Predi-XY: a python program for automated generation of NICS-XY-scans based on an additivity scheme

Abstract

Polycyclic aromatic systems are prevalent in chemistry and materials science because their thermodynamic stability, planarity, and tunable electronic properties make them uniquely suited for various uses. These properties are closely linked to the aromaticity of the systems. Therefore, characterizing the aromatic behavior is useful for designing new functional compounds and understanding their reactivity. NICS-XY-scans are a popular and simple tool for investigating the aromatic trends in polycyclic systems. Herein we present Predi-XY: an automated system for generating NICS-XY-scans for polycyclic aromatic systems using an additivity scheme. The program provides the predicted scans at a fraction of the computational cost of a full quantum mechanical calculation and enables rapid comparison of various polycyclic aromatic systems.

Predicting bond-currents in polybenzenoid hydrocarbons with an additivity scheme

“…The data that supports the findings of this study are available within the article [and its supplementary material]. The code used to implement the procedures described in this report is available from the corresponding author upon request and will also be included in the next release of Predi-XY, 34 which is freely downloadable from our group's GitLab repository.…”

“…In Figure 10 we reproduce results from our recent report, which demonstrated the use of the automated code Predi-XY to predict NICS-XY-Scans based on the NAdd. 34 We chose three PBHs, containing seven to ten rings, denoted 8-10. The NICS NAdd for these systems results can now be viewed in light of the conclusions outlined above, and we observe that they remain valid for larger systems as well.…”

“…32,33 One of the main advantages of the additivity method is that it allows generation of NICS-XY-Scans for large and diverse PASs in far less time and using far fewer computational resources. Very recently, we automated the additivity method in a Python-based program, Predi-XY, 34 which further cuts down the computation time (by five orders of magnitude, with the hardware we tested) and the manual labor required to generate the scan. Thus, we can now obtain predicted NICS-XY-Scans for PASs at a substantially reduced computational cost and in a fraction of a second.…”

Revealing Structure-Property Relationships in Polybenzenoid Hydrocarbons with Interpretable Machine-Learning

“…27 The generation of a LALAS for a given molecule proceeds according to the following protocol (similar to IUPAC rules for naming branched alkanes), which we have automated in a modified version of Predi-XY. 28 The modified code for generating the LALAS is freely accessible online. a.…”

The COMPAS Project: A Computational Database of Polycyclic Aromatic Systems. Phase 1: cata-condensed Polybenzenoid Hydrocarbons

“…To check for and filter out the incorrectly-optimized structures, we performed two individual tests. The first test used a modified version of the Predi-XY program 28 to check that all molecules contained only six-membered rings. The second test used the xyz2mol script developed by the Jensen group, 29 which converts xyz-coordinates to SMILES formats, to check for undesired motifs, such as saturated carbons.…”