Experimental and theoretical study of microstructure effect on piezoelectric property of one dimensional ZnO nanostructures

Emerging nanogenerators have attracted the attention of the research community, focusing on energy generation using piezoelectric nanomaterials. Nanogenerators can be utilized for powering NEMS/MEMS devices. Understanding the piezoelectric properties of ZnO one-dimensional materials such as ZnO nanobelts (NBs) and Nanowires (NWs) can have a significant impact on the design of new devices. The goal of this dissertation is to study the piezoelectric properties of one-dimensional ZnO nanostructures both experimentally and theoretically. First, the experimental procedure for producing the ZnO nanostructures is discussed. The produced ZnO nanostructures were characterized using an in-situ atomic force microscope and a piezoelectric force microscope. It is shown that the electrical conductivity of ZnO NBs is a function of applied mechanical force and its crystalline structure. This phenomenon was described in the context of formation of an electric field due to the piezoelectric property of ZnO NBs. In the PFM studies, it was shown that the piezoelectric response of the ZnO NBs depends on their production method and presence of defects in the NB. Second, a model was proposed for making nanocomposite electrical generators based on ZnO nanowires. The proposed model has advantages over the original configuration of nanogenerators which uses an AFM tip for bending the ZnO NWs. Higher stability of the electric source, capability for producing larger electric fields, and lower production costs are advantages of this configuration. Finally, piezoelectric properties of ZnO NBs were simulated using the molecular dynamics (MD) technique. The size-scale effect on piezoelectric properties of ZnO NBs was captured, and it is shown that the piezoelectric coefficient of ZnO NBs decreases by increasing their lateral dimensions. This phenomenon is attributed to the surface charge redistribution and compression of unit cells that are placed on the outer shell of ZnO NBs.

COMPUTATIONAL STUDY OF MICROSTRUCTURE-PROPERTYMECHANISM RELATIONS IN FERROIC COMPOSITES

Ferroic materials, as notable members of smart materials, have been widely used in applications that perform sensing, actuation and control. The macroscopic property change of ferroic materials may become remarkably large during ferroic phase transition, leading to the fact that the macroscopic properties can be tuned by carefully applying a suitable external field (electric, magnetic, stress). To obtain an enhancement in physical and/or mechanical properties, different kinds of ferroic composites have been fabricated. The properties of a ferroic composite are determined not only by the properties and relative amounts of the constituent phases, but also by the microstructure of individual phase such as the phase connectivity, phase size, shape and spatial arrangement. This dissertation mainly focuses on the computational study of microstructure – property – mechanism relations in two representative ferroic composites, i.e., two-phase particulate magnetoelectric (ME) composite and polymer matrix ferroelectric composite. The former is a great example of ferroic composite exhibiting a new property and functionality that neither of the constituent phases possesses individually. The latter well represents the kind of ferroic composites having property combinations that are better than the existing materials. Phase field modeling was employed as the computing tool, and the required models for ferroic composites were developed based on existing models for monolithic materials. Extensive computational simulations were performed to investigate the microstructure-property relations and the underlying mechanism in ferroic composites. In particulate, it is found that for ME composite 0-3 connectivity (isolated magnetostrictive phase) is necessary to exhibit ME effect, and small but finite electrical conductivity of isolated magnetic phase can beneficially enhance ME effect. It is revealed that longitudinal and transverse ME coefficients of isotropic 0-3 particulate composites can be effectively tailored by controlling magnetic domain structures without resort to anisotropic two-phase microstructures. Simulations also show that the macroscopic properties of the ferroelectricpolymer composites critically depend on the ferroelectric phase connectivity while are not sensitive to the sizes and internal grain structures of the ceramic particles. Texturing is found critical to exploit the paraelectric«ferroelectric phase transition and nonlinear polarization behavior in paraelectric polycrystal and its polymer matrix composite. Additionally, a Diffuse Interface Field model was developed to simulate packing and motion in liquid phase which is promising for studying the fabrication of particulatepolymer composites.

USING AUTO- AND CROSS-CORRELATIONS FROM SEISMIC NOISE TO MONITOR VELOCITY CHANGES AT VILLARRICA VOLCANO, CHILE

We used the Green's functions from auto-correlations and cross-correlations of seismic ambient noise to monitor temporal velocity changes in the subsurface at Villarrica volcano in the Southern Andes of Chile. Campaigns were conducted from March to October 2010 and February to April 2011 with 8 broadband and 6 short-period stations, respectively. We prepared the data by removing the instrument response, normalizing with a root-mean-square method, whitening the spectra, and filtering from 1 to 10 Hz. This frequency band was chosen based on the relatively high background noise level in that range. Hour-long auto- and cross-correlations were computed and the Green's functions stacked by day and total time. To track the temporal velocity changes we stretched a 24 hour moving window of correlation functions from 90% to 110% of the original and cross correlated them with the total stack. All of the stations' auto-correlations detected what is interpreted as an increase in velocity in 2010, with an average increase of 0.13%. Cross-correlations from station V01, near the summit, to the other stations show comparable changes that are also interpreted as increases in velocity. We attribute this change to the closing of cracks in the subsurface due either to seasonal snow loading or regional tectonics. In addition to the common increase in velocity across the stations, there are excursions in velocity on the same order lasting several days. Amplitude decreases as the station's distance from the vent increases suggesting these excursions may be attributed to changes within the volcanic edifice. In at least two occurrences the amplitudes at stations V06 and V07, the stations farthest from the vent, are smaller. Similar short temporal excursions were seen in the auto-correlations from 2011, however, there was little to no increase in the overall velocity.

White matter microstructure alterations of the medial forebrain bundle in melancholic depression

BACKGROUND The medial forebrain bundle (MFB) is a key structure of the reward system and connects the ventral tegmental area (VTA) with the nucleus accumbens (NAcc), the medial and lateral orbitofrontal cortex (mOFC, lOFC) and the dorsolateral prefrontal cortex (dlPFC). Previous diffusion tensor imaging (DTI) studies in major depressive disorder point to white matter alterations of regions which may be incorporated in the MFB. Therefore, it was the aim of our study to probe white matter integrity of the MFB using a DTI-based probabilistic fibre tracking approach. METHODS 22 patients with major depressive disorder (MDD) (12 melancholic-MDD patients, 10 non-melancholic-MDD patients) and 21 healthy controls underwent DTI scans. We used a bilateral probabilistic fibre tracking approach to extract pathways between the VTA and NACC, mOFC, lOFC, dlPFC respectively. Mean fractional anisotropy (FA) values were used to compare structural connectivity between groups. RESULTS Mean-FA did not differ between healthy controls and all MDD patients. Compared to healthy controls melancholic MDD-patients had reduced mean-FA in right VTA-lOFC and VTA-dlPFC connections. Furthermore, melancholic-MDD patients had lower mean-FA than non-melancholic MDD-patients in the right VTA-lOFC connection. Mean-FA of these pathways correlated negatively with depression scale rating scores. LIMITATIONS Due to the small sample size and heterogeneous age group comparisons between melancholic and non-melancholic MDD-patients should be regarded as preliminary. CONCLUSIONS Our results suggest that the melancholic subtype of MDD is characterized by white matter microstructure alterations of the MFB. White matter microstructure is associated with both depression severity and anhedonia.