During the last months, we’ve contacted you asking your opinion and experience with the software. Thanks for all your suggestions and needs we have improved the previous version of the software to make it easier, faster and more versatile.
What is new in this release?
- In collaboration with Mestrelab Software, AFFINImeter can now analyze Nuclear Magnetic Resonance (NMR) titration curves.
- The Main toolbar has been simplified:
“Data” & “Projects” have been merged into a single “Projects & Data*” menu
You can filter the elements to show by selecting “Projects & Data” (default), only “Projects” or only “Data“.
A new option has been included to easily pre-visualize the settings of your experiments directly from the list of data & projects.
The “Instruments” management menu has been removed.
*Data elements are represented by this icon –> 
*Projects elements are represented by this icon–> 
- Now you can organize all your data and projects into folders:
- Organize your data & projects as you would do on your computer.
- Looking for your already existing KinITC data? Go to Projects & Data, and look into the folder “KINITC”.
- A new parameter has been introduced to measure the quality of the FIT: Goodness of Fit
The GoF (Goodness of Fit) is the probability of finding the fitted value within a normal distribution with half-width equal to the uncertainty of each experimental point. The GoF for a curve is obtained as the mean GoF of all its points. The ideal value of perfect fit would be Gof=100%.
This parameter will be available when you execute a new FIT project/or re-execute an older project. If you visualize an already executed project, the previous parameter (χ 2) still will be present.
What have we improved from the previous version?
- We have incorporated the possibility to perform blank subtraction right after raw data upload and processing.
- Multiple minor usability improvements and performance tweaks.
- Multiple bug fixes and issues suggested by our users have been implemented and resolved.
Try the new AFFINImeter here