The mechanism of reductive etherification reactions between aromatic aldehydes and alcohols has been investigated with the DFT(B3LYP)/6-31G method. One or two BH(3) molecules have been used to simulate the role of the catalyst and reducing agent. The solvent effects of the title reactions have been studied by the PCM model. It is found that the reactions between aromatic aldehydes and primary, secondary, and tertiary alcohols can proceed more easily in a polar solvent such as acetonitrile. The results provide evidence in theory to broaden the applications of reductive etherification reactions for the optimization of the radiochemical synthesis process of (18)F-labeled ether radiotracers. 相似文献
We study the multi-stage portfolio selection problem where the utility function of an investor is ambiguous. The ambiguity is characterized by dynamic stochastic dominance constraints, which are able to capture the dynamics of the random return sequence during the investment process. We propose a multi-stage dynamic stochastic dominance constrained portfolio selection model, and use a mixed normal distribution with time-varying weights and the K-means clustering technique to generate a scenario tree for the transformation of the proposed model. Based on the scenario tree representation, we derive two linear programming approximation problems, using the sampling approach or the duality theory, which provide an upper bound approximation and a lower bound approximation for the original nonconvex problem. The upper bound is asymptotically tight with infinitely many samples. Numerical results illustrate the practicality and efficiency of the proposed new model and solution techniques.
