QCM-D is designed to detect minute variations in frequency, f, and dissipation, D. Here we have compiled a checklist that will help you optimize the reproducibility of your QCM-D measurements by minimizing unintentional changes of the recorded parameters.
There is a vast range of different QCM:s in the market, and they all seem to provide similar information. Learn more about the differences, and when to use which one.
The quartz crystal microbalance, QCM, has been around since the 60’ where it has been used for monitoring of thin-film deposition and characterization of thin films. So how does this technology work?
Model membranes are used in various fields of research. Read about how these lipid membranes can be characterized using QSense QCM-D technology.
Proteins tend to passively adsorb to surfaces. Read about how protein adsorption at various surface and solution conditions quickly can be measured.
Quantifying QCM mass, there are two different approaches to choose from, the Sauerbrey equation or viscoelastic modeling. But what if the wrong method is applied, what happens then? How critical are the consequences? Here we describe what happens if the wrong quantification approach is used.
One of the key factors to achieve reliable and reproducible QCM measurements is temperature stability. Here we list the top four factors that will help you eliminate temperature induced artifacts in your QCM data.
You have finished a set of successful QCM experiments, and it is time to analyze the data. Mass and thickness quantification are on the to-do list, and you must decide between the Sauerbrey equation and viscoelastic modeling. Here we present guidelines on how to evaluate which method to use.
The versatility of polyelectrolyte multilayers, PEMs, is high, which makes them interesting for e.g. biomedical applications. The functionality is largely determined by the layer properties, which needs to be understood to be tailored. Here, we show how PEMs can be characterized with QCM-D.