KinTek Explorer™ SpectraFit
SpectraFit™ is an optional add-on that allows fitting time-resolved spectra both directly and by singular value decomposition (SVD). Decomposition is performed automatically during spectra import, and as with any kind of data in KinTek Explorer, the model used in fitting is completely defined by the user. Multiple experiments, including time-resolved spectra collected at different concentrations of reactants, can be fit simultaneously as illustrated below.
Time-resolved spectra are de-convoluted by singular value decomposition (SVD) and the resulting amplitude vectors are then fit to the model programmed by the user to derive the spectra and time-dependence of individual species. Unlike other implementations of SVD, the user is not restricted to preprogrammed models with simplifying assumptions; rather, users fit data directly to the model based upon numerical integration of the rate equations with no simplifying assumptions. Moreover, multiple experiments with various signals and protocols can be fit simultaneously, taking advantage of the full power of KinTek Explorer™. In addition, KinTek Explorer™ provides comprehensive error analysis in fitting multiple experiments to a single model.
When data are imported into KinTek Explorer™, SVD is performed automatically. The user then enters a model, specifies the starting conditions for the experiment and defines the observable species. Fitting the data to the model resolves the individual spectra and time-dependence of each species. Finally, the model is used to reconstitute the original time-resolved spectra.
The complete fitting of time-resolved spectra is simple and relies on an intuitive, interactive user-interface, yet the fitting is done to the most rigorous standard with no simplifying assumptions. Multiple experiments of any time, such as concentration series at a single wavelength, rapid quench-flow-data, or additional time-resolved spectra derived at different starting concentrations, can all be fit simultaneously to a single unifying model. There is no better way to fit kinetic data!