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Skip to Search Results- 1Bendrich, Michelle
- 1Bineshmarvasti, Baher
- 1Boutros,Jenny
- 1De la Hoz Siegler, Hector Jr
- 1Dini, Yoann
- 1Hartley, Kendra Jade
- 3Huang, Biao (Chemical and Materials Engineering)
- 1Amos Ben-Zvi (Chemical and Materials Engineering)
- 1Antoniuk, Tim (Industrial Design)
- 1Ben-Zvi, Amos (Chemical and Materials Engineering)
- 1Chung, Hyun-Joong (Department of Chemical and Materials Engineering)
- 1De Klerk, Arno (Chemical and Material engineering)
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Spring 2012
Microalgae are a promising source of biofuels and other valuable chemicals. The low cell density and slow growth rate that have traditionally characterized microalgal cultures, however, have resulted in a reduced economical feasibility. To develop a sustainable microalgal process it is required...
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Fall 2011
Optimization techniques, in conjunction with a finite element thermal model, are used in this thesis to optimize the temperature profile (i.e. cooling rate and coiling temperature) of a steel skelp during laminar cooling. Optimization parameters include skelp velocity, laminar cooling bank...
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Optimization of the reaction conditions of two enzymes for use in a carbon sequestration process, and investigation into immobilization via encapsulation within polymersomes
DownloadFall 2016
Carbon dioxide emissions from human activities contribute to an increase of greenhouse gases in the atmosphere. In nature, this gas is sequestered through the use of enzymes found in the Calvin-Benson-Bassham cycle, with useful molecules such as sugars being synthesized as products. A biomimetic...
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Fall 2015
Oil sands bitumen is increasingly recovered by injecting steam into reservoirs using the energy intensive Steam assisted gravity drainage (SAGD) process. Interest in improving recovery and energy efficiencies have led to an interest in injecting light hydrocarbons along with or instead of steam...
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Spring 2020
Reinforcement learning (RL) has received wide attention in various fields lately. Model-free RL brings data-driven solutions that learn the control strategy directly from interaction with process data without the need for a process model. This is especially beneficial in the case of nonlinear...
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Robust Gaussian Process Regression and its Application in Data-driven Modeling and Optimization
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Availability of large amounts of industrial process data is allowing researchers to explore new data-based modelling methods. In this thesis, Gaussian process (GP) regression, a relatively new Bayesian approach to non-parametric data based modelling is investigated in detail. One of the primary...
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Spring 2014
The spontaneous assembly of polypeptides through non-covalent interactions at physiological conditions is the main focus of the presented work and will be discussed from two different perspectives: (i) the interaction of peptide chains with themselves leading to formation of higher order...
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Thermodynamic Investigation of the Effect of Interface Curvature on Solid-Liquid Equilibrium and Its Application to Zinc-Air Battery Electrolyte at Low Temperature
DownloadSpring 2018
Micro and nanoscale confinements and local curvatures, which are ubiquitous in natural and man-made materials and systems, cause significant impact on thermodynamic phase behavior. This effect has been extensively studied for single component solid's liquid phase transitions, but rarely for...