For a project we needed to read out our PC-222 multimeter. It supports RS-232, but the protocol is not documented at all and the software is proprietary. After a little research on the web, we found some information in a comment on Amazon. With this and a little trial–and–error we found out how it works.
ICP–OES is a common technique in analytical chemistry, which is characterized by simplicity, simultaneous multi-elemental determination capability, high sensitivity, linear dynamic range, low detection limits, and good precision . It seems to be the perfect method for element analysis (esp. metals). However, sometimes it can fool the user.
- K. Satyanarayana, and S. Durani, "Separation and inductively coupled plasma optical emission spectrometric (ICP-OES) determination of trace impurities in nuclear grade uranium oxide", Journal of Radioanalytical and Nuclear Chemistry, vol. 285, pp. 659-665, 2010. http://dx.doi.org/10.1007/s10967-010-0591-8
Last week, I posted an article about sigmoid functions and how to use them. Nevertheless, it is hard to guess the parameters for a given problem. So, people use software such as Origin  or QtiPlot to fit.
Personally, I use Origin/QtiPlot only for plotting and Excel/OO–Calc for evaluation/calculation, because both programs are much more comfortable and powerful. However, both lack the possibility to fit sigmoid functions, automatically.
It is possible to do such fits for nearly any function using the solver, though, but only a few people I’ve met knew how to do this or that it is even possible. But, I think the solver is a very handy feature and, therefore, I want to give here a short introduction into using it for fitting a sigmoid function to a set of data.
- " OriginLab - Origin and OriginPro - Data Analysis and Graphing Software " http://www.originlab.com/
Note: There was an error in the reverse formula (and maybe also with some of the values given). Frank pointed this out (see comments section below).
In analytical chemistry, linear regression or linear function is a common (maybe the most common) tool to describe the relationship between a measured signal and the concentration of an analyte. Even if the relationship is much more complex, one usually works in small ranges only where the assumption of linearity is convenient.
However, there are analytical problems, which cannot be solved with this simple approach. In this short article I want to introduce and present another useful function for data evaluation on the basis of a real example.