The rate-determining step in the hydroformylation of 1-octene, catalysed by the rhodium-Xantphos catalyst system, was determined by using a combination of experimentally determined (1)H/(2)H and (12)C/(13)C kinetic isotope effects and a theoretical approach. From the rates of hydroformylation and deuterioformylation, a small (1)H/(2)H isotope effect of 1.2 was determined for the hydride moiety of the rhodium catalyst. (12)C/(13)C isotope effects of 1.012(1) and 1.012(3) for the alpha-carbon and beta-carbon atoms of 1-octene were determined, respectively. Both quantum mechanics/molecular mechanics (QM/MM) and full quantum mechanics calculations were carried out on the key catalytic steps, for "real-world" ligand systems, to clarify whether alkene coordination or hydride migration is the rate-determining step. Our calculations (21.4 kcal mol(-1)) quantitatively reproduce the experimental energy barrier for CO dissociation (20.1 kcal mol(-1)) starting at the (bisphosphane)RhH(CO)(2) resting state. The barrier for hydride migration lies 3.8 kcal mol(-1) higher than the barrier for CO dissociation (experimentally determined trend approximately 3 kcal mol(-1)). The computed (1)H/(2)H and (12)C/(13)C kinetic isotope effects corroborate the results of the energy analysis.

In silicomethods provide an alternative and reliable route for the toxicity evaluation of metal oxide nanoparticles.

The development and implementation of safe-by-design strategies is key for the safe development of future generations of nanotechnology enabled products. The safety testing of the huge variety of nanomaterials that can be synthetized is unfeasible due to time and cost constraints. Computational modeling facilitates the implementation of alternative testing strategies in a time and cost effective way. The development of predictive nanotoxicology models requires the use of high quality experimental data on the structure, physicochemical properties and bioactivity of nanomaterials. The FP7 Project MODERN has developed and evaluated the main components of a computational framework for the evaluation of the environmental and health impacts of nanoparticles. This chapter describes each of the elements of the framework including aspects related to data generation, management and integration; development of nanodescriptors; establishment of nanostructure-activity relationships; identification of nanoparticle categories; hazard ranking and risk assessment.

The solubility of metal oxides is one of the key descriptors for the evaluation of their potential toxic effects, both in the bulk form and in nanoparticulated aggregates. Current work presents a new methodology for the in silico assessment of the solubility of metal oxides, which is demonstrated using a well-studied system, ZnO. The calculation of the solubility is based on statistical thermodynamics tools combined with Density Functional Tight Binding theory for the evaluation of the free energy exchange during the dissolution process. Models of small ZnO clusters are used for describing the final dissolved material, since the complete ionic dissolution of ZnO is hindered by the formation of O anions in solution, which are highly unstable. Results show very good agreement between the computed solubility values and experimental data for ZnO bulk, up to 0.5 mg L and equivalents of 50 μg L for the free Zn cation in solution. However, the reference model for solid nanoparticles formed by free space nanoparticles can only give a limited quantitative solubility evaluation for ZnO nanoparticles.

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