Branching networks play a major role in a variety of physiological and engineering structures over a range of physical scales. However, increasingly, artificial systems are being tailored towards the nanoscale to reduce costs and improve performance and process control. In this thesis, analytical and numerical models are developed to enable the efficient design and accurate simulation of nanofluidic branching networks, where non-continuum/non-equilibrium effects prohibit the use of common solutions. A hybrid molecular-continuum method is presented for the design and simulation of general high-aspect-ratio nanofl uidic networks. This increases the scope of hybrid techniques in two main ways: 1) the method is generalised to accurately model any nanofluidic network of connected channels, regardless of its size or complexity; 2) by generalising the application of constraints, the geometry or governing pressures can be the output of the method, enabling the design of networks without the need for a costly trial-and-error process. For a variety of constraint combinations, it is shown that the hybrid method converges quickly to the solution of a full molecular dynamics simulation, with relative errors of < 4% for all variables across all cases. Network design is further advanced by the development of a generalised optimisation principle that finds the daughter-parent area ratio maximising flow conductance per unit volume in all branches. Through numerically verified analytical models, it is demonstrated that the common branching principle `Murray's law' is sub-optimal for asymmetric branching (where the local optimisation of each individual channel does not correspond to the global optimum for the network as a whole), while the generalised law presented in this thesis is valid for 1) symmetric and asymmetric branching, 2) slip and plug fl flows, which occur at very small scales, and 3) any cross-sectional shape; making it a powerful tool for nanofluidic biomimetic modelling.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:675383 |
| Date | January 2015 |
| Creators | Stephenson, David |
| Publisher | University of Warwick |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://wrap.warwick.ac.uk/74103/ |
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