A prototype collection of knowledge on ligands in metal complexes, termed a ligand knowledge base (LKB), has been developed. This contribution describes the design of DFT-calculated descriptors for monodentate phosphorus(III) donor ligands in a range of representative complexes. Using the resulting data, a ligand space is mapped and predictive models are derived for metal complexes. Important characteristics, including chemical, computational and statistical robustness for the generation and exploitation of such an LKB are described. Chemical robustness ensures transferability of the descriptors, as well as comprehensive sampling of ligand space. To make the calculations amenable to automation in an e-science setting, a reliable, well-defined computational approach has been sought from which the descriptors can be readily extracted. The LKB has been explored with multivariate statistical methods. Principal component analysis (PCA) is used for the mapping of chemical space, projecting multiple descriptors into scatter plots which illustrate the clustering of chemically similar ligands. Interpretation of the resulting principal components in terms of established steric and electronic properties and the importance of its statistical robustness to variations in the ligand set are discussed. Multiple linear regression (MLR) models have been derived, demonstrating the versatility of the descriptors for modeling varied experimentally determined parameters (bond lengths, reaction enthalpies and bond-stretching frequencies). The importance of re-sampling methods for testing the robustness of predictions is highlighted. A strategy for the construction of a robust LKB suitable for the modeling of ligand and complex behavior is outlined based on these observations.

The development of efficient sensors for the determination of the water content in organic solvents is highly desirable for a number of chemical industries. Presented herein is a Mg(2+) metal-organic framework (MOF), which exhibits the remarkable capability to rapidly detect traces of water (0.05-5 % v/v) in various organic solvents through an unusual turn-on luminescence sensing mechanism. The extraordinary sensitivity and fast response of this MOF for water, and its reusability make it one of the most powerful water sensors known.

A new class of cyclic hydrocoppers(I) with the general formula CunHn (n = 3-6), resembling the cyclic hydrocarbon analogues, were predicted by means of DFT calculations to be stable molecules adopting a perfect planar configuration of high-symmetry characteristic of the aromatic systems.

Density functional theory calculations are reported concerning the dissociative mechanism for alkene metathesis by ruthenium dichloride catalysts, including both bisphosphine and diaminocarbene/phosphine complexes. The calculations use a hierarchy of models, ranging from [(L)(PH(3))Ru(Cl)(2)(CH(2))](L=PH(3) or diaminocarbene) through the larger [(L)(PMe(3))Ru(Cl)(2)(CHPh)] to the "real"[(L)(PCy(3))Ru(Cl)(2)(CHPh)]. Calculations show that the rate-limiting step for metathesis is either ring closing from an alkene complex to form a ruthena-cyclobutane, or ring-opening of the latter intermediate to form an isomeric alkene complex. The higher efficiency of the diaminocarbene based catalysts is due to the stabilization of the formal +iv oxidation state of the ruthenium centre in the metallacycle. This effect is partly masked in the smaller model systems due to a previously unnoticed stereoelectronic effect. The calculations do not reproduce the experimental observation whereby the initiation step, phosphine dissociation, is more energetically demanding and hence slower for the diaminocarbene-containing catalyst system than for the bisphosphine. Further calculations on the corresponding bond energies using a variety of DFT and hybrid DFT/molecular mechanics methods all find instead a larger phosphine dissociation energy for the bisphosphine catalyst. This reversed order of binding energies would in fact be the one expected based on the stronger trans influence of the diaminocarbene ligand. The discrepancy with experiment is small and could have a number of causes which are discussed here.