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Data for Efficient prediction of nucleus independent chemical shifts for polycyclic aromatic hydrocarbons
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Kilymis, Dimitrios, Bartók, Albert P., Pickard, Chris J., Forse, Alexander C. and Merlet, Céline (2021) Data for Efficient prediction of nucleus independent chemical shifts for polycyclic aromatic hydrocarbons. [Dataset]
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Official URL: http://doi.org/10.5281/zenodo.3676905
Abstract
Nuclear Magnetic Resonance (NMR) is one of the most powerful experimental techniques to characterize the structure of molecules and confined liquids. Nevertheless, the complexity of the systems under investigation usually requires complementary computational studies to interpret the NMR results. In this work we focus on polycyclic aromatic hydrocarbons (PAHs), an important class of organic molecules which have been commonly used as simple analogues for the spectroscopic properties of more complex systems, such as porous disordered carbons. We use Density Functional Theory (DFT) to calculate 13C chemical shifts and Nucleus Independent Chemical Shifts (NICS) for 34 PAHs. The results show a clear molecular size dependence of the two quantities, as well as the convergence of the 13C NMR shifts towards the values observed for graphene. We then present two computationally cheap models for the prediction of NICS in simple PAHs. We show that while a simple dipolar model fails to produce accurate values, a perturbative tight-binding approach can be successfully applied for the prediction of NICS in this series of molecules, including some non-planar ones containing 5- and 7-membered rings. This model, one to two orders of magnitude faster than DFT calculations, is very promising and can be further refined in order to study more complex systems.
Item Type: | Dataset | ||||||||||||||||||
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Subjects: | Q Science > QD Chemistry | ||||||||||||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Physics | ||||||||||||||||||
Type of Data: | Experimental data | ||||||||||||||||||
Library of Congress Subject Headings (LCSH): | Nuclear magnetic resonance, Density functionals, Quantum chemistry, Mathematical physics, Polycyclic aromatic hydrocarbons | ||||||||||||||||||
Publisher: | University of Warwick, Department of Physics | ||||||||||||||||||
Official Date: | 8 March 2021 | ||||||||||||||||||
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Status: | Not Peer Reviewed | ||||||||||||||||||
Publication Status: | Published | ||||||||||||||||||
Media of Output (format): | .dat .xy | ||||||||||||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||||||||||||
Copyright Holders: | University of Warwick | ||||||||||||||||||
Description: | Data record consists of a three zip files containing raw data, one containing the Dipolar model, one the TB model, and the results in the third. |
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