  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 magnitudes faster than DFT calculations, is very promising
and can be further refined in order to study more complex systems.
