QSense Omni is designed to minimize the user knowledge required to produce high-quality QCM-D data.
The quality of the data produced by an analytical instrument is crucial and noise and drift play a significant role in determining the outcome.
Learn the guidelines on how to assess which method to use to quantify QCM mass.
Learn more about QSense 4th generation QCM-D platform
Temperature stability is critical for reliable QCM data. Here are the top four factors that will help you eliminate temperature induced artifacts.
Sensitivity vs Limit of detection (LOD) - read about how they compare and why one is more imoprtant than the other.
Read about the key signatures in the QCM data that reveal if viscoelastic modelling should be used to extract the mass.
Viscoelasticity is a quality involving both viscous and elastic properties at the same time.
Read about what the different QCM parameters mean and which ones you should keep an eye on