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Title: Exploring stability landscapes for optimal material design : application to wetting of structured surfaces
Author: Panter, Jack Ramon
ISNI:       0000 0004 8509 3911
Awarding Body: Durham University
Current Institution: Durham University
Date of Award: 2019
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Nature exhibits a diverse and sophisticated range of complex surface micro- and nanostructures which are highly adapted to manipulating liquids. Many exhibit surfaces which are efficient at shedding even wetting or pressurised liquids, self-cleaning, anti-fouling, antimicrobial, abrasion-resistant or able to produce strongly directional liquid motion; properties which are immensely desirable across a broad range of applications, from water purification to absorbent wipes. Here, optimised surface designs are produced for two wetting applications: superomniphobic surfaces for liquid-repellency, and enclosed fluid diodes for directional flow. In the superomniphobic investigation, we study three key wetting properties: the minimum energy barrier to the breakdown of liquid-repellency, the contact angle hysteresis (liquid mobility), and the critical pressure (maximum sustainable liquid pressure). We then treat all three properties simultaneously to produce optimal superomniphobic designs. In the fluid diode investigation, we study the critical pressures required for liquid to flow into and out of a membrane pore with both chemical and physical gradients. We then maximise the contrast between these two critical pressures, to design pores with optimal liquid directionality. Previously, two major hurdles have existed to such optimal design. The first is that the wetting properties on complex surface structures feature multiple competing mechanisms, which previously have been inefficient or expensive to investigate. In this thesis, we overcome this by employing and developing computationally efficient, high-dimensional energy landscape methods. The second is that when multiple wetting properties are desired, optimisation of one property can diminish another. We show how this can be overcome through simultaneous optimisation.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available