, or any way to solve this? Thank you!

If I understand you, you need the correct summation of amounts for the group peak in samples, taking into account that two of the 3 peaks have their own response factors? For ease of explanation, lets call the 3 peaks in the named group as 1,2 and 3 and lets call peak 1 the standard peak with its own response factor.

Make a named group of 1,2 and 3 and make sure to select "User entered, curve or sum peaks for quantitation" as the source of Calibration x value. Next, create a peak, real custom field called Factor with formula Area*CConst1, and for peak 1, put this factor, whatever it is, into the CConst1 row, and for all the other peaks, put in 1.00 as CConst1 to keep the formula active. In the processing method, under Y Value for both peak 1 and the named group, select Factor. For the other peaks 2 and 3, select a curve reference of peak 1 and enter the appropriate response factors. Make sure the Named Group is NOT in the component editor. Delete that row. Enter relevant amounts for the other 3 peaks in the component editor. Save your changes.

Apply this processing method to a sample set after building your calibration curve and you will get the amounts for the named group, all taking into account the response factors of both the standard peak 1 and the other peaks 2 and 3. I tested it on some data there and it worked perfect for me.