Abstract
Benzenoids are a subfamily of hydrocarbons (molecules that are only made of hydrogen and carbon atoms) whose carbon atoms form hexagons. These molecules are widely studied in theoretical chemistry. Then, there is a lot of problems relative to this subject, like the benzenoid generation or the enumeration of all its Kekulé structures (i.e. all valid configurations of double bonds). In this context, the computation of the local aromaticity of a given benzenoid is an important problematic since the aromaticity cannot be measured. Nowadays, computing aromaticity requires quantum chemistry calculations that are too expensive to be used on medium to large-sized molecules. But, there exist some methods related to graph theory which can allow us to compute it. In this article, we describe how constraint programming can be useful in order to compute the aromaticity of benzenoids. Moreover we show that our method is much faster than the reference one, namely NICS.
This work has been funded by the Agence Nationale de la Recherche project ANR-16-C40-0028.
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Carissan, Y., Dim, CA., Hagebaum-Reignier, D., Prcovic, N., Terrioux, C., Varet, A. (2020). Computing the Local Aromaticity of Benzenoids Thanks to Constraint Programming. In: Simonis, H. (eds) Principles and Practice of Constraint Programming. CP 2020. Lecture Notes in Computer Science(), vol 12333. Springer, Cham. https://doi.org/10.1007/978-3-030-58475-7_39
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