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    Scalable machining of micro-features for orthopedic and tribological applications

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    LIU-THESIS-2016.pdf (4.603Mb)
    Date
    2016-05-18
    Author
    Liu, Ryan
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    Abstract
    Micro-scale surface textures have found profound application in various industrial sectors, including the biomedical and tribological communities. While numerous manufacturing methods are available for the fabrication of these micro-features, advancements in high-precision machinery and piezoelectric actuation have allowed for the development of new and scalable processes for mechanical surface texturing based on modulation-assisted machining. The present study aims to understand the effects of micro-scale surface textures produced by modulation-assisted machining on surface performance in biomedical and tribological configurations. To accomplish this, a predictive geometric model was developed to simulate surfaces generated in multiple mechanical texturing orientations. Experimental studies were carried out to generate controlled surface textures over a range of characteristics in terms of feature size and morphology. The surface performance of the resulting textures in a biomedical implant application were tested for osseointegration capability with in vivo and in vitro tests. For these tests, a bilateral rat tibia model and precursor osteoblast MC3T3-E1 cell culture were used, respectively. Surface performance of the micro-scale surface textures in a tribological application was evaluated using a pin-on-disk wear testing configuration. The results of both studies show promising findings that demonstrate the beneficial effects of surface textures produced by modulation-assisted machining.
    URI
    http://hdl.handle.net/1853/58191
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    • Georgia Tech Theses and Dissertations [23877]
    • School of Mechanical Engineering Theses and Dissertations [4086]

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