Among the top 10 features are electrotopological state (EState) index features which represent the combination of the electronic character and topological environment of each atom in a molecule. Most of the top ten features represent graph-based descriptors that focus on the electron distribution and polarity of molecules. Perhaps as expected, but nonetheless interesting, common descriptors that provide evaluation of size and steric of atoms and molecules were not found to be important, which is consistent with TEP values describing electronic effects without significant steric effects. With the development of the TEPid machine learning model, we were then able to analyze the Kraken phosphine ligand library to determine the distribution of electronic effects. We then calculated the TEP values for 294,860 phosphine structures retrieved from the Kraken database's application programming interface (API). A few of the phosphines could not be calculated with TEPid because they had null values for some of the 19 descriptors. Figure plots the distribution of Kraken phosphine TEP values. Comparison of Figure with Figure shows that the Kraken phosphines have a significant shift to lower TEP values than our DFT calculated set of phosphines with a mean of 2066.8 cm -1 and a standard deviation of 5.7 cm -1 compared to the DFT calculated set of phosphines with a mean of 2078.1 cm -1 and a standard deviation of 9.9 cm -1 . This suggests that the structures in the Kraken database tend to more electron-donating phosphine complexes that transfer more electron density to the nickel. In an effort to have access to more electron-withdrawing phosphines and an electronically balanced library, we decided to build our own phosphine ligand library beginning with our ReaLigands library that contains all ligands detached and classified from all transition metal complexes in the CSD. In our ReaLigands library there are 1,078 phosphines. The machine learning calculated TEP values for these experimental phosphines ranges from 2053.1 to 2107.7 cm -1 with a mean of 2068.1 cm -1 (standard deviation of 7.7 cm -1 ). We dismantled these 1,078 phosphines using our program Polyjuice 51 to obtain a set of 205 organic groups that were then used to assemble new phosphines. Like Kraken, we first generated phosphines with two identical organic groups and one different organic group (labeled as RR'2P). This generated 42,025 unique phosphines with a mean calculated TEP value of 2067.8 cm -1 with a standard deviation of 7.3 cm -1 , which is a very similar mean and distribution to the Kraken phosphine library. To increase the number of electron-withdrawing phosphines we identified the 76 organic groups that provided TEP values of 2070 cm -1 or greater and then used these groups to generate 76,076 new phosphines where all three groups on the phosphine are different (labeled as RR'R''P). This set of phosphines showed the expected higher mean value of 2076.3 cm -1 with a standard deviation of 7.1 cm -1 . To this library, we also added phosphines that have two covalent connections to a single organic group and a third independent organic group (labeled as RR'P). This was done by using Polyjuice to identify 201 unique organic groups from the ReaLigand's phosphines that provide two covalent bonds to phosphine. We then combined these 201 organic groups with the previously mentioned 205 single connection organic groups to yield 31,666 more phosphine structures. Figure plots the TEP values for all the created phosphine ligands. The complete set of phosphines is available for download from GitHub. Figure ) for all phosphines created by using the organic groups detached from phosphines in the ReaLigand library. b) Color-coded plot of machine learning calculated TEP values (cm -1 ) for ReaLigand phosphines (red) and newly created phosphines with the structures RR'2P (pink), RR'R''P (orange), and RR'P (green).