The role of theory level in prediction of benzene magnetic indexes of aromaticity is analysed and compared with calculated nuclear magnetic shieldings of He used as NMR probe. Three closely related nucleus-independent chemical shift (NICS) based indexes were calculated for benzene at SCF-HF, MP2, and DFT levels of theory and the impact of basis set on these quantities was studied. The changes of benzene NICS(0), NICS(1), and NICS(1)zz parameters calculated using SCF-HF, MP2 and several density functionals were within 1 to 3 ppm. Similar deviations between magnetic indexes of aromaticity were observed for values calculated with selected basis sets. Only very small effect of polar solvent on benzene aromaticity was predicted. The He nuclear magnetic isotropic shielding (σ) and its zz-components (σ ) of helium atom approaching the centre of benzene ring from above produced similar curves versus benzene-He distance to NICS parameters calculated for similarly moving Bq ghost atom. We also propose an experimental verification of NICS calculations by designing the He NMR measurement for benzene saturated with helium gas or in low temperature matrices.

Phosphorus nitride (PN) is the simplest molecule formed solely by phosphorus and nitrogen. It represents an interesting model for materials, where phosphorus is directly attached to nitrogen. Nevertheless, both theoretical and experimental studies often provide an incomplete picture on the structural, electronic, and spectral properties of PN. Theoretical predictions often suffer from insufficient level of theory, incomplete basis set, or from neglecting several effects, for example, zero‐point vibrational correction (ZPVC). Therefore, we performed an extensive benchmark study on structural, electronic, and spectral properties of PN at the Hartree‐Fock, density functional theory (DFT), or even the coupled‐cluster levels. We paid special attention to the basis set effect. We tested three variants of Dunning's aug‐cc‐pVXZ basis sets with the size from double‐ζ to sextuple‐ζ, as well as Jensen's aug‐pc‐n, aug‐pcJ‐n, and aug‐pcSseg‐n basis sets, where n = 1‐4. Obtained energetics, PN distance, dipole moment, vibrational frequencies, and nuclear magnetic resonance (NMR) parameters were extrapolated to the complete basis set limit (CBS) using three‐ or two‐parameter formulas. The 31P NMR shieldings estimated with the aug‐cc‐pVXZ and aug‐cc‐pV(X + d)Z basis sets strongly depend on the basis set size providing scattered convergence patterns toward CBS. The Hartree‐Fock self‐consistent field (HF‐SCF) NMR parameters evinced similar behavior as the coupled‐cluster data. The only smooth convergence was achieved using the aug‐cc‐pCVXZ basis sets that include core‐valence effects. The KT3 functional underestimated the phosphorus CBS shieldings by about 12 ppm compared to coupled cluster with singles and doubles (CCSD) (T). Nevertheless, KT3 unambiguously surpasses the HF‐SCF and CCSD levels that provide 31P shieldings that are lower by about 150 ppm and 24 ppm compared to CCSD(T). The convergence of nitrogen shieldings was regular for all basis set hierarchies and all theoretical methods. Relativistic and vibrational effects on selected properties were also discussed.

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Landslides are a major natural hazard in Jamaica, and have resulted in loss of life, major economic losses, social disruption and damage to public and private properties. There is a need to delineate areas that are prone to slope instability in order to mitigate their effects. The first and most important stage for the creation of a landslide risk maps is the collection of accurate landslide data in a timely manner. However the type of terrain makes landslide mapping particularly difficult. Aerial Photographs have proven to be an effective way of mapping landslides but acquiring new photographs to map recent landslides is very expensive. High resolution satellite imagery were evaluated for their effectiveness in delineating landslides. The landslides on a whole had no distinctive spectral property; hence no one classification technique could be used to identify them. This research developed integrative methods utilising a combination of: edge enhancement to delineate the scarps area; Wetness Index to identify back titling blocks and debris flow lobes where moisture is higher; shape classification (to distinguish from e.g. ground cleared for agriculture); and slope curvature to map scarps. The information from the image classification was combined in a GIS and automated to determine the probability of the presence and or absence of a landslides. Data derived was validated against detailed field mapping at a scale of 1:5000. For more recent landslides, the modelling proved to be effective, accurately identifying 91% of the landslide both in terms of the location and extent. For the older landslides Pre 2000) the mapping was less effective, with misclassification as high as 24% particularly for smaller landslides. However, the use of these imagery does have great potential as they prove useful for mapping new landslides quickly and efficiently after landslide disaster and are much cheaper and quicker to acquire.