I tried to create a QSAR (Quantitative Structure Activity Relationship) model for my thesis that tries to predict the melting points of certain ZIFs (Zeolitic Imidazolate Frameworks) based on relative Zn-N bond energies obtained from DFT calculations (B3LYP/aug-cc-pVDZ) as well as Labute's Solvent Accessible Surface Area (LASA) and the stoichiometry of a mixed-linker "Xim-" for a ZIF of sum formula Zn(im)_2-x(Xim)_x.

I found out that the calculated bond energies correlate more or less with Hammett-Parameters (meta-position, sigma_m)

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and so I got to thinking: What if I had a nice json or csv table i could easily import in python or KNIME (Konstanz Data Miner), that contains a long list of Hammett-Parameters for certain substituents? That way I may not have to perform a DFT calculation for each new substituent X and instead use the Hammett-Parameters, which are already available.

What I found is this publication, which probably has the longest list of Hammett-Parameters available. The problem: It's a PDF and I don't think that gels well with... programmatically importable data?

Now I am willing to manually turn this into a csv/json of my very own, but I'd rather ask first if something like this already exists, if there's a source for such data that I do not know about, or if there is a smart way to convert this PDF into a nicer format that can easily be imported into python.

  • $\begingroup$ Just a clarification, the paper contains several tables. The one you're interested in is table 1. Correct? $\endgroup$
    – ksousa
    Commented Feb 2 at 15:11
  • $\begingroup$ yes. I was planning on working my way through it eventually, but table 1 seems to be the most important one. $\endgroup$
    – J.Doe
    Commented Feb 2 at 17:19


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