Thesis (M.S.)--West Virginia University, 2003. / Title from document title page. Document formatted into pages; contains viii, 67 p. : ill. Includes abstract. Includes bibliographical references (p. 53).

Thesis (Ph. D.)--University of New South Wales, 2003. / Also available online.

Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2003. / Includes bibliographical references (leaves 122-129). Also available in electronic version. Access restricted to campus users.

Thesis (Ph. D.)--Mechanical Engineering, Georgia Institute of Technology, 2006. / Lackey, W. Jack, Committee Chair ; Cochran, Joe K., Committee Member ; Danyluk, Steven, Committee Member ; Fedorov, Andrei G., Committee Member ; Rosen, David W., Committee Member ; Wang, Zhonglin, Committee Member.

Thesis (M.Eng. (Mechanical )) -- University of Pretoria, 2007. / Includes bibliographical references (leaves 73-81)

This thesis compiles the publications I coauthored during my doctoral studies at University of Leipzig on the subject of optimizing thermodynamic systems, focusing on three optimization perspectives: maximum efficiency, maximum power, and maximum efficiency at given power. We considered two currently intensely studied models in finite-time thermodynamics, i.e., low-dissipation models and Brownian systems. The low-dissipation model is used to derive general bounds on the performance of real-world machines, while Brownian systems allow us to better understand the practical limits and features of small systems. First, we derived maximum efficiency at given power for various low-dissipation setups, with a particular focus on the behavior close to maximum power, which helps us to determine whether it is more beneficial to operate the system at maximum power, near maximum power or in a different regime. Then, we move to the design of maximum-efficiency and maximum-power protocols for Brownian systems under different boundary conditions. Particularly, when the constraints on control parameters are experimentally motivated, we presented a geometric method yielding maximum-efficiency and maximum-power protocols valid for systems with periodically scaled energy spectrum and otherwise arbitrary dynamics. Each chapter contains a short informal introduction to the matter as well as an outlook, pointing out the direction for our research in the future.

The self-assembly of structured particles into monodisperse clusters is a challenge on the nano-, micro- and even macro-scale. While biological systems are able to self-assemble with comparative ease, many aspects of this self-assembly are not fully understood. In this thesis, we look at the strategies and rules that can be applied to encourage the formation of monodisperse clusters. Though much of the inspiration is biological in nature, the simulations use a simple minimal patchy particle model and are thus applicable to a wide range of systems. The topics that this thesis addresses include: Encapsulation: We show how clusters can be used to encapsulate objects and demonstrate that such `templates' can be used to control the assembly mechanisms and enhance the formation of more complex objects. Hierarchical self-assembly: We investigate the use of hierarchical mechanisms in enhancing the formation of clusters. We find that, while we are able to extend the ranges where we see successful assembly by using a hierarchical assembly pathway, it does not straightforwardly provide a route to enhance the complexity of structures that can be formed. Pore formation: We use our simple model to investigate a particular biological example, namely the self-assembly and formation of heptameric alpha-haemolysin pores, and show that pore insertion is key to rationalising experimental results on this system. Phase re-entrance: We look at the computation of equilibrium phase diagrams for self-assembling systems, particularly focusing on the possible presence of an unusual liquid-vapour phase re-entrance that has been suggested by dynamical simulations, using a variety of techniques.