Hi, I’m Todd Houlahan.
Welcome to the eighth in our video series
on best practice use of portable XRF
for Geochem applications.
I’m joined by Alex Thurston today,
our applications engineering manager.
How you doing Alex? I’m doing well Todd, thanks.
OK, this video is all about quality assurance quality control, QA QC.
Our customers are starting to generate
generate their own chemistry on their samples
so they need to take responsibility for the integrity of that data.
Right, and those users that frequently send samples to the lab
are likely to have already an established QA QC procedure.
So some of the aspects of this video
may not be entirely new to them however
I do think that they will pick up on some
unique aspects of handheld XRF.
My customers always ask what QA QC should they do.
So I always reply to them,
well, why don’t you replicate what you’re doing for the lab.
That way they create uniformity,
they can standardize their protocols,
and on a basic level it’s just easier for them to remember.
Right, I think it boils down to essentially three aspects,
that would be contamination, accuracy and repeatability.
OK, the XRF contamination check.
This is where we use a blank sample
to test the cleanliness of the front of the analyzer, the window.
It also allows us to check
if there’s any dust affecting the results.
We supply a silicon dioxide fused quartz disc with every analyzer
and when measuring that we should only measure silicon.
Right and the user should insert this blank
at regular intervals during their batch testing.
Right, so the next thing to do is to check the accuracy of the analyzer.
So the customer could use all sorts of samples to do this.
Either some matrix matched certified reference materials,
some samples from their project
that have been assayed by the lab,
or the nist sample that we supply with every geochem unit.
Right and a good rule of thumb for the frequency
of this type testing would be about every one in 20 tests.
Ideally the accuracy level is up to the user
but it should be ultimately fit for their purpose.
Right. And that accuracy is going to be determined
by a whole series of things that we’ve discussed in this series,
sample prep, test times, calibration,
the sample containers that we use.
So the user should send off a percentage
of the samples that they are testing with the Vanta
to a lab to confirm the analysis of the instrument.
And what that helps them do
is build up a library of samples
that they can ensure the accuracy of the Vanta to their needs
is confirmed with the known good lab analysis.
Right. My experience is they send off a lot of samples
right at the beginning of a project
but once they build up confidence in their method,
their workflows, get some data back from the lab
that confirms the accuracy, they then drop the amount of samples
that they send to the lab over the duration of a project.
So Todd could you speak to how we would check the XRF precision?
Sure. Checking the XRF precision is all about
testing the stability of the analyzer.
It’s a good way to check repeatability
so multiple measurements on the same sample
and looking at the variability of the data.
It’s more important than accuracy most of the time
because we can use samples of known concentrations
and adjust the instruments’ factory calibration
to get the results that we need.
Right, and the precision of these results
are critical to the reliability of that data.
And that’s something that we’ve worked on here in the factory,
in order to achieve that precision,
is by improving the hardware of the instrument
as well as through a number of signal processing
improvements that we call AxonTM technology.
Right and I’ve really seen that bear out
when I do my relative standard deviation checks,
by precision measurements,
where we do a minimum of seven readings on the same sample
and calculating the RSD’s,
we can really see the RSD really low.
Right and the stability of the instrument
is where the Vanta really shines.
From working from weeks to months in harsh conditions,
high sample throughputs, and in hot temperatures,
you can see onscreen here that the stability of the Vanta
is maintained through temperature cycling.
And customers can check this precision really easily
on the stability of their analyzer over time
by just going back and monitoring those XRF accuracy checks
that we talked about earlier.
If they look at that data over a long period of time
it will help them identify if there is anything out of spec.
In the example we can see on the screen here
was perfect because we can see that the anomaly,
there’s an anomaly identified associated
with the instrument being out of spec after a certain period of time
and that allowed them to go back and check that.
I also like to do a lot of repeatability measurements
of the same sample under different sample preparation regimes
to help me optimize what sample prep is going to be best
to achieve a customer’s data quality objectives.
I also like to do repeat measurements
to define instrument error from sample error.
Can you speak a little bit more about that?
Yeah, by taking multiple measurements of a sample
but in different locations of that sample
we get a better feeling for the heterogeneity of the sample
and how much that is affecting the results.
If we test that same sample
but leaving the analyzer in the same location
then we define instrument error.
And by comparing those two allows us to optimize the sample prep
that is going to work best to achieve certain data quality objectives.
That’s helpful. And users can always
contact us for more information on that subject right?
For sure, yes. So let’s summarize.
QA QC, we need to test blanks,
test some samples of known concentrations,
send those samples to the lab,
and do some repeatability measurements,
duplicates, calculate some RSD’s.
And for frequency a good rule of thumb
is one in twenty
or we could just repeat what we do for our laboratory procedure.
Brilliant. Thanks Alex. Happy to help Todd.
Next time we’ll be covering some tips
on implementing your portable XRF program,
things we haven’t covered in the previous episodes
so see you next time.