Dataset for "Element-Specific Donor Numbers for Anions"

Selecting the optimum anion represents an immense but vital challenge for many areas of chemistry and biology. Data-driven approaches, including machine learning, are limited by the small number of existing experimental anion interaction descriptors - new experimental anion interaction descriptors are very rarely discovered, with the two principal descriptors both discovered during the 1970s. Furthermore, the existing descriptors all have the same limitations. We used a powerful combination of core-level X-ray photoelectron spectroscopy (XPS) experiments and lone-anion solvation model density (SMD) calculations to produce a new set of descriptors, element-specific donor numbers we have named DNE-XPS, for 52 anions.

This compressed file is supplementary to the article 'Element-Specific Donor Numbers for Anions'. Its contents are two-fold.

(1) Experimental X-ray photoelectron spectroscopy data of all new samples published in the article, in .vms format which can be accessed using CasaXPS.

(2) The output files of all the anions studied computationally. These computational files will allow you to replicate the Density Functional Theory (DFT) calculations using Gaussian 16 shown in the article.