PhD Dissertation Defense:Merve Senem Avaz
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Merve Senem Avaz
Materials Science and Nano Engineering, PhD Dissertation, 2017


Thesis Jury

Prof. Yusuf Ziya Menceloğlu (Thesis Advisor), Prof. Canan Atılgan

, Assoc. Prof. Ayhan Bozkurt, Prof. İ. Ersin Serhatlı, Assoc. Prof. Derya Yüksel İmer



Date&Time: 24.07.2017 & 13:30

Place: FENS G029

Keywords : Chitosan Modification, Freeze concentration, Molecular Imprinting, Graphene, Nanosensor Fabrication, Molecular dynamics simulations, Mesoscale molecular dynamics, Structure-morphology-function relationship





Chitosan shows merit as a biomaterial in medical research particularly in terms of its good biocompatibility, but its poor solubility at physiological pH values narrows its potential scope of use. In this first part of this thesis, a freeze-concentrated chemical modification approach was developed to transform chitosan, yielding derivatives with reduced chain regularity and improved solubility. In confirming the generality of this approach, chitosan solutions spiked with acrylic, citraconic, itaconic, or maleic acid were incubated at -10 °C, transforming primary amino groups to the corresponding Michael type adduct. The purified derivatives were characterized via 13C-NMR, ATR-FTIR, XRD, ninhydrin, solubility measurements, and SEM, with changes in XRD and ninhydrin profiles particularly correlating well with improved solubility. It follows to reason that this approach enhanced processability of challenging or thermally sensitive biopolymers and contribute to the Michael reactions in the sense our method yields the free acid directly, which is in fact another novelty in chitosan research.

In the second part, a molecularly imprinted chitosan and graphene-based nanosensor was fabricated to selectively detect nitrotriazolone (NTO) molecules with a molecularly imprinted film via simple electrical measurements. Molecularly imprinted polymer comprising chitosan was used as sensitive layer. Gold electrodes for electrical measurements were lithographically fabricated on Si/SiO2 substrate, followed by monolayer graphene transfer and polymeric film coating. Monolayer graphene and molecularly imprinted polymer were characterized by ATR-FTIR, UV-Vis, SEM and Raman spectroscopy. Transfer-length measurements (TLM) indicate that the sensor selectively and linearly responds against aqueous NTO solutions within a wide range of concentration of 0.01–0.1 mg mL_1 that covers the lowest toxic level of NTO determined by USEPA. This nanosensor with embedded electrodes is re-usable and suitable for field applications, offering real-time electrical measurements unlike current techniques where complex analytics are required.

Third part of the thesis deals with theoretical investigation of structure-morphology-property relationship in thermoplastic polyurethanes. Soft segment (SS) chain length is known to affect the morphologies and mechanical behavior of poly(ethylene oxide) based-segmented poly(urethane-urea) copolymers in binary solvents. Here, a multi-scale computational study is carried out to determine the origins of this behavior. First, single chains of a series of poly(ethylene oxide) (PEO) of varying lengths are comparatively examined by molecular dynamics (MD) and dissipative particle dynamics (DPD) simulations in THF:DMF mixture to verify that the coarse graining strategy is applicable to the system at hand. In the second step, hard segment (HS) beads containing urethane groups are attached into PEO chains to study the effect of hard segment on morphology. Density fields obtained from DPD calculations results in a stable channel formation of soft segment molecules in the copolymers with the lower soft segment lengths. Morphologies of copolymers with three different soft segment lengths investigated by DPD are followed by reverse mapping to full atomistic detail. Monitoring the trajectories and the reverse mapped structures, we find that urethane-PEO interactions are significantly stronger in copolymer with lowest soft segment length leading to channel formation. The findings are corroborated by atomic force microscopy (AFM) images obtained for the corresponding copolymers. The strategy employed in this work lays the foundations for predicting novel morphologies and macro-properties using designs based on HS-SS cooligomers.