Dear Ayushi, Getting the values of k1 and qe with non-linear regression mostly depends on the software you would like to use. If you are familiar with programming, one of the easiest way is to create (or use an existing) code, for example in Python. If you want to use specific softwares, you should consider statistical programs like R, SSPS, MATLAB, etc. MS Excel with Solver extension can also be used for NLR, but keep in mind that the statistical computation capabilities are more limited than that of a specific statistical software. Whichever method (or more specifically, software) you choose, the initial "guess" for the parameters are crucial. Before running the regression analysis, you need to provide initial guess values for the parameters qe and k1. These initial guesses are cornerstones, as they can affect the ability of the regression algorithm to find the best fit values. You can obtain these initial guesses from a preliminary linear regression or from the literature.

I typically use OriginLab if I'm trying to do NLR. I've used it for both PFO and PSO fits.

Ryan G. Hoerr Thank you so much.

To do the NLR, I can suggest OriginLab or an old but still working Gnuplot (freeware)(http://www.gnuplot.info/). If you learn how to fit an equation parameters to get the results (with errors), then it works quickly (and the results are automatically saved in the file "fit.log", which is a fantastic feature). Previously, I have also used EnzFitter, SigmaPlot, LABFit, and CurveFitter, for example.