QCM-D measurement best practice – Measurement setup
Malin Edvardsson Mar 28, ’23 > 10 min

QCM-D measurement best practice – Measurement setup

To collect high-quality QCM-D data, it is important to pay careful attention to the entire process of measurement preparation, setup, and execution.

To learn more about the best practice procedures, I interviewed my colleague, Jennie Ringberg, Technical product manager for QSense. Jennie described the five steps of QCM-D measurement preparation and execution. In this post I share what I learned about steps three and four – measurement setup and execution.

QCM-D Measurement setup and execution in five steps

To get the most out of QCM-D your measurement in terms of data quality and reproducibility, there are several aspects to pay attention to. The measurement setup and execution could be divided into five steps:

  1. Sensor preparation
  2. Preparation of sample liquids
  3. Measurement setup
  4. Running the experiment
  5. After-measurement

In previous blogposts, we have talked about steps 1 and 2, i.e., sensor preparation and preparation of sample liquids. In this post we continue with step 3 and look at what is important to consider during the measurement setup.

Set the measurement temperature

The first thing that I would recommend that you do when you set up your measurement is that you mount the sensor and start the temperature equilibration, Jennie says. This should be done as soon as possible because the temperature affects the signal, and as long as you have an equilibration process of temperature going on in the sensor, there will be some change in the signal, she explains. Set the temperature of the instrument, mount the sensor and start running the buffer over the sensor so that it can start to equilibrate.

Listen to Pod Episode: Collecting quality data with QCM-D – what to consider  and pitfalls to avoid

Quality check to make sure that there is no air in the system

Before you start the baseline stabilization there is one more thing that you should do, and that is to do a quality check to make sure you don’t have air in the system, Jennie says. Unless you plan to run the measurement in air, of course, she adds. So, before you start running the buffer to temperature equilibrium you should do this check.

What you do here is that you look at the absolute values of the dissipation, first in air, to verify that everything is mounted correctly, Jennie says. The dissipation value for a clean sensor in air at the third harmonic and 20°C, should be around 165. Then, you look at the absolute values of the dissipation, as you have introduced deionized water, to confirm that there is no air in the system, Jennie continues. The dissipation value for a clean sensor in DI water at the third harmonic and 20°C, should be approximately 181. This is a good check because normally when you have mounted your sensor and you look for the frequencies and so on, you get these numbers. If you see already in air that the dissipation value is far away from 165 for the third harmonic, then you can start to suspect that there is something wrong. Maybe the sensor is not correctly mounted or maybe it is not clean. So, there you have a first status indication before you have filled your instrument or a system with liquid, etc. This check will save you time because starting all over can be time-consuming. As a first quality check, you can start by looking at these values, Jennies says.

Let the baseline stabilize

Next, you introduce the solvent you plan to use and let the baseline stabilize, Jennies says. The temperature is not measured at the sensor but a bit underneath. Therefore, if you look at the temperature curve, it might look like the set temperature has been reached, but the sensor temperature might be a bit delayed, and this can be interpreted as drift of the signal. It is not an actual drift though, it is just an equilibration in temperature going on, which is natural, so to speak. If you give the sensor temperature time to equilibrate, the baseline will stabilize, Jennie explains.

I would also like to mention that a stable baseline is really important to make the most of the measurement and to facilitate the data analysis. If the baseline is not stable when you start your measurement, the result does not say much because you do not know if the drift continued with the same slope throughout the entire measurement. This makes it difficult to interpret the data. So, I would really like to emphasize the importance of letting the baseline stabilize before you start your experiment, Jennie says.

What is a stable baseline?

So what defines a stable baseline can depend on what your measurement is like, Jennie says. Let us say that you want to measure an interaction that gives rise to a frequency shift of three Hz, i.e., a relatively small shift. In this situation it is much more crucial to have a perfectly stable baseline than if you expect to measure a frequency shift of 300 Hz.

What if the baseline doesn’t stabilize?

So, what should you do if the baseline does not stabilize? How long is it reasonable to wait? Sometimes there can be an ongoing drift, Jennie says. You know that the temperature is stable, but there is still a drift. If the frequency is decreasing, there could be some contamination somewhere in the flow path That contamination can be absorbing onto the sensor, and this is what you measure. For example, the inlet tubing may contain some contaminants which come loose due to the liquid flow and then absorbs to the sensor surface.

If you have a positive trend in the frequency curve, on the other hand, then it could be that you had something on the surface already when you started the measurement, and this is now being removed. Perhaps the surface was not clean, and now when liquid flows over the surface this dirt comes loose and shows like a frequency increase, i.e., a mass loss.

If it is just a small amount of contaminant, maybe it will be removed by the flow over the sensor surface and the curves will stabilize over time. But here again, we come back to the importance of cleaning and making sure that all parts are clean when you start the measurement. Make sure to have clean equipment, sensors, tweezers, and everything that you plan to use in the measurement. Then you do not have to worry about drift caused by contamination.

Another aspect that could result in drift is if the solvent that you are using is not compatible with the sensor surface, Jennie says. This could result in the coating dissolving or reacting with the solution. Maybe this is a reaction that you are not aware of, and it could show as both mass uptake and mass loss, depending on the kind of reaction that takes place.

Also, if the solvent is not compatible with the material of the O-ring there could also be an observed drift. For example, in some solvents the O-ring will swell and that will show in the signal. So, it is very important to consider these things before you start your measurement, Jennie says.

Tips and tricks on how to collect quality data with QCM-D

If you want to learn more about QCM-D measurement best practice, listen to the interview with Jennie as she shares some tips and tricks in the pod episode Collecting quality data with QCM-D – what to consider and pitfalls to avoid.

Scientific data analysis methods

Listen to the podcast episode to learn more about QCM-D measurement best practise

Podcast  Episode: Collecting Quality data with QCM-D - what to consider and pitfalls to  avoid  Listen

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