Details
Dissipation and Control in Microscopic Nonequilibrium Systems
Springer Theses
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181,89 € |
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| Verlag: | Springer |
| Format: | |
| Veröffentl.: | 23.10.2021 |
| ISBN/EAN: | 9783030858254 |
| Sprache: | englisch |
| Anzahl Seiten: | 236 |
Dieses eBook enthält ein Wasserzeichen.
Beschreibungen
This thesis establishes a multifaceted extension of the deterministic control framework that has been a workhorse of nonequilibrium statistical mechanics, to stochastic, discrete, and autonomous control mechanisms. This facilitates the application of ideas from stochastic thermodynamics to the understanding of molecular machines in nanotechnology and in living things. It also gives a scale on which to evaluate the nonequilibrium energetic efficiency of molecular machines, guidelines for designing effective synthetic machines, and a perspective on the engineering principles that govern efficient microscopic energy transduction far from equilibrium. The thesis also documents the author’s design, analysis, and interpretation of the first experimental demonstration of the utility of this generally applicable method for designing energetically-efficient control in biomolecules. Protocols designed using this framework systematically reduced dissipation, when compared to naive protocols, in DNA hairpins across a wide range of experimental unfolding speeds and between sequences with wildly different physical characteristics.
Chapter 1. Introduction.- Chapter 2. Theoretical background.- Chapter 3. DNA hairpins I: Calculating the generalized friction.- Chapter 4. DNA Hairpins II: reducing dissipation in nonequilibrium protocols.- Chapter 5. DNA Hairpins III: robustness, variability, and conclusions.- Chapter 6. Stochastic control in microscopic nonequilibrium systems.- Chapter 7. Optimal discrete control: minimizing dissipation in discretely driven systems.- Chapter 8. On dissipation bounds: discrete stochastic control of nonequilibrium systems.- Chapter 9. Free energy transduction within autonomous systems.- Chapter 10. Hidden excess power and autonomous Maxwell demons in strongly coupled nonequilibrium systems.- Chapter 11. Conclusions and outlook.<p></p>
<p>Dr. Steven Large grew up in Victoria, Canada, and received his undergraduate honours degree in Nanoscience in 2015 from the University of Guelph in Ontario, Canada. He then completed his PhD in Physics at Simon Fraser University in Vancouver, Canada, defending his thesis in December 2020 under the supervision of Prof. David Sivak. Currently, Dr. Large works as a Data Scientist with Viewpoint Investment Partners, in Calgary, Alberta, using quantitative analysis methods and machine learning techniques to develop robust long-term financial investment strategies.</p>
This thesis establishes a multifaceted extension of the deterministic control framework that has been a workhorse of nonequilibrium statistical mechanics, to stochastic, discrete, and autonomous control mechanisms. This facilitates the application of ideas from stochastic thermodynamics to the understanding of molecular machines in nanotechnology and in living things. It also gives a scale on which to evaluate the nonequilibrium energetic efficiency of molecular machines, guidelines for designing effective synthetic machines, and a perspective on the engineering principles that govern efficient microscopic energy transduction far from equilibrium. The thesis also documents the author’s design, analysis, and interpretation of the first experimental demonstration of the utility of this generally applicable method for designing energetically-efficient control in biomolecules. Protocols designed using this framework systematically reduced dissipation, when compared to naive protocols, in DNA hairpins across a wide range of experimental unfolding speeds and between sequences with wildly different physical characteristics.
Nominated as an outstanding PhD thesis by Simon Fraser University Includes an accessible introduction to the mathematics that describes microscopic, fluctuating systems Advances theory and simulation of nonequilibrium systems, and experimental design and data analysis of DNA hairpins
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