The overall goal with any experiment is information output, and the analysis output will be no better than the input. Successful data analysis therefore starts already in the lab. So why not make sure you get the most out of the time spent running experiments, and collect as much info as you can while you are at it? Here we list three simple ways that can help you get the most out of your QCM-D data collection.
For the data set to be high quality and straightforward to analyze, we must make sure that it captures as much information as possible about the process that we would like to analyze. We also want to minimize the presence of other processes that may compete with the phenomenon that we are interested in. To do this, we must pay careful attention to the entire measurement execution, i.e., the baseline, when to stop the experiment, and which harmonics to include in the measurement.
High quality data is a prerequisite for successful data analysis, and successful data analysis therefore starts already in the lab. Make sure you get the most out of the time you spend in the lab running experiments by starting well, ending well, and collecting as much information as possible there in between. Wait for the baseline to stabilize before you insert your samples, collect information from as many harmonics as possible, and wait for the process to terminate before you end the measurement.
Learn more about QCM-D data collection at the Biolin Scientific Academy
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Jennie is Global Technical Product Manager for QSense at Biolin Scientific. She has a Master of Science in Bioengineering from Chalmers University of Technology and spent the first years after graduation focusing on membrane proteins and how to identify and characterize these in the best way. At Biolin Scientific, she has also worked as an Application Specialist for QSense, In-House Sales Manager, and Academy Manager.