Intermediate ion stability and regio selectivity polymerization using neutral salicyladiminato in propene nickel(II) and palladium(II) complexes as catalysts

The mechanism of the Heck reaction has been studied with regard to transition metal catalysis of the addition of propene and the formation of unsaturated polymers. The reactivity of nickel and palladium complexes with five different bidentate ligands with O,N donor atoms has been investigated by computational methods involving density functional theory. Hence, it is possible to understand the electronic and steric factors affecting the reaction and their relative importance in determining the products formed in regard of their control of the regiochemistry of the products. Our results show that whether the initial addition of propene is trans to O or to N of the bidentate ligand is of crucial importance to the subsequent reactions. Thus when the propene is trans to 0, 1,2-insertion is favoured, but when the propene is trans to N, then 2,1-insertion is favoured. This difference in the preferred insertion pathway can be related to the charge distribution engendered in the propene moiety when the complex is formed. Indeed charge effects are important for catalytic activity but also for regioselectivity. Steric effects are shown to be of lesser importance even when t-butyl is introduced into the bidentate ligand as a substituent. (C) 2007 Elsevier B.V. All rights reserved.

Ensemble projections for wine production in the Douro Valley of Portugal

Wine production is largely governed by atmospheric conditions, such as air temperature and precipitation, together with soil management and viticultural/enological practices. Therefore, anthropogenic climate change is likely to have important impacts on the winemaking sector worldwide. An important winemaking region is the Portuguese Douro Valley, which is known by its world-famous Port Wine. The identification of robust relationships between atmospheric factors and wine parameters is of great relevance for the region. A multivariate linear regression analysis of a long wine production series (1932–2010) reveals that high rainfall and cool temperatures during budburst, shoot and inflorescence development (February-March) and warm temperatures during flowering and berry development (May) are generally favourable to high production. The probabilities of occurrence of three production categories (low, normal and high) are also modelled using multinomial logistic regression. Results show that both statistical models are valuable tools for predicting the production in a given year with a lead time of 3–4 months prior to harvest. These statistical models are applied to an ensemble of 16 regional climate model experiments following the SRES A1B scenario to estimate possible future changes. Wine production is projected to increase by about 10 % by the end of the 21st century, while the occurrence of high production years is expected to increase from 25 % to over 60 %. Nevertheless, further model development will be needed to include other aspects that may shape production in the future. In particular, the rising heat stress and/or changes in ripening conditions could limit the projected production increase in future decades.