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https://scholarbank.nus.edu.sg/handle/10635/164592
DC Field | Value | |
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dc.title | MICRO AND NANOSTRUCTURED MATERIALS FOR NEURAL RECORDING AND STIMULATING | |
dc.contributor.author | CHEN NUAN | |
dc.date.accessioned | 2020-02-17T18:00:31Z | |
dc.date.available | 2020-02-17T18:00:31Z | |
dc.date.issued | 2019-08-21 | |
dc.identifier.citation | CHEN NUAN (2019-08-21). MICRO AND NANOSTRUCTURED MATERIALS FOR NEURAL RECORDING AND STIMULATING. ScholarBank@NUS Repository. | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/164592 | |
dc.description.abstract | During the past decades, neural electrodes have attracted great interest due to their potential of direct communication with neural tissue for various diagnostic and therapeutic applications. In this thesis, coatings made of poly(3,4-ethylenedioxythiophene) (PEDOT) and carbon nanotube (CNT), enriched with micro- and nanotubular structures and surface functionalization, were developed as an effective and stable intermediate layer between the electrode and the native tissue for neural recording and stimulating. The PEDOT-CNT tubular coating showed good electroactivity, adhesion to the electrode and biocompatibility. The employment of the coating supported neural recording and stimulating at the cell-electrode interface, with high-quality recording and decoding of neural signals from different stimuli and modulation on neural cell growth, respectively. Overall, the findings indicate that the PEDOT-CNT tubular coatings will be a promising strategy to improve the efficacy and durability of the neural electrode. | |
dc.language.iso | en | |
dc.subject | neural interface, electrode coating, carbon, conducting polymer, nanotechnology, functionalization | |
dc.type | Thesis | |
dc.contributor.department | MECHANICAL ENGINEERING | |
dc.contributor.supervisor | Seeram Ramakrishna | |
dc.contributor.supervisor | Thakor, Nitish Vyomesh | |
dc.description.degree | Ph.D | |
dc.description.degreeconferred | DOCTOR OF PHILOSOPHY (FOE) | |
Appears in Collections: | Ph.D Theses (Open) |
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ChenN.pdf | 5.37 MB | Adobe PDF | OPEN | None | View/Download |
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