A program for automatically predicting supramolecular aggregates and its application to urea and porphin

in: Journal of Computational Chemistry (2018)
Sachse, Torsten; Dietzek, Benjamin; Martínez, Todd; Presselt, Martin
Not only the molecular structure but also the presence or absence of aggregates determines many properties of organic materials. Theoretical investigation of such aggregates requires the prediction of a suitable set of diverse structures. Here, we present the open-source program EnergyScan for the unbiased prediction of geometrically diverse sets of small aggregates. Its bottom-up approach is complementary to existing ones by performing a detailed scan of an aggregate's potential energy surface, from which diverse local energy minima are selected. We crossvalidate this approach by predicting both literature-known and heretofore unreported geometries of the urea dimer. We also predict a diverse set of dimers of the less intensely studied case of porphin, which we investigate further using quantum chemistry. For several dimers, we find strong deviations from a reference absorption spectrum, which we explain using computed transition densities. This proof of principle clearly shows that EnergyScan successfully predicts aggregates exhibiting large structural and spectral diversity

Cookies & Skripte von Drittanbietern

Diese Website verwendet Cookies. Für eine optimale Performance, eine reibungslose Verwendung sozialer Medien und aus Werbezwecken empfiehlt es sich, der Verwendung von Cookies & Skripten durch Drittanbieter zuzustimmen. Dafür werden möglicherweise Informationen zu Ihrer Verwendung der Website von Drittanbietern für soziale Medien, Werbung und Analysen weitergegeben.
Weitere Informationen finden Sie unter Datenschutz und im Impressum.
Welchen Cookies & Skripten und der damit verbundenen Verarbeitung Ihrer persönlichen Daten stimmen Sie zu?

Sie können Ihre Einstellungen jederzeit unter Datenschutz ändern.