Regenerating used QCM sensors can seem to be a resource efficient way of running experiments. However, we generally do not recommend this approach. In this post, we explain why.
Can QCM sensors be reused?
Cleaning used QCM sensors to be able to use them again could be considered a resource efficient approach seemingly saving both time and money. We often get questions on how to remove different types of samples from used sensors to make sure the surface is clean and back to the state it was before it was used in a measurement. Our general answer to this question, however, is that we do not recommend reusing sensors. The reason is that we as suppliers can only guarantee the quality of the sensors when they come directly from us, i.e., when they are new and unused. When you get the sensors from us, we can say that this is a good sensor, we know what’s on top of the surface and so on. But if you have used it once, and then try to remove the sample from the sensor surface, maybe you are not completely successful. There may be some leftovers from the old sample remaining at the surface and you might even change the chemical composition and/or the surface roughness of the sensor. This would mean that in the next experiment, you will not start with the same surface as you had in the previous one. If this is the case, you cannot expect high measurement reproducibility. This aspect is worth emphasizing because sensor regeneration is such a common question.
Are there any situations when the QCM sensor could be used?
There might be cases where the measurement reproducibility is not that critical. Perhaps you are only after a yes/no kind of answer. Then reusing the sensor could potentially work for that purpose. However, it is then the responsibility of you as a user to evaluate if the data quality or reproducibility is good enough, we as supplier cannot take responsibility for the result.
Tips and tricks on how to collect quality data with QCM-D
If you want to learn more about QCM-D measurement best practice, we share some tips and tricks in the pod episode Collecting quality data with QCM-D – what to consider and pitfalls to avoid.
