How to get the most from your data with the help of Certified Reference Material

CRMs, News and Events

Certified Reference Materials (CRM’s) are of great assistance with pXRF data QAQC (Quality Assurance and Quality Control). They provide a check for elemental concentrations as well as a quick way to check for low level contamination of the instrument.

A question we always get asked is: How do I use CRMs with pXRF to get the best result?

There a numerous ways you can use CRMs and each depends on the individual but the following is what we may suggest you take into consideration:

  • Analyse a CRM and a blank standard every 20 to 30 samples
  • Monitor the expected result for an element(s) of interest in the CRM to maintain confidence in the results
  • Use a quartz blank to monitor low-level contamination in the tube of the instrument

QAQC
One way of doing your QAQC on the fly is to analyse your selected CRMs 10 times each. This will give you an idea of the range of results you can expect from the CRMs for your specific instrument.

You can then calculate the minimum and maximum thresholds for some selected elements of your choosing. For example, this may be Cu, Zn and Pb.

Once the CRM’s have been run 10 times on the XRF for 60 seconds, you can calculate the minimum and maximum numbers you would expect to see. This is achieved by taking the average of your values, then calculating the standard deviation times by 2. To find the minimum value minus the average by the SD*2, and to get the maximum values add your SD*2 to the average.

For example,

 

 

 

Once you have ascertained what values you expect to find, you can then use these values to check your CRMs as you go. This ensures better data collection and can help speed up the identification of any problems with how you may be sampling.

It can be of great assistance, as it will ensure you identify any issues as you go rather than finding out at the end of your sampling programme that your data is not reliable. It will also assist you in determining if any adjustments are required to ensure you are collecting good quality data that is fit for purpose.

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