The syntheses and characterization of nickel complexes; investigation of Ni(dppp)2 and [NiX(dppp)n]x, potentially catalytically active nickel(0)/(I) species for cross-coupling reactions

This thesis describes an investigation in which we compare Ni(0), Ni(I) and Ni(II) complexes containing 1,3-bis(diphenylphosphino)propane (dppp) as a phosphine ligand for their abilities to effect three types of cross-coupling reactions: Buchwald-Hartwig Amination, Heck-Mizoroki, and Suzuki-Miyaura cross-coupling reactions with different types of substrates. The Ni(0) complex Ni(dppp)2 is known and we have synthesized it via a new procedure involving zinc reduction of the known NiCl2(dppp) in the presence of an excess of dppp. The Ni(0) complex was characterized by NMR spectroscopy and X-ray crystallography. Since Ni(I) complexes of dppp seem unknown, we have synthesized what at this stage appear to be NiXdpppn/[NiX(dppp)n]x (X = Cl, Br, I; n = 1,2, x = 1, 2) by comproportionation of molar equivalents of Ni(dppp)2 and NiX2dppp, X= Cl, Br, I.

Tracing the Development of Athletes Using Retrospective Interview Methods: A Proposed Interview and Validation Procedure for Reported Information

A new interview procedure is proposed for collecting valid information on the acquisition of high-level performance in sport. The procedure elicits verifiable information on the development of athletes' achievements in their primary sport, as well as factors that might influence performance, including involvement in other sporting activities, injuries, physical growth and quality of training resources. Interviewed athletes also describe their engagement in specific training and other relevant activities during each year of their development as well as how they experienced each type of activity. The collected information is then examined to identify those aspects of the athletes' recall of their development that meet criteria of reliability and validity. Recommendations to coaches and scientists are discussed for how retrospective interviews can uncover aspects of development that distinguish elite from less accomplished athletes.

New Rigorous Decomposition Methods for Mixed-integer Linear and Nonlinear Programming

Process systems design, operation and synthesis problems under uncertainty can readily be formulated as two-stage stochastic mixed-integer linear and nonlinear (nonconvex) programming (MILP and MINLP) problems. These problems, with a scenario based formulation, lead to large-scale MILPs/MINLPs that are well structured. The first part of the thesis proposes a new finitely convergent cross decomposition method (CD), where Benders decomposition (BD) and Dantzig-Wolfe decomposition (DWD) are combined in a unified framework to improve the solution of scenario based two-stage stochastic MILPs. This method alternates between DWD iterations and BD iterations, where DWD restricted master problems and BD primal problems yield a sequence of upper bounds, and BD relaxed master problems yield a sequence of lower bounds. A variant of CD, which includes multiple columns per iteration of DW restricted master problem and multiple cuts per iteration of BD relaxed master problem, called multicolumn-multicut CD is then developed to improve solution time. Finally, an extended cross decomposition method (ECD) for solving two-stage stochastic programs with risk constraints is proposed. In this approach, a CD approach at the first level and DWD at a second level is used to solve the original problem to optimality. ECD has a computational advantage over a bilevel decomposition strategy or solving the monolith problem using an MILP solver. The second part of the thesis develops a joint decomposition approach combining Lagrangian decomposition (LD) and generalized Benders decomposition (GBD), to efficiently solve stochastic mixed-integer nonlinear nonconvex programming problems to global optimality, without the need for explicit branch and bound search. In this approach, LD subproblems and GBD subproblems are systematically solved in a single framework. The relaxed master problem obtained from the reformulation of the original problem, is solved only when necessary. A convexification of the relaxed master problem and a domain reduction procedure are integrated into the decomposition framework to improve solution efficiency. Using case studies taken from renewable resource and fossil-fuel based application in process systems engineering, it can be seen that these novel decomposition approaches have significant benefit over classical decomposition methods and state-of-the-art MILP/MINLP global optimization solvers.