Hi Jenny,
I understand the difference between peak fitting and linear combination fitting. It is like, If I don't know anything about my sample, peak fitting should be used. If I know the components of my sample, I can use linear combination. That is why I use peak fitting first, because I know very little about my sample. However, what I am thinking is that from the results of peak fitting, I know there may be some types of sulphur in my sample, and based on the peak positions, I can chose the standards for linear combination fitting.
I don't think the two methods are normally used together but rather are used to get completely different kinds of information. As Bruce mentioned, there is no relationship between the results of one in relation to the other.
I can't use linear combination fitting in the first place, because I don't exactly know what sulphur forms in my sample, and I may miss an important species if I chose the wrong standards. However, I still want to try linear combination after peak fitting, because I think the linear combination fitting may be more accurate than peak fitting. It uses the whole spectrum of the standard, while the peak fitting neglectes the effect of small features on the fitting. Does it make sense?
I am not sure what you mean by 'more accurate'. I suppose it depends on how you define accuracy. I hope this this doesn't sound banal but the basic principle of both peak fitting and linear combination fitting is the same. You are trying to use some basis set of functions to model a spectrum. A point that I think Bruce was making is that the important part is in how you interpret the functions. Obviously, a collection of mathematical functions has no physical meaning in terms of species. On the hand, if you just randomly combine some spectra from a standard list that give you a nice fit it does not have any more physical meaning that the Gaussian functions.
My samples are fluid coke and their activation products. They have reduced and oxidized sulphur species, more likely in organic forms. I have 26 standards covering the sulphur oxidation states from elemental sulphur to sulphate. Most of them are organic sulphur.
Any more suggestions? Thank you!
Best regards,
Jenny
I hesitant to mention but I suppose you could take a brute-force approach and fit many combinations of your standards. The result though is that you will likely find multiple combinations that all add up to fit your spectrum with equal statistical goodness of fit. You then have to decide which (if any) might be the right one. You need chemical information to either know what is in your sample or at least what is most likely. You could then perhaps narrow down the search space to find something that is consistent with the data. For example if you happen to have a species with a particularly unique signature. However, there are a large number of organic sulphur species so this seems unlikely. Rather than trying to fit specific species you might try to see if you can classify groups of related sulphur compounds. Can you match peaks in your spectra with major features of a class of sulphur species? In other words, using vibrational spectroscopy terms, look for 'functional groups' first. Once you have separated groups of candidates then use chemical or other information to narrow the list. You might not be able to identify exact species but that may not be necessary. I have no idea what you what to know but do you need to know the exact composition? Or only the types of products? Or how reduced/oxidized the sample is? Inorganic/organic sulphur? You may be able to answer these sorts of questions without knowing the exact composition. I hope this helps. Cheers, Adam